[FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass

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[FreeCourseSite.com] Udemy - Manage Finance Data with Python & Pandas Unique Masterclass

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文件列表

  • 19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).mp4 140.9 MB
  • 19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.mp4 130.3 MB
  • 8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().mp4 120.3 MB
  • 3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.mp4 118.9 MB
  • 5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.mp4 108.1 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).mp4 101.3 MB
  • 3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).mp4 95.9 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).mp4 92.8 MB
  • 6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.mp4 92.3 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.mp4 90.7 MB
  • 1. Getting Started/5. Installation of Anaconda.mp4 90.4 MB
  • 19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).mp4 90.2 MB
  • 8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).mp4 89.7 MB
  • 5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.mp4 89.3 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.mp4 88.6 MB
  • 4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).mp4 88.0 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.mp4 84.6 MB
  • 5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.mp4 83.3 MB
  • 6. Pandas Advanced Topics/18. stack() and unstack().mp4 82.6 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.mp4 82.3 MB
  • 19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.mp4 81.5 MB
  • 4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.mp4 80.8 MB
  • 4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().mp4 78.7 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4 77.2 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.mp4 76.6 MB
  • 4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 76.2 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.mp4 76.0 MB
  • 4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).mp4 75.4 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).mp4 75.3 MB
  • 1. Getting Started/1. Course Overview and how to maximize your learning success.mp4 74.4 MB
  • 6. Pandas Advanced Topics/16. split-apply-combine applied.mp4 74.1 MB
  • 5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).mp4 73.7 MB
  • 11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).mp4 73.3 MB
  • 4. Pandas Intermediate Topics/30. Handling NA Values missing Values.mp4 71.9 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).mp4 71.8 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.mp4 70.8 MB
  • 1. Getting Started/7. How to use Jupyter Notebooks.mp4 69.5 MB
  • 4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.mp4 68.6 MB
  • 1. Getting Started/6. Opening a Jupyter Notebook.mp4 68.2 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.mp4 67.9 MB
  • 19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).mp4 67.5 MB
  • 11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.mp4 67.5 MB
  • 6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).mp4 66.6 MB
  • 19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).mp4 65.8 MB
  • 5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).mp4 65.2 MB
  • 3. Pandas Basics/19. Summary and Outlook.mp4 65.1 MB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).mp4 64.7 MB
  • 3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).mp4 63.5 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).mp4 63.3 MB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).mp4 63.0 MB
  • 19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.mp4 62.4 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).mp4 61.4 MB
  • 6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).mp4 61.3 MB
  • 19. Appendix 1 Python Crash Course (optional)/11. For Loops.mp4 61.2 MB
  • 8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().mp4 60.8 MB
  • 4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.mp4 60.4 MB
  • 19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).mp4 60.2 MB
  • 3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).mp4 59.5 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).mp4 59.3 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).mp4 59.1 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).mp4 58.7 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.mp4 58.1 MB
  • 6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).mp4 57.2 MB
  • 4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().mp4 57.0 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.mp4 56.9 MB
  • 3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.mp4 56.8 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.mp4 56.7 MB
  • 3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).mp4 56.6 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.mp4 56.3 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/3. Numpy Arrays Indexing and Slicing.mp4 56.1 MB
  • 4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).mp4 55.5 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).mp4 54.9 MB
  • 19. Appendix 1 Python Crash Course (optional)/16. User Defined Functions (Part 3).mp4 54.7 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.mp4 53.5 MB
