[Udemy] Complete 2-in-1 Python for Business and Finance Bootcamp [EN]

磁力链接/BT种子名称

[Udemy] Complete 2-in-1 Python for Business and Finance Bootcamp [EN]

磁力链接/BT种子简介

种子哈希：934626ad49c7839a7104ac1f371e832c5d6dc9be
文件大小： 10.97G
已经下载：1596次
下载速度：极快
收录时间：2022-01-15
最近下载：2024-12-05

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:934626AD49C7839A7104AC1F371E832C5D6DC9BE
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 暗网禁地 91短视频 TikTok成人版 PornHub 草榴社区 乱伦社区

最近搜索

文件列表

  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/100 Statistics - Overview Terms and Vocabulary.mp4 100.4 MB
  • 24 Managing Time Series and Financial Data with Pandas/284 Creating a customized DatetimeIndex with pd.date_range().mp4 98.2 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/249 Customization of Plots.mp4 88.2 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.mp4 85.3 MB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/068 Customizing Plots (Part 2).mp4 84.3 MB
  • 20 Pandas Basics - Starting from Zero/210 Slicing Rows and Columns with loc (label-based indexing).mp4 84.2 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/378 Detecting and Handling Serial Correlation (Autocorrelation).mp4 83.2 MB
  • 24 Managing Time Series and Financial Data with Pandas/303 Importing Financial Data from Excel.mp4 81.6 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/316 Coding Exercise 13 (Solution).mp4 81.5 MB
  • 23 Pandas Advanced/267 Adding new Rows to a DataFrame.mp4 79.9 MB
  • 08 The Numpy Package Working with numbers made easy/083 Coding Exercise 7.mp4 76.7 MB
  • 21 Pandas Intermediate/246 Coding Exercise 6 (Solution).mp4 76.4 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/310 Creating many random Portfolios with Python.mp4 76.0 MB
  • 24 Managing Time Series and Financial Data with Pandas/288 Downsampling Time Series with resample() (Part 1).mp4 75.7 MB
  • 01 Getting Started/003 How to download and install Anaconda for Python coding.mp4 74.4 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/319 The Portfolio Diversification Effect.mp4 74.4 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/254 Categorical Seaborn Plots.mp4 74.2 MB
  • 17 How to create your own user-defined Functions/179 Putting it all together - Case Study.mp4 72.6 MB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/197 Download of Part 4 Course Materials.mp4 71.7 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/373 Detecting and Handling Outliers (Part 1).mp4 71.3 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/192 Dynamic path-dependent Simulations (Part 2).mp4 70.7 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/255 Seaborn Regression Plots.mp4 69.7 MB
  • 23 Pandas Advanced/277 stack() and unstack().mp4 69.3 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/194 Dynamic path-dependent Simulations (Part 4).mp4 68.7 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/365 Single-Factor Models with the Fama-French Market Portfolio (Part 1).mp4 66.7 MB
  • 21 Pandas Intermediate/226 Changing Row Index with set_index() and reset_index().mp4 66.1 MB
  • 21 Pandas Intermediate/239 Coding Exercise 5 (Solution).mp4 66.0 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/377 Detecting and Correcting Heteroskedasticity.mp4 64.3 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/060 Solving for a Project s IRR.mp4 63.7 MB
  • 21 Pandas Intermediate/217 Analyzing Numerical Series with unique() nunique() and value_counts().mp4 63.6 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/320 Systematic vs. unsystematic Risk.mp4 62.4 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/128 Probabilities and Z-Values with scipy.stats.mp4 62.2 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/326 Coding Exercise 14 (Solution).mp4 62.1 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/248 Visualization with Matplotlib (Intro).mp4 62.0 MB
  • 23 Pandas Advanced/275 split-apply-combine applied.mp4 62.0 MB
  • 24 Managing Time Series and Financial Data with Pandas/295 Importing Stock Price Data from Yahoo Finance (it still works).mp4 61.3 MB
  • 21 Pandas Intermediate/219 EXCURSUS Updating Pandas Anaconda.mp4 61.2 MB
  • 21 Pandas Intermediate/241 Handling NA Values missing Values.mp4 59.0 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/063 Coding Exercise 5.mp4 58.5 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/368 How to create a Fama-French Three-Factor Model.mp4 58.1 MB
  • 21 Pandas Intermediate/236 Advanced Filtering with between() isin() and ~.mp4 57.1 MB
  • 29 Multiple Regression Models/361 Creating and working with Dummy Variables (Part 1).mp4 57.0 MB
  • 20 Pandas Basics - Starting from Zero/212 Summary and Outlook.mp4 56.9 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/258 Coding Exercise 7 (Solution).mp4 56.7 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/046 Coding Exercise 3.mp4 56.4 MB
  • 20 Pandas Basics - Starting from Zero/199 First Steps (Inspection of Data Part 1).mp4 56.4 MB
  • 29 Multiple Regression Models/359 Regression Coefficients Hypothesis Testing Model Specification.mp4 56.2 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/349 Confidence Intervals for Regression Coefficients - Bootstrapping.mp4 56.1 MB
  • 01 Getting Started/005 How to work with Jupyter Notebooks.mp4 56.1 MB
  • 23 Pandas Advanced/263 Arithmetic Operations (Part 1).mp4 55.3 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/146 Two-tailed Z-Test with known Population Variance.mp4 55.3 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/364 Fama-French An Introduction.mp4 55.1 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/187 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 3).mp4 53.5 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/145 Hypothesis Testing (Theory).mp4 53.4 MB
  • 01 Getting Started/004 Jupyter Notebooks - let s get started.mp4 53.4 MB
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/327 Introduction to Regression Analysis.mp4 53.1 MB
  • 29 Multiple Regression Models/356 Movies Dataset - Preparing the Data.mp4 52.0 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/153 Testing for Normality of Financial Returns with scipy.stats.mp4 51.9 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/367 The Factors Size Value.mp4 51.5 MB
  • 24 Managing Time Series and Financial Data with Pandas/281 Converting strings to datetime objects with pd.to_datetime().mp4 51.2 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/344 OLS Regression with statsmodels - Intro.mp4 51.2 MB
  • 23 Pandas Advanced/264 Arithmetic Operations (Part 2).mp4 51.1 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/376 Detecting and Handling Multicollinearity.mp4 50.9 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/129 Confidence Intervals with scipy.stats.mp4 50.5 MB
  • 23 Pandas Advanced/270 Coding Exercise 8 (Solution).mp4 50.2 MB
  • 24 Managing Time Series and Financial Data with Pandas/306 Coding Exercise 12 (Solution).mp4 50.1 MB
  • 27 Correlation and Regression/330 Cleaning and preparing the Data - Movies Database (Part 1).mp4 49.3 MB
  • 21 Pandas Intermediate/243 Summary Statistics and Accumulations.mp4 49.2 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/019 Coding Exercise 1.mp4 49.1 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/370 How to create a Fama-French Five-Factor Model.mp4 48.8 MB
  • 20 Pandas Basics - Starting from Zero/206 Selecting Rows with iloc (position-based indexing).mp4 48.1 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/309 Creating the equally-weighted Portfolio.mp4 48.0 MB
  • 24 Managing Time Series and Financial Data with Pandas/301 Financial Time Series - Return and Risk.mp4 47.1 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/312 Portfolio Analysis and the Sharpe Ratio with Python.mp4 47.0 MB
  • 21 Pandas Intermediate/233 Filtering DataFrames (one Condition).mp4 47.0 MB
  • 21 Pandas Intermediate/231 Sorting DataFrames with sort_index() and sort_values().mp4 46.4 MB
  • 29 Multiple Regression Models/362 Creating and working with Dummy Variables (Part 2).mp4 46.1 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/103 Population vs. Sample.mp4 46.0 MB
  • 20 Pandas Basics - Starting from Zero/201 Built-in Functions Attributes and Methods.mp4 46.0 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/186 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 2).mp4 45.6 MB
  • 23 Pandas Advanced/265 Creating DataFrames from Scratch with pd.DataFrame().mp4 45.5 MB
  • 20 Pandas Basics - Starting from Zero/214 Coding Exercise 2 (Solution).mp4 45.1 MB
  • 20 Pandas Basics - Starting from Zero/200 First Steps (Inspection of Data Part 2).mp4 44.9 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/054 Coding Exercise 4.mp4 44.4 MB
  • 23 Pandas Advanced/273 Splitting with many Keys.mp4 44.3 MB
  • 24 Managing Time Series and Financial Data with Pandas/291 Advanced Indexing with reindex().mp4 44.2 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/188 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 1).mp4 44.0 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/191 Dynamic path-dependent Simulations (Part 1).mp4 43.6 MB
  • 24 Managing Time Series and Financial Data with Pandas/289 Downsampling Time Series with resample (Part 2).mp4 43.5 MB
  • 23 Pandas Advanced/261 Removing Rows.mp4 43.4 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/097 Capital Budgeting - Mutually exclusive Projects (Part 2).mp4 43.0 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/049 Intro to Strings.mp4 42.8 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/381 Logistic Regression with statsmodels (Part 2).mp4 42.7 MB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/069 Plotting NPV IRR.mp4 42.7 MB
  • 24 Managing Time Series and Financial Data with Pandas/283 Indexing and Slicing Time Series.mp4 42.6 MB
  • 23 Pandas Advanced/274 split-apply-combine.mp4 42.0 MB