  • 3. Pandas Basics/6. Built-in Functions, Attributes and Methods.mp4 53.1 MB
  • 3. Pandas Basics/22. Coding Exercise 2 (Solution).mp4 53.0 MB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).mp4 52.9 MB
  • 8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().mp4 52.9 MB
  • 11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.mp4 52.7 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.mp4 52.3 MB
  • 11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).mp4 52.2 MB
  • 6. Pandas Advanced Topics/14. Splitting with many Keys.mp4 52.1 MB
  • 6. Pandas Advanced Topics/3. Removing Rows.mp4 52.1 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().mp4 52.0 MB
  • 19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.mp4 51.9 MB
  • 8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).mp4 51.5 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).mp4 50.7 MB
  • 8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.mp4 50.5 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.mp4 50.1 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).mp4 50.0 MB
  • 6. Pandas Advanced Topics/15. split-apply-combine.mp4 49.3 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.mp4 49.2 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().mp4 48.9 MB
  • 6. Pandas Advanced Topics/13. Understanding the GroupBy Object.mp4 48.5 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.mp4 48.0 MB
  • 4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.mp4 47.9 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.mp4 47.8 MB
  • 11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.mp4 47.7 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.mp4 47.7 MB
  • 3. Pandas Basics/3. First Steps (Inspection of Data, Part 1).mp4 47.4 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.mp4 47.0 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.mp4 47.0 MB
  • 8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).mp4 46.6 MB
  • 6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).mp4 46.6 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.mp4 46.4 MB
  • 11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).mp4 46.4 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).mp4 46.4 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.mp4 46.3 MB
  • 8. Time Series Data in Pandas Introduction/14. Coding Exercise 11 (Solution).mp4 46.2 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4 46.1 MB
  • 1. Getting Started/2. Tips How to get the most out of this Course.mp4 45.8 MB
  • 4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.mp4 45.1 MB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.mp4 45.0 MB
  • 4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 45.0 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.mp4 44.9 MB
  • 11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.mp4 44.8 MB
  • 5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.mp4 44.8 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.mp4 44.7 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.mp4 44.7 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/4. Initial Inspection and Visualization.mp4 44.4 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/14. The S&P 500 Weather Radar.mp4 43.9 MB
  • 19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.mp4 43.8 MB
  • 8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.mp4 43.8 MB
  • 4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.mp4 43.4 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.mp4 43.1 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().mp4 43.0 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.mp4 42.5 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().mp4 42.2 MB
  • 11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.mp4 41.4 MB
  • 3. Pandas Basics/10. Explore your own Dataset Coding Exercise 1 (Solution).mp4 41.4 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).mp4 40.7 MB
  • 8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.mp4 40.7 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.mp4 40.6 MB
  • 3. Pandas Basics/11. Selecting Columns.mp4 40.4 MB
  • 19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.mp4 40.1 MB
  • 19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.mp4 40.0 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).mp4 38.7 MB
  • 19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.mp4 38.5 MB
  • 5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.mp4 37.9 MB
  • 6. Pandas Advanced Topics/2. Removing Columns.mp4 37.8 MB
  • 4. Pandas Intermediate Topics/2. First Steps with Pandas Series.mp4 37.7 MB
  • 4. Pandas Intermediate Topics/11. Coding Exercise 3 (Solution).mp4 37.6 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.mp4 37.5 MB
  • 20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.mp4 37.3 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).mp4 37.2 MB
  • 8. Time Series Data in Pandas Introduction/3. Initial Analysis Visualization of Time Series.mp4 36.7 MB
  • 11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.mp4 36.7 MB
  • 19. Appendix 1 Python Crash Course (optional)/2. First Steps.mp4 35.9 MB
  • 5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).mp4 35.8 MB
  • 4. Pandas Intermediate Topics/15. Renaming Index & Column Labels with rename().mp4 35.2 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.mp4 34.6 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.mp4 34.6 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/13. The S&P 500 Dollar Triangle.mp4 34.5 MB
  • 6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.mp4 34.5 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.mp4 34.2 MB
  • 4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.mp4 34.2 MB
  • 11. Create and Analyze Financial Indexes/14. Comparison of weighting methods.mp4 34.1 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.mp4 33.8 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/1. Intro.mp4 33.7 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).mp4 33.1 MB
  • 19. Appendix 1 Python Crash Course (optional)/3. Variables.mp4 33.0 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().mp4 32.9 MB
  • 6. Pandas Advanced Topics/9. Manipulating Elements in a DataFrame.mp4 32.8 MB
  • 4. Pandas Intermediate Topics/23. Filtering DataFrames by many Conditions (OR).mp4 32.3 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/19. Merging Aligning Financial Time Series (hands-on).mp4 32.2 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.mp4 32.1 MB
  • 3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).mp4 31.8 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).mp4 30.7 MB
  • 11. Create and Analyze Financial Indexes/3. Getting the Data.mp4 29.4 MB
  • 3. Pandas Basics/1. Intro to Tabular Data Pandas.mp4 28.9 MB
  • 4. Pandas Intermediate Topics/18. Coding Exercise 4 (Solution).mp4 28.7 MB
  • 1. Getting Started/3. Did you know that....mp4 28.2 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/9. Advanced Date Shifting.mp4 27.9 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/7. Candle-Stick and OHLC Charts with Plotly.mp4 27.8 MB
  • 3. Pandas Basics/14. Slicing Rows and Columns with iloc (position-based indexing).mp4 27.2 MB
  • 4. Pandas Intermediate Topics/22. Filtering DataFrames by many Conditions (AND).mp4 27.2 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.mp4 27.0 MB
  • 11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.mp4 26.6 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/16. Expanding Windows.mp4 26.3 MB
  • 4. Pandas Intermediate Topics/7. The copy() method.mp4 26.0 MB
  • 5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).mp4 25.8 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).mp4 24.9 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/9. Sharpe Ratio - visualized and explained.mp4 24.4 MB
  • 4. Pandas Intermediate Topics/33. The agg() method.mp4 23.9 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/11. Coding Exercise 15 (Intro).mp4 23.6 MB
  • 5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.mp4 23.2 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/1. Intro.mp4 23.2 MB
  • 3. Pandas Basics/12. Selecting Rows with Square Brackets (not advisable).mp4 23.1 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/2. Getting Ready (Installing required library).mp4 22.8 MB
  • 4. Pandas Intermediate Topics/14. Changing Column Labels.mp4 22.2 MB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/20. Coding Exercise 13 (intro).mp4 21.6 MB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.mp4 21.5 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/2. Getting Ready (Installing required libraries).mp4 19.7 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/13. Coding Exercise 16 (Intro).mp4 19.7 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).mp4 19.2 MB
  • 6. Pandas Advanced Topics/4. Adding new Columns to a DataFrame.mp4 18.8 MB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/12. Coding Exercise 12 (intro).mp4 18.4 MB
  • 4. Pandas Intermediate Topics/25. any() and all().mp4 18.4 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.mp4 17.7 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/1. Intro.mp4 17.3 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/2. Capital Market Line (CML) & Two-Fund-Theorem.mp4 16.6 MB
  • 4. Pandas Intermediate Topics/34. Coding Exercise 6 (Intro).mp4 16.1 MB
  • 4. Pandas Intermediate Topics/31. Exporting DataFrames to csv.mp4 13.9 MB
  • 8. Time Series Data in Pandas Introduction/6. More on pd.date_range().mp4 13.0 MB
  • 12. Create, Analyze and Optimize Financial Portfolios/2. Getting the Data.mp4 12.8 MB
  • 11. Create and Analyze Financial Indexes/16. Coding Exercise 14 (intro).mp4 11.9 MB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/9. More Technical Indicators with Plotly (Volume, MACD, DMI).mp4 11.7 MB
  • 4. Pandas Intermediate Topics/27. Coding Exercise 5 (Intro).mp4 11.5 MB
  • 5. Data Visualization with Matplotlib and Seaborn/11. Coding Exercise 7 (Intro).mp4 11.2 MB
  • 4. Pandas Intermediate Topics/10. Coding Exercise 3 (Intro).mp4 11.0 MB
  • 6. Pandas Advanced Topics/12. Introduction to GroupBy Operations.mp4 10.5 MB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/1. Intro.mp4 10.5 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1. Financial Analyst Challenge (Intro).mp4 10.5 MB
  • 8. Time Series Data in Pandas Introduction/7. Coding Exercise 10 (intro).mp4 10.4 MB
  • 6. Pandas Advanced Topics/10. Coding Exercise 8 (Intro).mp4 9.5 MB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/4. resample() and OHLC().mp4 9.2 MB
  • 8. Time Series Data in Pandas Introduction/13. Coding Exercise 11 (intro).mp4 9.2 MB
  • 3. Pandas Basics/21. Coding Exercise 2 (Intro).mp4 9.1 MB