  • 27 Correlation and Regression/338 A simple Linear Regression Model with numpy Scipy.mp4 41.6 MB
  • 23 Pandas Advanced/272 Understanding the GroupBy Object.mp4 41.3 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/056 Keywords pass continue and break.mp4 41.3 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/321 Capital Asset Pricing Model (CAPM) Security Market Line (SLM).mp4 41.1 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).mp4 41.0 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/093 Mortgage Loan Analysis - Debt Sizing.mp4 41.0 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/313 Finding the Optimal Portfolio.mp4 41.0 MB
  • 27 Correlation and Regression/335 Creating a Confidence Interval for the Correlation Coefficient (Bootstrapping).mp4 40.8 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/150 Two-tailed t-Test (unknown Population Variance).mp4 40.7 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/126 The Standard Normal Distribution and Z-Values.mp4 40.5 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/055 Conditional Statements.mp4 40.5 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/043 Adding and removing Elements fromto Lists.mp4 40.4 MB
  • 24 Managing Time Series and Financial Data with Pandas/287 Coding Exercise 10 (Solution).mp4 40.3 MB
  • 24 Managing Time Series and Financial Data with Pandas/293 Coding Exercise 11 (Solution).mp4 40.1 MB
  • 21 Pandas Intermediate/240 Intro to NA Values missing Values.mp4 40.0 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/029 Coding Exercise 2.mp4 39.8 MB
  • 08 The Numpy Package Working with numbers made easy/082 Creating Numpy Arrays from Scratch.mp4 39.7 MB
  • 23 Pandas Advanced/279 Coding Exercise 9 (Solution).mp4 39.6 MB
  • 01 Getting Started/001 Tips How to get the most out of this Course (don t skip).mp4 39.4 MB
  • 24 Managing Time Series and Financial Data with Pandas/297 Normalizing Time Series to a Base Value (100).mp4 39.2 MB
  • 21 Pandas Intermediate/225 First Steps with Pandas Index Objects.mp4 39.0 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/061 Bonds and the Yield to Maturity - YTM (Theory).mp4 38.8 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/323 Redefining the Market Portfolio.mp4 38.5 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/105 Relative and Cumulative Frequencies with plt.hist().mp4 38.2 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/345 OLS Regression - ANOVA (Theory).mp4 38.1 MB
  • 17 How to create your own user-defined Functions/171 What s the difference between Positional Arguments vs. Keyword Arguments.mp4 38.1 MB
  • 24 Managing Time Series and Financial Data with Pandas/296 Initial Inspection and Visualization.mp4 38.1 MB
  • 21 Pandas Intermediate/220 Analyzing non-numerical Series with unique() nunique() value_counts().mp4 37.9 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/189 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 2).mp4 37.9 MB
  • 08 The Numpy Package Working with numbers made easy/072 Numpy Arrays.mp4 37.5 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/256 Seaborn Heatmaps.mp4 37.4 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/119 Probability Distributions - Overview.mp4 37.4 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/058 While Loops.mp4 37.4 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/053 Comparison Logical and Membership Operators in Action.mp4 37.2 MB
  • 17 How to create your own user-defined Functions/177 Scope - easily explained.mp4 37.0 MB
  • 24 Managing Time Series and Financial Data with Pandas/300 Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 36.6 MB
  • 20 Pandas Basics - Starting from Zero/203 Explore your own Dataset Coding Exercise 1 (Solution).mp4 36.4 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/044 Mutable vs. immutable Objects (Part 1).mp4 36.2 MB
  • 24 Managing Time Series and Financial Data with Pandas/280 Importing Time Series Data from csv-files.mp4 36.1 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/131 Sample Statistic Sampling Error and Sampling Distribution (Theory).mp4 35.6 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/322 Beta and Alpha.mp4 35.2 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/026 Calculate FV and PV for many Cashflows.mp4 35.2 MB
  • 24 Managing Time Series and Financial Data with Pandas/290 The PeriodIndex object.mp4 35.1 MB
  • 21 Pandas Intermediate/222 Sorting of Series and Introduction to the inplace - parameter.mp4 35.0 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/027 The Net Present Value - NPV (Theory).mp4 34.9 MB
  • 20 Pandas Basics - Starting from Zero/204 Selecting Columns.mp4 34.6 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/085 Evaluating Annuities with np.fv() - Funding Phase.mp4 34.4 MB
  • 24 Managing Time Series and Financial Data with Pandas/299 The methods diff() and pct_change().mp4 34.3 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp4 34.3 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/152 Hypothesis Testing with Bootstrapping.mp4 34.0 MB
  • 08 The Numpy Package Working with numbers made easy/071 Modules Packages and Libraries - No need to reinvent the Wheel.mp4 33.6 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/091 How to evaluate a Retirement Plan A-Z.mp4 33.5 MB
  • 29 Multiple Regression Models/357 Multiple Regression Analysis with statsmodels.mp4 32.8 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/149 One-tailed Z-Test with known Population Variance.mp4 32.7 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/380 Logistic Regression with statsmodels (Part 1).mp4 32.7 MB
  • 27 Correlation and Regression/331 Cleaning and preparing the Data - Movies Database (Part 2).mp4 32.6 MB
  • 21 Pandas Intermediate/224 Coding Exercise 3 (Solution).mp4 32.6 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/048 Dictionaries.mp4 32.5 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/092 Retirement Plan Sensitivity Analysis.mp4 32.2 MB
  • 21 Pandas Intermediate/216 First Steps with Pandas Series.mp4 31.9 MB
  • 02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/006 Overview Download of Course Materials for Part 1.mp4 31.8 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/136 Central Limit Theorem (Coding Part 2).mp4 31.8 MB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/102 Download of Part 2 Course Materials.mp4 31.7 MB
  • 17 How to create your own user-defined Functions/178 How to create Nested Functions.mp4 31.6 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/024 For Loops - Iterating over Lists.mp4 31.4 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/047 Tuples.mp4 31.2 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/142 Student s t-Distribution vs. Normal Distribution with scipy.stats.mp4 31.1 MB
  • 23 Pandas Advanced/260 Removing Columns.mp4 31.1 MB
  • 24 Managing Time Series and Financial Data with Pandas/298 The shift() method.mp4 30.9 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/252 Scatterplots.mp4 30.9 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/185 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 1).mp4 30.9 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/353 Case Study (Part 3) The Market Model (Single Factor Model).mp4 30.3 MB
  • 24 Managing Time Series and Financial Data with Pandas/282 Initial Analysis Visualization of Time Series.mp4 30.3 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/159 How to slice 2-dim Numpy Arrays (Part 1).mp4 30.3 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/251 Histogramms (Part 2).mp4 30.3 MB
  • 17 How to create your own user-defined Functions/172 How to work with Default Arguments.mp4 29.9 MB
  • 08 The Numpy Package Working with numbers made easy/080 Advanced Filtering Bitwise Operators.mp4 29.7 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/120 Discrete Uniform Distributions.mp4 29.6 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/143 Bootstrapping with Python an alternative method without Statistics.mp4 29.4 MB
  • 21 Pandas Intermediate/228 Renaming Index Column Labels with rename().mp4 29.4 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/110 Variability around the Central Tendency Dispersion (Theory).mp4 29.0 MB
  • 27 Correlation and Regression/332 Covariance and Correlation Coefficient (Theory).mp4 28.9 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/165 Arithmetic Vectorized Operations with 2-dim Numpy Arrays.mp4 28.8 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/115 How to calculate Skew and Kurtosis with scipy.stats.mp4 28.8 MB
  • 17 How to create your own user-defined Functions/170 Defining your first user-defined Function.mp4 28.7 MB
  • 23 Pandas Advanced/276 Hierarchical Indexing with Groupby.mp4 28.3 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4 28.2 MB
  • 17 How to create your own user-defined Functions/173 The Default Argument None.mp4 28.1 MB
  • 21 Pandas Intermediate/232 nunique() and nlargest() nsmallest() with DataFrames.mp4 28.0 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/140 Unknown Population Variance - the Standard Case (Example 1).mp4 27.6 MB
  • 27 Correlation and Regression/340 Case Study (Part 1) The Market Model (Single Factor Model).mp4 27.6 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/135 Central Limit Theorem (Coding Part 1).mp4 27.6 MB
  • 17 How to create your own user-defined Functions/175 Sequences as arguments and args.mp4 27.5 MB
  • 29 Multiple Regression Models/355 Multiple Regression (Theory).mp4 27.2 MB
  • 23 Pandas Advanced/268 Manipulating Elements in a DataFrame.mp4 27.2 MB
  • 24 Managing Time Series and Financial Data with Pandas/304 Merging Aligning Financial Time Series (hands-on).mp4 27.2 MB
  • 21 Pandas Intermediate/235 Filtering DataFrames by many Conditions (OR).mp4 27.1 MB
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/329 Course-Materials-Part5.zip 26.9 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/182 Analyzing the Data past Performance.mp4 26.7 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/033 Build-in Functions.mp4 26.6 MB
  • 20 Pandas Basics - Starting from Zero/209 Selecting Rows with loc (label-based indexing).mp4 26.5 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/117 How to generate Random Numbers with Numpy.mp4 26.4 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/163 Reshaping and Transposing 2-dim Numpy Arrays.mp4 25.9 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/037 More on Lists.mp4 25.8 MB
  • 08 The Numpy Package Working with numbers made easy/075 Changing Elements in Numpy Arrays Mutability.mp4 25.7 MB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/067 Customizing Plots (Part 1).mp4 25.6 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/086 Evaluating Annuities with np.fv() - Payout Phase.mp4 25.6 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/030 Data Types in Action.mp4 25.5 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/035 Floats.mp4 25.5 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/372 Linear Regression - not that easy.mp4 25.4 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/123 Creating a normally distributed Random Variable.mp4 25.3 MB
  • 27 Correlation and Regression/333 How to calculate Covariance and Correlation in Python.mp4 25.2 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/059 The Internal Rate of Return - IRR (Theory).mp4 25.1 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/183 How to use the Parametric Method to calculate Value-at-Risk (VaR).mp4 25.0 MB
  • 21 Pandas Intermediate/230 Coding Exercise 4 (Solution).mp4 24.6 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).mp4 24.6 MB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/065 Line Plots.mp4 24.5 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/314 Sharpe Ratio - visualized and explained.mp4 24.4 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/096 Capital Budgeting - Mutually exclusive Projects (Part 1).mp4 24.2 MB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/198 Tabular Data and Pandas DataFrames.mp4 24.1 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/104 Visualizing Frequency Distributions with plt.hist().mp4 23.7 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/375 Non-Linear Relationships - Feature Transformation.mp4 23.7 MB
  • 08 The Numpy Package Working with numbers made easy/081 Determining a Project s Payback Period with np.where().mp4 23.6 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/162 How to perform row-wise and column-wise Operations.mp4 23.6 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/107 Coding Measures of Central Tendency - Mean and Median.mp4 23.4 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/084 Evaluating Investments with np.npv() and np.irr().mp4 23.3 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/016 More on Variables and Memory.mp4 23.3 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/148 Calculating and interpreting z-statistic and p-value with scipy.stats.mp4 23.3 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/348 OLS Regression with statsmodels and DataFrames.mp4 23.1 MB
  • 08 The Numpy Package Working with numbers made easy/077 Numpy Array Methods and Attributes.mp4 23.0 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/057 Calculate a Project s Payback Period.mp4 22.9 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/045 Mutable vs. immutable Objects (Part 2).mp4 22.9 MB
  • 30 Case Study Multi-Factor Models (Fama-French)/369 The Factors Profitability and Investment.mp4 22.9 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/090 Frequency of compounding and the effective annual interest rate.mp4 22.9 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/133 Sampling Distribution.mp4 22.6 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/374 Detecting and Handling Outliers (Part 2).mp4 22.6 MB
  • 21 Pandas Intermediate/234 Filtering DataFrames by many Conditions (AND).mp4 22.3 MB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/101 Coding Projects Part 2 - Overview.mp4 22.1 MB
  • 24 Managing Time Series and Financial Data with Pandas/302 Financial Time Series - Covariance and Correlation.mp4 22.1 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/352 Regression Analysis with statsmodels - the Summary Table.mp4 22.0 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/036 How to round Floats (and Integers) with round().mp4 21.9 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/166 The keepdims parameter.mp4 21.8 MB
  • 21 Pandas Intermediate/221 The copy() method.mp4 21.8 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/106 Measures of Central Tendency (Theory).mp4 21.7 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/132 Sampling with np.random.choice().mp4 21.6 MB
  • 20 Pandas Basics - Starting from Zero/207 Slicing Rows and Columns with iloc (position-based indexing).mp4 21.6 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/250 Histogramms (Part 1).mp4 21.5 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/181 What is the Value-at-Risk (VaR) (Theory).mp4 21.4 MB
  • 29 Multiple Regression Models/360 How to test the Significance of the Model as a whole (F-Test).mp4 21.3 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/139 The Student s t-distribution What is it and whywhen do we use it.mp4 21.1 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/039 Slicing Lists.mp4 21.1 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/121 Continuous Uniform Distributions.mp4 21.1 MB
  • 27 Correlation and Regression/334 Correlation and Scatterplots visual Interpretation.mp4 21.0 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/190 Conditional Value-at-Risk (CVaR).mp4 20.4 MB
  • 08 The Numpy Package Working with numbers made easy/076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp4 20.2 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/012 Calculate Interest Rates and Returns with Python.mp4 20.2 MB
  • 15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/156 Coding Projects Part 3 - Overview.mp4 19.8 MB
  • 21 Pandas Intermediate/244 The agg() method.mp4 19.8 MB
  • 20 Pandas Basics - Starting from Zero/205 Selecting Rows with Square Brackets (not advisable).mp4 19.7 MB
  • 08 The Numpy Package Working with numbers made easy/074 Vectorized Operations with Numpy Arrays.mp4 19.6 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/168 Merging and Concatenating Numpy Arrays.mp4 19.6 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/098 Capital Budgeting - Mutually exclusive Projects (Part 3).mp4 19.6 MB
  • 17 How to create your own user-defined Functions/174 How to unpack Iterables.mp4 19.5 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/122 The Normal Distribution (Theory).mp4 19.3 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/157 How to work with nested Lists.mp4 19.1 MB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/253 First Steps with Seaborn.mp4 19.1 MB
  • 08 The Numpy Package Working with numbers made easy/079 Boolean Arrays and Conditional Filtering.mp4 19.0 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/013 Introduction to Variables.mp4 19.0 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/114 Skew and Kurtosis (Theory).mp4 18.9 MB
  • 21 Pandas Intermediate/227 Changing Column Labels.mp4 18.8 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/346 OLS Regression with Statsmodels - ANOVA.mp4 18.7 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/141 Unknown Population Variance - the Standard Case (Example 2).mp4 18.7 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/351 Hypothesis Testing of Regression Coefficients with statsmodels.mp4 18.6 MB
  • 08 The Numpy Package Working with numbers made easy/078 Numpy Universal Functions.mp4 18.6 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/193 Dynamic path-dependent Simulations (Part 3).mp4 18.6 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/038 Lists and Element-wise Operations.mp4 18.4 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/112 Percentiles with PythonNumpy.mp4 18.4 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/018 The print() Function.mp4 18.3 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/050 String Replacement.mp4 18.1 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/118 Reproducibility with np.random.seed().mp4 18.1 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/307 Intro.mp4 18.1 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/025 The range Object - another Iterable.mp4 17.9 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/017 Variables - Dos Don ts and Conventions.mp4 17.9 MB
  • 23 Pandas Advanced/266 Adding new Rows (Hands-on).mp4 17.8 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/137 Central Limit Theorem (Theory).mp4 17.8 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/164 Creating 2-dim Numpy Arrays from Scratch.mp4 17.7 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/311 What is the Sharpe Ratio and a Risk Free Asset.mp4 17.7 MB
  • 27 Correlation and Regression/336 Testing for Correlation (t-Test).mp4 17.4 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/108 Coding Measures of Central Tendency - Geometric Mean.mp4 17.4 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/161 Recap Changing Elements in a Numpy Array slice.mp4 17.3 MB
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/328 Coding Projects Part 5 - Overview.mp4 17.3 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/167 Adding Removing Elements.mp4 17.3 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/008 Intro to the Time Value of Money (TVM) Concept (Theory).mp4 17.3 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/113 Variance and Standard Deviation with PythonNumpy.mp4 17.1 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/158 2-dimensional Numpy Arrays.mp4 16.9 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/318 Capital Market Line (CML) Two-Fund-Theorem.mp4 16.6 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/087 How to solve for annuity payments with np.pmt().mp4 16.5 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/151 One-tailed t-Test (unknown Population Variance).mp4 16.3 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/350 Hypothesis Testing of Regression Coefficients (Theory).mp4 16.3 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4 16.1 MB
  • 02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/007 Coding Projects Part 1 - Overview.mp4 16.1 MB
  • 24 Managing Time Series and Financial Data with Pandas/294 Getting Ready (Installing required library).mp4 16.1 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/089 How to calculate the required Contract Value with np.pv().mp4 16.0 MB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/379 Logistic Regression (Theory).mp4 15.8 MB
  • 23 Pandas Advanced/262 Adding new Columns to a DataFrame.mp4 15.8 MB
  • 29 Multiple Regression Models/358 Coefficient of Determination (Adjusted R squared).mp4 15.8 MB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/127 Properties of the Standard Normal Distribution (Theory).mp4 15.6 MB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/064 Intro.mp4 15.2 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/028 Calculate an Investment Project s NPV.mp4 15.0 MB
  • 21 Pandas Intermediate/237 any() and all().mp4 14.9 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/011 Interest Rates and Returns (Theory).mp4 14.9 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/023 Indexing Lists.mp4 14.5 MB
  • 08 The Numpy Package Working with numbers made easy/073 Indexing and Slicing Numpy Arrays.mp4 14.3 MB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/184 How to use the Historical Method to calculate Value-at-Risk (VaR).mp4 14.3 MB
  • 17 How to create your own user-defined Functions/176 How to return many results.mp4 14.1 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/042 Sorting and Reversing Lists.mp4 13.8 MB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/147 What is the p-value (Theory).mp4 13.7 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/009 Calculate Future Values (FV) with Python Compounding.mp4 13.4 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/088 How to solve for the number of periodic payments with np.nper().mp4 13.3 MB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/062 Solving for a Bond s Yield to Maturity (YTM).mp4 13.1 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/109 Excursus Why Log Returns are useful.mp4 13.0 MB
  • 27 Correlation and Regression/339 How to interpret Intercept and Slope Coefficient.mp4 12.9 MB
  • 11 How to perform Descriptive Statistics on Populations and Samples/111 Minimum Maximum and Range with PythonNumpy.mp4 12.9 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/308 Getting the Data.mp4 12.8 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/052 Operators (Theory).mp4 12.3 MB
  • 27 Correlation and Regression/337 What is Linear Regression (Theory).mp4 12.2 MB
  • 15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/155 Overview Download of Course Materials for Part 3.mp4 11.8 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/015 Excursus How to add inline comments.mp4 11.8 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/034 Integers.mp4 11.5 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/031 The Data Type Hierarchy (Theory).mp4 11.3 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/134 Standard Error.mp4 11.2 MB
  • 21 Pandas Intermediate/242 Exporting DataFrames to csv.mp4 11.1 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/020 TVM Problems with many Cashflows.mp4 11.0 MB
  • 27 Correlation and Regression/341 Case Study (Part 2) The Market Model (Single Factor Model).mp4 10.8 MB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.mp4 10.6 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/041 Changing Elements in Lists.mp4 10.6 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/010 Calculate Present Values (FV) with Python Discounting.mp4 10.5 MB
  • 24 Managing Time Series and Financial Data with Pandas/285 More on pd.date_range().mp4 10.2 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/051 Booleans.mp4 9.3 MB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/160 How to slice 2-dim Numpy Arrays (Part 2).mp4 9.2 MB
  • 23 Pandas Advanced/271 Introduction to GroupBy Operations.mp4 8.5 MB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/317 Intro CAPM.mp4 8.4 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/021 Intro to Python Lists.mp4 8.1 MB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/022 Zero-based Indexing and negative Indexing in Python (Theory).mp4 7.8 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/343 OLS (Ordinary Least Squares) Regression (Theory).mp4 7.6 MB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/066 Scatter Plots.mp4 7.6 MB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/196 Introduction.mp4 7.5 MB
  • 28 OLS Regression ANOVA and Hypothesis Testing/347 Coefficient of Determination (R squared).mp4 7.2 MB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/014 Variables and Memory (Theory).mp4 5.7 MB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/197 Course-Materials-Part4.zip 5.5 MB
  • 05 100 Python Objects Data Types Operators Functional Programming/032 Excursus Dynamic Typing in Python.mp4 5.4 MB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/100 Overview.pdf 1.0 MB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/131 Sampling.pdf 792.4 kB
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/328 Coding-Projects-Part5.pdf 651.9 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/139 studentsT.pdf 582.8 kB
  • 02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/007 Python-for-Finance-Projects-Part1.pdf 525.1 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/145 Hypothesis.pdf 519.5 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/119 Prob-distr.pdf 489.5 kB
  • 15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/156 Coding-Projects-Part3.pdf 475.0 kB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/101 Python-for-Finance-Projects-Part2.pdf 473.9 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/114 skew-kurtosis.pdf 435.3 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/122 Normal.pdf 422.3 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/127 standard-normal.pdf 403.4 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/147 p-value.pdf 353.8 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/137 central-limit-th.pdf 349.3 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/364 Fama-French.pdf 329.9 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/106 Central-tend.pdf 306.4 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/110 Dispersion.pdf 306.1 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/345 ANOVA.pdf 273.5 kB
  • 02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/006 Course-Materials-Part1.zip 258.3 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/181 Value-at-Risk.pdf 257.4 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/027 NPV.pdf 251.6 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/059 IRR.pdf 248.8 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/379 Logistic-Regression.pdf 245.6 kB
  • 27 Correlation and Regression/332 Cov-Corr.pdf 233.6 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/098 Capital-budgeting.pdf 228.2 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/350 Testing.pdf 227.9 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/008 TVM.pdf 200.5 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/026 PV-FV-many.pdf 199.2 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/369 Profitability-Investment.pdf 194.7 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/367 Size-Value.pdf 193.4 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/011 Interest-Rates.pdf 192.3 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/085 Annuity.pdf 191.5 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/061 Bonds-YTM.pdf 182.9 kB
  • 27 Correlation and Regression/339 Coeff.pdf 182.0 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/020 FV-many.pdf 180.2 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/045 Mutability.pdf 170.5 kB
  • 29 Multiple Regression Models/355 Multiple-Reg.pdf 167.9 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/031 Type-Hierarchy.pdf 166.3 kB
  • 29 Multiple Regression Models/360 F-Test.pdf 159.4 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/093 Mortgage.pdf 156.5 kB
  • 27 Correlation and Regression/337 Regression.pdf 153.8 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/343 OLS.pdf 151.4 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/052 Operators.pdf 149.1 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/014 Variables.pdf 146.4 kB
  • 29 Multiple Regression Models/358 Rsquared-adjusted.pdf 135.2 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/022 Indexing.pdf 125.8 kB
  • 08 The Numpy Package Working with numbers made easy/076 Slicing-arrays.pdf 125.5 kB
  • 08 The Numpy Package Working with numbers made easy/075 Mutability-arrays.pdf 124.7 kB
  • 27 Correlation and Regression/334 Visual.pdf 121.4 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/040 Slicing-cheatsheet.pdf 107.8 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/190 CVaR.pdf 101.5 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/033 Built-in-func.pdf 94.8 kB
  • 15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/155 Course-Materials-Part3.zip 94.6 kB
  • 20 Pandas Basics - Starting from Zero/208 pandas-iloc.pdf 73.7 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/017 keywords.pdf 71.1 kB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/102 Course-Materials-Part2.zip 70.8 kB
  • 20 Pandas Basics - Starting from Zero/211 Pandas-loc.pdf 69.4 kB
  • 24 Managing Time Series and Financial Data with Pandas/284 Creating a customized DatetimeIndex with pd.date_range().en.srt 18.5 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/254 Categorical Seaborn Plots.en.srt 17.5 kB
  • 01 Getting Started/005 How to work with Jupyter Notebooks.en.srt 17.3 kB
  • 23 Pandas Advanced/277 stack() and unstack().en.srt 17.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/288 Downsampling Time Series with resample() (Part 1).en.srt 16.7 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/364 Fama-French An Introduction.en.srt 16.5 kB
  • 23 Pandas Advanced/267 Adding new Rows to a DataFrame.en.srt 16.0 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/319 The Portfolio Diversification Effect.en.srt 15.5 kB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/100 Statistics - Overview Terms and Vocabulary.en.srt 15.4 kB
  • 21 Pandas Intermediate/217 Analyzing Numerical Series with unique() nunique() and value_counts().en.srt 15.1 kB
  • 23 Pandas Advanced/263 Arithmetic Operations (Part 1).en.srt 15.1 kB
  • 23 Pandas Advanced/264 Arithmetic Operations (Part 2).en.srt 14.8 kB
  • 23 Pandas Advanced/275 split-apply-combine applied.en.srt 14.6 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/320 Systematic vs. unsystematic Risk.en.srt 14.5 kB
  • 17 How to create your own user-defined Functions/179 Putting it all together - Case Study.en.srt 14.3 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/094 Mortgage Loan Analysis - Interest Payments and Amortization Schedule.en.srt 14.2 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/255 Seaborn Regression Plots.en.srt 14.2 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/249 Customization of Plots.en.srt 14.2 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/378 Detecting and Handling Serial Correlation (Autocorrelation).en.srt 14.1 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/310 Creating many random Portfolios with Python.en.srt 13.8 kB
  • 08 The Numpy Package Working with numbers made easy/083 Coding Exercise 7.en.srt 13.7 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/060 Solving for a Project s IRR.en.srt 13.7 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/046 Coding Exercise 3.en.srt 13.6 kB
  • 21 Pandas Intermediate/241 Handling NA Values missing Values.en.srt 13.4 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/068 Customizing Plots (Part 2).en.srt 13.3 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/192 Dynamic path-dependent Simulations (Part 2).en.srt 13.2 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/128 Probabilities and Z-Values with scipy.stats.en.srt 13.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/303 Importing Financial Data from Excel.en.srt 13.0 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/145 Hypothesis Testing (Theory).en.srt 12.9 kB
  • 21 Pandas Intermediate/233 Filtering DataFrames (one Condition).en.srt 12.8 kB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/197 Download of Part 4 Course Materials.en.srt 12.8 kB
  • 20 Pandas Basics - Starting from Zero/210 Slicing Rows and Columns with loc (label-based indexing).en.srt 12.7 kB
  • 21 Pandas Intermediate/246 Coding Exercise 6 (Solution).en.srt 12.7 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/063 Coding Exercise 5.en.srt 12.6 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/349 Confidence Intervals for Regression Coefficients - Bootstrapping.en.srt 12.5 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/316 Coding Exercise 13 (Solution).en.srt 12.2 kB
  • 20 Pandas Basics - Starting from Zero/199 First Steps (Inspection of Data Part 1).en.srt 12.2 kB
  • 21 Pandas Intermediate/226 Changing Row Index with set_index() and reset_index().en.srt 12.1 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/061 Bonds and the Yield to Maturity - YTM (Theory).en.srt 12.1 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/153 Testing for Normality of Financial Returns with scipy.stats.en.srt 12.1 kB
  • 21 Pandas Intermediate/243 Summary Statistics and Accumulations.en.srt 12.0 kB
  • 23 Pandas Advanced/274 split-apply-combine.en.srt 12.0 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/043 Adding and removing Elements fromto Lists.en.srt 11.9 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/194 Dynamic path-dependent Simulations (Part 4).en.srt 11.9 kB
  • 20 Pandas Basics - Starting from Zero/212 Summary and Outlook.en.srt 11.8 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/187 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 3).en.srt 11.7 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/344 OLS Regression with statsmodels - Intro.en.srt 11.7 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/146 Two-tailed Z-Test with known Population Variance.en.srt 11.7 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/056 Keywords pass continue and break.en.srt 11.7 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/019 Coding Exercise 1.en.srt 11.7 kB
  • 24 Managing Time Series and Financial Data with Pandas/281 Converting strings to datetime objects with pd.to_datetime().en.srt 11.4 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/055 Conditional Statements.en.srt 11.4 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/367 The Factors Size Value.en.srt 11.2 kB
  • 01 Getting Started/004 Jupyter Notebooks - let s get started.en.srt 11.1 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/248 Visualization with Matplotlib (Intro).en.srt 11.1 kB
  • 21 Pandas Intermediate/231 Sorting DataFrames with sort_index() and sort_values().en.srt 11.0 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/345 OLS Regression - ANOVA (Theory).en.srt 11.0 kB
  • 20 Pandas Basics - Starting from Zero/200 First Steps (Inspection of Data Part 2).en.srt 10.9 kB
  • 21 Pandas Intermediate/240 Intro to NA Values missing Values.en.srt 10.9 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/054 Coding Exercise 4.en.srt 10.9 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/373 Detecting and Handling Outliers (Part 1).en.srt 10.9 kB
  • 21 Pandas Intermediate/222 Sorting of Series and Introduction to the inplace - parameter.en.srt 10.8 kB
  • 24 Managing Time Series and Financial Data with Pandas/300 Measuring Stock Performance with MEAN Returns and STD of Returns.en.srt 10.8 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/377 Detecting and Correcting Heteroskedasticity.en.srt 10.8 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/044 Mutable vs. immutable Objects (Part 1).en.srt 10.6 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/256 Seaborn Heatmaps.en.srt 10.5 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/326 Coding Exercise 14 (Solution).en.srt 10.5 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/029 Coding Exercise 2.en.srt 10.4 kB
  • 24 Managing Time Series and Financial Data with Pandas/291 Advanced Indexing with reindex().en.srt 10.4 kB
  • 29 Multiple Regression Models/359 Regression Coefficients Hypothesis Testing Model Specification.en.srt 10.4 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/069 Plotting NPV IRR.en.srt 10.4 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/049 Intro to Strings.en.srt 10.3 kB
  • 17 How to create your own user-defined Functions/177 Scope - easily explained.en.srt 10.3 kB
  • 24 Managing Time Series and Financial Data with Pandas/289 Downsampling Time Series with resample (Part 2).en.srt 10.2 kB
  • 24 Managing Time Series and Financial Data with Pandas/295 Importing Stock Price Data from Yahoo Finance (it still works).en.srt 10.2 kB
  • 29 Multiple Regression Models/361 Creating and working with Dummy Variables (Part 1).en.srt 10.2 kB
  • 24 Managing Time Series and Financial Data with Pandas/301 Financial Time Series - Return and Risk.en.srt 10.1 kB
  • 20 Pandas Basics - Starting from Zero/201 Built-in Functions Attributes and Methods.en.srt 10.1 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/309 Creating the equally-weighted Portfolio.en.srt 10.1 kB
  • 23 Pandas Advanced/272 Understanding the GroupBy Object.en.srt 10.0 kB
  • 23 Pandas Advanced/265 Creating DataFrames from Scratch with pd.DataFrame().en.srt 10.0 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/024 For Loops - Iterating over Lists.en.srt 9.9 kB
  • 24 Managing Time Series and Financial Data with Pandas/280 Importing Time Series Data from csv-files.en.srt 9.8 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/365 Single-Factor Models with the Fama-French Market Portfolio (Part 1).en.srt 9.8 kB
  • 21 Pandas Intermediate/239 Coding Exercise 5 (Solution).en.srt 9.8 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/027 The Net Present Value - NPV (Theory).en.srt 9.7 kB
  • 08 The Numpy Package Working with numbers made easy/072 Numpy Arrays.en.srt 9.7 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/093 Mortgage Loan Analysis - Debt Sizing.en.srt 9.5 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/191 Dynamic path-dependent Simulations (Part 1).en.srt 9.5 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/053 Comparison Logical and Membership Operators in Action.en.srt 9.5 kB
  • 27 Correlation and Regression/335 Creating a Confidence Interval for the Correlation Coefficient (Bootstrapping).en.srt 9.3 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/026 Calculate FV and PV for many Cashflows.en.srt 9.3 kB
  • 21 Pandas Intermediate/236 Advanced Filtering with between() isin() and ~.en.srt 9.2 kB
  • 24 Managing Time Series and Financial Data with Pandas/306 Coding Exercise 12 (Solution).en.srt 9.2 kB
  • 08 The Numpy Package Working with numbers made easy/071 Modules Packages and Libraries - No need to reinvent the Wheel.en.srt 9.1 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/376 Detecting and Handling Multicollinearity.en.srt 9.1 kB
  • 20 Pandas Basics - Starting from Zero/204 Selecting Columns.en.srt 9.1 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/085 Evaluating Annuities with np.fv() - Funding Phase.en.srt 9.1 kB
  • 01 Getting Started/003 How to download and install Anaconda for Python coding.en.srt 9.0 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/368 How to create a Fama-French Three-Factor Model.en.srt 9.0 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/091 How to evaluate a Retirement Plan A-Z.en.srt 9.0 kB
  • 27 Correlation and Regression/332 Covariance and Correlation Coefficient (Theory).en.srt 9.0 kB
  • 29 Multiple Regression Models/356 Movies Dataset - Preparing the Data.en.srt 9.0 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/322 Beta and Alpha.en.srt 9.0 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/058 While Loops.en.srt 9.0 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/321 Capital Asset Pricing Model (CAPM) Security Market Line (SLM).en.srt 8.9 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/323 Redefining the Market Portfolio.en.srt 8.8 kB
  • 21 Pandas Intermediate/220 Analyzing non-numerical Series with unique() nunique() value_counts().en.srt 8.8 kB
  • 24 Managing Time Series and Financial Data with Pandas/283 Indexing and Slicing Time Series.en.srt 8.7 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/150 Two-tailed t-Test (unknown Population Variance).en.srt 8.7 kB
  • 24 Managing Time Series and Financial Data with Pandas/298 The shift() method.en.srt 8.7 kB
  • 20 Pandas Basics - Starting from Zero/206 Selecting Rows with iloc (position-based indexing).en.srt 8.7 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/129 Confidence Intervals with scipy.stats.en.srt 8.7 kB
  • 24 Managing Time Series and Financial Data with Pandas/299 The methods diff() and pct_change().en.srt 8.6 kB
  • 29 Multiple Regression Models/362 Creating and working with Dummy Variables (Part 2).en.srt 8.6 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/313 Finding the Optimal Portfolio.en.srt 8.6 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/258 Coding Exercise 7 (Solution).en.srt 8.5 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/312 Portfolio Analysis and the Sharpe Ratio with Python.en.srt 8.4 kB
  • 23 Pandas Advanced/273 Splitting with many Keys.en.srt 8.3 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/047 Tuples.en.srt 8.3 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/252 Scatterplots.en.srt 8.3 kB
  • 23 Pandas Advanced/261 Removing Rows.en.srt 8.3 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/016 More on Variables and Memory.en.srt 8.3 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/092 Retirement Plan Sensitivity Analysis.en.srt 8.3 kB
  • 21 Pandas Intermediate/216 First Steps with Pandas Series.en.srt 8.2 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/251 Histogramms (Part 2).en.srt 8.2 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/048 Dictionaries.en.srt 8.1 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/119 Probability Distributions - Overview.en.srt 8.1 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/103 Population vs. Sample.en.srt 8.1 kB
  • 27 Correlation and Regression/338 A simple Linear Regression Model with numpy Scipy.en.srt 8.1 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/189 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 2).en.srt 8.1 kB
  • 20 Pandas Basics - Starting from Zero/214 Coding Exercise 2 (Solution).en.srt 8.1 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/110 Variability around the Central Tendency Dispersion (Theory).en.srt 8.0 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/188 Monte Carlo Simulations for Value-at-Risk - Bootstrapping (Part 1).en.srt 7.9 kB
  • 24 Managing Time Series and Financial Data with Pandas/297 Normalizing Time Series to a Base Value (100).en.srt 7.9 kB
  • 17 How to create your own user-defined Functions/173 The Default Argument None.en.srt 7.8 kB
  • 29 Multiple Regression Models/355 Multiple Regression (Theory).en.srt 7.8 kB
  • 27 Correlation and Regression/330 Cleaning and preparing the Data - Movies Database (Part 1).en.srt 7.8 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/381 Logistic Regression with statsmodels (Part 2).en.srt 7.8 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/366 Single-Factor Models with the Fama-French Market Portfolio (Part 2).en.srt 7.7 kB
  • 23 Pandas Advanced/276 Hierarchical Indexing with Groupby.en.srt 7.7 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/186 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 2).en.srt 7.7 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/008 Intro to the Time Value of Money (TVM) Concept (Theory).en.srt 7.7 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/324 Cyclical vs. non-cyclical Stocks - another Intuition on Beta.en.srt 7.6 kB
  • 17 How to create your own user-defined Functions/170 Defining your first user-defined Function.en.srt 7.6 kB
  • 23 Pandas Advanced/279 Coding Exercise 9 (Solution).en.srt 7.6 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/033 Build-in Functions.en.srt 7.6 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/126 The Standard Normal Distribution and Z-Values.en.srt 7.6 kB
  • 23 Pandas Advanced/270 Coding Exercise 8 (Solution).en.srt 7.6 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/149 One-tailed Z-Test with known Population Variance.en.srt 7.5 kB
  • 17 How to create your own user-defined Functions/171 What s the difference between Positional Arguments vs. Keyword Arguments.en.srt 7.5 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/090 Frequency of compounding and the effective annual interest rate.en.srt 7.3 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/030 Data Types in Action.en.srt 7.3 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/097 Capital Budgeting - Mutually exclusive Projects (Part 2).en.srt 7.3 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/059 The Internal Rate of Return - IRR (Theory).en.srt 7.3 kB
  • 24 Managing Time Series and Financial Data with Pandas/290 The PeriodIndex object.en.srt 7.3 kB
  • 21 Pandas Intermediate/219 EXCURSUS Updating Pandas Anaconda.en.srt 7.3 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/035 Floats.en.srt 7.3 kB
  • 27 Correlation and Regression/331 Cleaning and preparing the Data - Movies Database (Part 2).en.srt 7.2 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/120 Discrete Uniform Distributions.en.srt 7.2 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/253 First Steps with Seaborn.en.srt 7.2 kB
  • 08 The Numpy Package Working with numbers made easy/080 Advanced Filtering Bitwise Operators.en.srt 7.2 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/115 How to calculate Skew and Kurtosis with scipy.stats.en.srt 7.0 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/122 The Normal Distribution (Theory).en.srt 7.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/282 Initial Analysis Visualization of Time Series.en.srt 7.0 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/181 What is the Value-at-Risk (VaR) (Theory).en.srt 7.0 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/067 Customizing Plots (Part 1).en.srt 7.0 kB
  • 17 How to create your own user-defined Functions/172 How to work with Default Arguments.en.srt 6.9 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/086 Evaluating Annuities with np.fv() - Payout Phase.en.srt 6.8 kB
  • 08 The Numpy Package Working with numbers made easy/075 Changing Elements in Numpy Arrays Mutability.en.srt 6.8 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/159 How to slice 2-dim Numpy Arrays (Part 1).en.srt 6.8 kB
  • 21 Pandas Intermediate/225 First Steps with Pandas Index Objects.en.srt 6.7 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/152 Hypothesis Testing with Bootstrapping.en.srt 6.7 kB
  • 01 Getting Started/001 Tips How to get the most out of this Course (don t skip).en.srt 6.7 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/036 How to round Floats (and Integers) with round().en.srt 6.7 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/143 Bootstrapping with Python an alternative method without Statistics.en.srt 6.7 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/370 How to create a Fama-French Five-Factor Model.en.srt 6.7 kB
  • 20 Pandas Basics - Starting from Zero/209 Selecting Rows with loc (label-based indexing).en.srt 6.7 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/123 Creating a normally distributed Random Variable.en.srt 6.6 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/106 Measures of Central Tendency (Theory).en.srt 6.6 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/065 Line Plots.en.srt 6.6 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/131 Sample Statistic Sampling Error and Sampling Distribution (Theory).en.srt 6.6 kB
  • 17 How to create your own user-defined Functions/178 How to create Nested Functions.en.srt 6.6 kB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/198 Tabular Data and Pandas DataFrames.en.srt 6.5 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/013 Introduction to Variables.en.srt 6.5 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/142 Student s t-Distribution vs. Normal Distribution with scipy.stats.en.srt 6.5 kB
  • 21 Pandas Intermediate/232 nunique() and nlargest() nsmallest() with DataFrames.en.srt 6.5 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/136 Central Limit Theorem (Coding Part 2).en.srt 6.5 kB
  • 08 The Numpy Package Working with numbers made easy/082 Creating Numpy Arrays from Scratch.en.srt 6.5 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/165 Arithmetic Vectorized Operations with 2-dim Numpy Arrays.en.srt 6.4 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/037 More on Lists.en.srt 6.4 kB
  • 27 Correlation and Regression/333 How to calculate Covariance and Correlation in Python.en.srt 6.4 kB
  • 17 How to create your own user-defined Functions/175 Sequences as arguments and args.en.srt 6.4 kB
  • 01 Getting Started/002 FAQ Your Questions answered.html 6.4 kB
  • 24 Managing Time Series and Financial Data with Pandas/287 Coding Exercise 10 (Solution).en.srt 6.4 kB
  • 02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/006 Overview Download of Course Materials for Part 1.en.srt 6.3 kB
  • 20 Pandas Basics - Starting from Zero/207 Slicing Rows and Columns with iloc (position-based indexing).en.srt 6.3 kB
  • 27 Correlation and Regression/334 Correlation and Scatterplots visual Interpretation.en.srt 6.3 kB
  • 08 The Numpy Package Working with numbers made easy/081 Determining a Project s Payback Period with np.where().en.srt 6.3 kB
  • 29 Multiple Regression Models/357 Multiple Regression Analysis with statsmodels.en.srt 6.3 kB
  • 08 The Numpy Package Working with numbers made easy/077 Numpy Array Methods and Attributes.en.srt 6.3 kB
  • 24 Managing Time Series and Financial Data with Pandas/293 Coding Exercise 11 (Solution).en.srt 6.2 kB
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/327 Introduction to Regression Analysis.en.srt 6.2 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/185 Monte Carlo Simulations for Value-at-Risk - Parametric (Part 1).en.srt 6.2 kB
  • 24 Managing Time Series and Financial Data with Pandas/296 Initial Inspection and Visualization.en.srt 6.2 kB
  • 23 Pandas Advanced/260 Removing Columns.en.srt 6.2 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/314 Sharpe Ratio - visualized and explained.en.srt 6.1 kB
  • 29 Multiple Regression Models/360 How to test the Significance of the Model as a whole (F-Test).en.srt 6.1 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/011 Interest Rates and Returns (Theory).en.srt 6.1 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/105 Relative and Cumulative Frequencies with plt.hist().en.srt 6.1 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/369 The Factors Profitability and Investment.en.srt 6.1 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/353 Case Study (Part 3) The Market Model (Single Factor Model).en.srt 6.0 kB
  • 21 Pandas Intermediate/224 Coding Exercise 3 (Solution).en.srt 6.0 kB
  • 21 Pandas Intermediate/235 Filtering DataFrames by many Conditions (OR).en.srt 6.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/304 Merging Aligning Financial Time Series (hands-on).en.srt 6.0 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/057 Calculate a Project s Payback Period.en.srt 5.9 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/372 Linear Regression - not that easy.en.srt 5.9 kB
  • 27 Correlation and Regression/340 Case Study (Part 1) The Market Model (Single Factor Model).en.srt 5.9 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/182 Analyzing the Data past Performance.en.srt 5.9 kB
  • 20 Pandas Basics - Starting from Zero/203 Explore your own Dataset Coding Exercise 1 (Solution).en.srt 5.9 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/045 Mutable vs. immutable Objects (Part 2).en.srt 5.9 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/380 Logistic Regression with statsmodels (Part 1).en.srt 5.9 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/140 Unknown Population Variance - the Standard Case (Example 1).en.srt 5.8 kB
  • 23 Pandas Advanced/268 Manipulating Elements in a DataFrame.en.srt 5.8 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/025 The range Object - another Iterable.en.srt 5.8 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/163 Reshaping and Transposing 2-dim Numpy Arrays.en.srt 5.8 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/084 Evaluating Investments with np.npv() and np.irr().en.srt 5.8 kB
  • 17 How to create your own user-defined Functions/174 How to unpack Iterables.en.srt 5.8 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/139 The Student s t-distribution What is it and whywhen do we use it.en.srt 5.8 kB
  • 08 The Numpy Package Working with numbers made easy/076 View vs. copy - potential Pitfalls when slicing Numpy Arrays.en.srt 5.7 kB
  • 24 Managing Time Series and Financial Data with Pandas/302 Financial Time Series - Covariance and Correlation.en.srt 5.7 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/117 How to generate Random Numbers with Numpy.en.srt 5.7 kB
  • 08 The Numpy Package Working with numbers made easy/079 Boolean Arrays and Conditional Filtering.en.srt 5.6 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/038 Lists and Element-wise Operations.en.srt 5.6 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/138 Point Estimates vs. Confidence Interval Estimates (known Population Variance).en.srt 5.6 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/311 What is the Sharpe Ratio and a Risk Free Asset.en.srt 5.6 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/375 Non-Linear Relationships - Feature Transformation.en.srt 5.6 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/162 How to perform row-wise and column-wise Operations.en.srt 5.6 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/183 How to use the Parametric Method to calculate Value-at-Risk (VaR).en.srt 5.5 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/052 Operators (Theory).en.srt 5.5 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/157 How to work with nested Lists.en.srt 5.4 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/250 Histogramms (Part 1).en.srt 5.4 kB
  • 21 Pandas Intermediate/221 The copy() method.en.srt 5.4 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/114 Skew and Kurtosis (Theory).en.srt 5.4 kB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/102 Download of Part 2 Course Materials.en.srt 5.3 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/018 The print() Function.en.srt 5.3 kB
  • 21 Pandas Intermediate/234 Filtering DataFrames by many Conditions (AND).en.srt 5.3 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/039 Slicing Lists.en.srt 5.2 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/190 Conditional Value-at-Risk (CVaR).en.srt 5.2 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/132 Sampling with np.random.choice().en.srt 5.2 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/348 OLS Regression with statsmodels and DataFrames.en.srt 5.2 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/135 Central Limit Theorem (Coding Part 1).en.srt 5.1 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/050 String Replacement.en.srt 5.0 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/133 Sampling Distribution.en.srt 5.0 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/108 Coding Measures of Central Tendency - Geometric Mean.en.srt 5.0 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/017 Variables - Dos Don ts and Conventions.en.srt 4.9 kB
  • 21 Pandas Intermediate/228 Renaming Index Column Labels with rename().en.srt 4.9 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/307 Intro.en.srt 4.9 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/012 Calculate Interest Rates and Returns with Python.en.srt 4.8 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/121 Continuous Uniform Distributions.en.srt 4.8 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/352 Regression Analysis with statsmodels - the Summary Table.en.srt 4.8 kB
  • 08 The Numpy Package Working with numbers made easy/074 Vectorized Operations with Numpy Arrays.en.srt 4.8 kB
  • 21 Pandas Intermediate/237 any() and all().en.srt 4.8 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/148 Calculating and interpreting z-statistic and p-value with scipy.stats.en.srt 4.7 kB
  • 08 The Numpy Package Working with numbers made easy/078 Numpy Universal Functions.en.srt 4.7 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/379 Logistic Regression (Theory).en.srt 4.7 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/350 Hypothesis Testing of Regression Coefficients (Theory).en.srt 4.7 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/158 2-dimensional Numpy Arrays.en.srt 4.7 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/351 Hypothesis Testing of Regression Coefficients with statsmodels.en.srt 4.7 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/166 The keepdims parameter.en.srt 4.6 kB
  • 20 Pandas Basics - Starting from Zero/205 Selecting Rows with Square Brackets (not advisable).en.srt 4.6 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/104 Visualizing Frequency Distributions with plt.hist().en.srt 4.6 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/168 Merging and Concatenating Numpy Arrays.en.srt 4.6 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/164 Creating 2-dim Numpy Arrays from Scratch.en.srt 4.6 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/167 Adding Removing Elements.en.srt 4.6 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/161 Recap Changing Elements in a Numpy Array slice.en.srt 4.6 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/124 Normal Distribution - Probability Density Function (pdf) with scipy.stats.en.srt 4.6 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/020 TVM Problems with many Cashflows.en.srt 4.6 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/107 Coding Measures of Central Tendency - Mean and Median.en.srt 4.6 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/137 Central Limit Theorem (Theory).en.srt 4.5 kB
  • 21 Pandas Intermediate/230 Coding Exercise 4 (Solution).en.srt 4.5 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/098 Capital Budgeting - Mutually exclusive Projects (Part 3).en.srt 4.4 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/042 Sorting and Reversing Lists.en.srt 4.4 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/031 The Data Type Hierarchy (Theory).en.srt 4.4 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/118 Reproducibility with np.random.seed().en.srt 4.4 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/147 What is the p-value (Theory).en.srt 4.4 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/009 Calculate Future Values (FV) with Python Compounding.en.srt 4.3 kB
  • 27 Correlation and Regression/336 Testing for Correlation (t-Test).en.srt 4.3 kB
  • 21 Pandas Intermediate/244 The agg() method.en.srt 4.3 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/096 Capital Budgeting - Mutually exclusive Projects (Part 1).en.srt 4.3 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/112 Percentiles with PythonNumpy.en.srt 4.2 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/087 How to solve for annuity payments with np.pmt().en.srt 4.2 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/089 How to calculate the required Contract Value with np.pv().en.srt 4.2 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/113 Variance and Standard Deviation with PythonNumpy.en.srt 4.1 kB
  • 21 Pandas Intermediate/227 Changing Column Labels.en.srt 4.1 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/318 Capital Market Line (CML) Two-Fund-Theorem.en.srt 4.0 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/346 OLS Regression with Statsmodels - ANOVA.en.srt 4.0 kB
  • 23 Pandas Advanced/262 Adding new Columns to a DataFrame.en.srt 3.9 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/034 Integers.en.srt 3.9 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/023 Indexing Lists.en.srt 3.9 kB
  • 23 Pandas Advanced/266 Adding new Rows (Hands-on).en.srt 3.8 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/151 One-tailed t-Test (unknown Population Variance).en.srt 3.8 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/127 Properties of the Standard Normal Distribution (Theory).en.srt 3.8 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/141 Unknown Population Variance - the Standard Case (Example 2).en.srt 3.7 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/028 Calculate an Investment Project s NPV.en.srt 3.7 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/015 Excursus How to add inline comments.en.srt 3.7 kB
  • 24 Managing Time Series and Financial Data with Pandas/285 More on pd.date_range().en.srt 3.6 kB
  • 29 Multiple Regression Models/358 Coefficient of Determination (Adjusted R squared).en.srt 3.5 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/088 How to solve for the number of periodic payments with np.nper().en.srt 3.5 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/041 Changing Elements in Lists.en.srt 3.5 kB
  • 15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/156 Coding Projects Part 3 - Overview.en.srt 3.5 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/184 How to use the Historical Method to calculate Value-at-Risk (VaR).en.srt 3.4 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/109 Excursus Why Log Returns are useful.en.srt 3.4 kB
  • 17 How to create your own user-defined Functions/176 How to return many results.en.srt 3.4 kB
  • 06 How to solve for IRR YTM with While Loops and Conditional Statements/062 Solving for a Bond s Yield to Maturity (YTM).en.srt 3.4 kB
  • 27 Correlation and Regression/339 How to interpret Intercept and Slope Coefficient.en.srt 3.4 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/125 Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.en.srt 3.3 kB
  • 08 The Numpy Package Working with numbers made easy/073 Indexing and Slicing Numpy Arrays.en.srt 3.3 kB
  • 27 Correlation and Regression/337 What is Linear Regression (Theory).en.srt 3.3 kB
  • 31 Issues in Linear Regression Analysis and Logistic Regression/374 Detecting and Handling Outliers (Part 2).en.srt 3.3 kB
  • 32 What s next/382 Get your special BONUS here.html 3.3 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/095 Calculate PV of equal installments with np.pv() - Valuation of Bonds.en.srt 3.3 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/022 Zero-based Indexing and negative Indexing in Python (Theory).en.srt 3.2 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/134 Standard Error.en.srt 3.2 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/193 Dynamic path-dependent Simulations (Part 3).en.srt 3.1 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/010 Calculate Present Values (FV) with Python Discounting.en.srt 3.1 kB
  • 04 How to use Lists and For Loops for TVM Problems with many Cashflows/021 Intro to Python Lists.en.srt 3.0 kB
  • 10 --- PART 2 STATISTICS AND HYPOTHESIS TESTING WITH PYTHON NUMPY AND SCIPY ---/101 Coding Projects Part 2 - Overview.en.srt 2.9 kB
  • 27 Correlation and Regression/341 Case Study (Part 2) The Market Model (Single Factor Model).en.srt 2.9 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/343 OLS (Ordinary Least Squares) Regression (Theory).en.srt 2.9 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/051 Booleans.en.srt 2.9 kB
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/328 Coding Projects Part 5 - Overview.en.srt 2.9 kB
  • 15 -- PART 3 ADVANCED PYTHON MONTE CARLO SIMULATIONS AND VALUE AT RISK (VAR) ---/155 Overview Download of Course Materials for Part 3.en.srt 2.9 kB
  • 21 Pandas Intermediate/242 Exporting DataFrames to csv.en.srt 2.8 kB
  • 24 Managing Time Series and Financial Data with Pandas/294 Getting Ready (Installing required library).en.srt 2.8 kB
  • 23 Pandas Advanced/271 Introduction to GroupBy Operations.en.srt 2.7 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/308 Getting the Data.en.srt 2.6 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/111 Minimum Maximum and Range with PythonNumpy.en.srt 2.5 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/066 Scatter Plots.en.srt 2.5 kB
  • 03 How to use Python as a Calculator for basic Time Value of Money Problems/014 Variables and Memory (Theory).en.srt 2.4 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/160 How to slice 2-dim Numpy Arrays (Part 2).en.srt 2.4 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/317 Intro CAPM.en.srt 2.3 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/347 Coefficient of Determination (R squared).en.srt 2.3 kB
  • 02 ---- PART 1 PYTHON BASICS TIME VALUE OF MONEY AND CAPITAL BUDGETING ----/007 Coding Projects Part 1 - Overview.en.srt 2.2 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/247 Intro.html 2.2 kB
  • 19 --- PART 4 MANAGING (FINANCIAL) DATA WITH PANDAS BEYOND EXCEL ---/196 Introduction.en.srt 2.1 kB
  • 05 100 Python Objects Data Types Operators Functional Programming/032 Excursus Dynamic Typing in Python.en.srt 2.0 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/064 Intro.en.srt 1.7 kB
  • 21 Pandas Intermediate/215 Intro.html 1.5 kB
  • 21 Pandas Intermediate/218 UPDATE Pandas Version 0.24.0 (Jan E9).html 1.2 kB
  • 23 Pandas Advanced/259 Intro.html 1.2 kB
  • 20 Pandas Basics - Starting from Zero/202 Explore your own Dataset Coding Exercise 1 (Intro).html 1.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/286 Coding Exercise 10 (intro).html 1.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/292 Coding Exercise 11 (intro).html 1.0 kB
  • 24 Managing Time Series and Financial Data with Pandas/305 Coding Exercise 12 (intro).html 1.0 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/315 Coding Exercise 13 (Intro).html 1.0 kB
  • 25 Creating analyzing and optimizing Financial Portfolios with Python/325 Coding Exercise 14 (Intro).html 1.0 kB
  • 20 Pandas Basics - Starting from Zero/213 Coding Exercise 2 (Intro).html 1.0 kB
  • 21 Pandas Intermediate/223 Coding Exercise 3 (Intro).html 1.0 kB
  • 21 Pandas Intermediate/229 Coding Exercise 4 (Intro).html 1.0 kB
  • 21 Pandas Intermediate/238 Coding Exercise 5 (Intro).html 1.0 kB
  • 21 Pandas Intermediate/245 Coding Exercise 6 (Intro).html 1.0 kB
  • 22 Data Visualization with Pandas Matplotlib and Seaborn/257 Coding Exercise 7 (Intro).html 1.0 kB
  • 23 Pandas Advanced/269 Coding Exercise 8 (Intro).html 1.0 kB
  • 23 Pandas Advanced/278 Coding Exercise 9 (Intro).html 1.0 kB
  • 07 How to create great graphs with Matplotlib - Plotting NPV and IRR/070 Coding Exercise 6.html 1.0 kB
  • 09 How to solve complex TVM and Capital Budgeting problems with Python and Numpy/099 Coding Exercise 8.html 1.0 kB
  • 11 How to perform Descriptive Statistics on Populations and Samples/116 Coding Exercise 1.html 1.0 kB
  • 12 Common Probability Distributions and how to construct Confidence Intervals/130 Coding Exercise 2.html 1.0 kB
  • 13 How to estimate Population parameters with Samples - Sampling and Estimation/144 Coding Exercise 3.html 1.0 kB
  • 14 How to perform Hypothesis Tests Z-Tests t-Tests Bootstrapping more/154 Coding Exercise 4.html 1.0 kB
  • 16 n-dimensional Numpy Arrays How to work with numerical Tabular Data/169 Coding Exercise 1.html 1.0 kB
  • 17 How to create your own user-defined Functions/180 Coding Exercise 2.html 1.0 kB
  • 18 Monte Carlo Simulations and Value-at-Risk (VAR) with Python and Numpy/195 Coding Exercise 3.html 1.0 kB
  • 27 Correlation and Regression/342 Coding Exercise 1.html 1.0 kB
  • 28 OLS Regression ANOVA and Hypothesis Testing/354 Coding Exercise 2.html 1.0 kB
  • 29 Multiple Regression Models/363 Coding Exercise 3.html 1.0 kB
  • 30 Case Study Multi-Factor Models (Fama-French)/371 Coding Exercise 4.html 1.0 kB
  • 20 Pandas Basics - Starting from Zero/208 Position-based Indexing Cheat Sheets.html 1.0 kB
  • 20 Pandas Basics - Starting from Zero/211 Label-based Indexing Cheat Sheets.html 995 Bytes
  • 26 --- PART 5 REGRESSION ANALYSIS (A MUST-HAVE FOR MACHINE LEARNING) ---/329 Download of Part 5 Course Materials.html 995 Bytes
  • 05 100 Python Objects Data Types Operators Functional Programming/040 Slicing Cheat Sheet.html 968 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
>