  • 6. Pandas Advanced Topics/20. Coding Exercise 9 (Intro).mp4 8.2 MB
  • 4. Pandas Intermediate Topics/17. Coding Exercise 4 (Intro).mp4 8.0 MB
  • 19. Appendix 1 Python Crash Course (optional)/1. Intro.mp4 6.2 MB
  • 3. Pandas Basics/9.1 Finance_Data_Exc.zip.zip 4.5 MB
  • 3. Pandas Basics/5.1 Video-Lecture-NBs.zip.zip 2.5 MB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1.1 Final_Project.zip.zip 2.1 MB
  • 19. Appendix 1 Python Crash Course (optional)/7. Data Types Lists (Part 2).vtt 18.6 kB
  • 8. Time Series Data in Pandas Introduction/5. Creating a customized DatetimeIndex with pd.date_range().vtt 16.1 kB
  • 3. Pandas Basics/5. Coding Exercise 0 Coding the Video Lectures.vtt 15.9 kB
  • 5. Data Visualization with Matplotlib and Seaborn/8. Categorical Seaborn Plots.vtt 15.2 kB
  • 1. Getting Started/7. How to use Jupyter Notebooks.vtt 15.2 kB
  • 6. Pandas Advanced Topics/18. stack() and unstack().vtt 14.9 kB
  • 19. Appendix 1 Python Crash Course (optional)/17. Visualization with Matplotlib.vtt 14.8 kB
  • 8. Time Series Data in Pandas Introduction/9. Downsampling Time Series with resample() (Part 1).vtt 14.7 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/13. Numpy Quiz Solution.vtt 14.6 kB
  • 6. Pandas Advanced Topics/8. Adding new Rows to a DataFrame.vtt 14.0 kB
  • 19. Appendix 1 Python Crash Course (optional)/10. Conditional Statements (if, elif, else, while).vtt 13.8 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/4. The Portfolio Diversification Effect.vtt 13.6 kB
  • 4. Pandas Intermediate Topics/3. Analyzing Numerical Series with unique(), nunique() and value_counts().vtt 13.2 kB
  • 6. Pandas Advanced Topics/5. Arithmetic Operations (Part 1).vtt 13.2 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/11. Visualization and (Linear) Regression.vtt 12.9 kB
  • 6. Pandas Advanced Topics/6. Arithmetic Operations (Part 2).vtt 12.9 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/6. S&P 500 Performance Reporting - rolling risk and return.vtt 12.9 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/5. Systematic vs. unsystematic Risk.vtt 12.8 kB
  • 6. Pandas Advanced Topics/16. split-apply-combine applied.vtt 12.8 kB
  • 19. Appendix 1 Python Crash Course (optional)/19. Quiz Solution.vtt 12.7 kB
  • 5. Data Visualization with Matplotlib and Seaborn/9. Seaborn Regression Plots.vtt 12.5 kB
  • 5. Data Visualization with Matplotlib and Seaborn/3. Customization of Plots.vtt 12.4 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/21. Coding Exercise 13 (Solution).vtt 12.4 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/2. Importing Financial Data from Excel.vtt 12.2 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/4. Creating many random Portfolios with Python.vtt 12.1 kB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/5. It´s not that simple - Part 2 (Investments 101 vs. Real World).vtt 11.9 kB
  • 4. Pandas Intermediate Topics/30. Handling NA Values missing Values.vtt 11.8 kB
  • 4. Pandas Intermediate Topics/21. Filtering DataFrames (one Condition).vtt 11.4 kB
  • 1. Getting Started/1. Course Overview and how to maximize your learning success.vtt 11.2 kB
  • 4. Pandas Intermediate Topics/35. Coding Exercise 6 (Solution).vtt 11.2 kB
  • 3. Pandas Basics/17. Slicing Rows and Columns with loc (label-based indexing).vtt 11.1 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/12. Coding Exercise 15 (Solution).vtt 10.8 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/2. Filling NA Values with bfill, ffill and interpolation.vtt 10.7 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/7. S&P 500 Investment Horizon and Performance.vtt 10.6 kB
  • 4. Pandas Intermediate Topics/13. Changing Row Index with set_index() and reset_index().vtt 10.6 kB
  • 6. Pandas Advanced Topics/15. split-apply-combine.vtt 10.6 kB
  • 11. Create and Analyze Financial Indexes/1. Financial Indexes - an Overview.vtt 10.6 kB
  • 4. Pandas Intermediate Topics/32. Summary Statistics and Accumulations.vtt 10.5 kB
  • 3. Pandas Basics/19. Summary and Outlook.vtt 10.4 kB
  • 3. Pandas Basics/7. Make it easy TAB Completion and Tooltip.vtt 10.4 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.vtt 10.2 kB
  • 19. Appendix 1 Python Crash Course (optional)/11. For Loops.vtt 10.2 kB
  • 19. Appendix 1 Python Crash Course (optional)/5. Data Types Strings.vtt 10.1 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/8. Simple Returns vs. Log Returns.vtt 10.0 kB
  • 8. Time Series Data in Pandas Introduction/2. Converting strings to datetime objects with pd.to_datetime().vtt 9.9 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/11. The S&P 500 Return Triangle (Part 2).vtt 9.9 kB
  • 19. Appendix 1 Python Crash Course (optional)/9. Operators & Booleans.vtt 9.9 kB
  • 11. Create and Analyze Financial Indexes/6. Creating a Price-Weighted Stock Index with Python.vtt 9.8 kB
  • 1. Getting Started/6. Opening a Jupyter Notebook.vtt 9.8 kB
  • 11. Create and Analyze Financial Indexes/10. Market Value-Weighted Index - Theory.vtt 9.7 kB
  • 5. Data Visualization with Matplotlib and Seaborn/2. Visualization with Matplotlib (Intro).vtt 9.7 kB
  • 4. Pandas Intermediate Topics/19. Sorting DataFrames with sort_index() and sort_values().vtt 9.7 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/3. Simple Moving Averages (SMA) with rolling().vtt 9.7 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/8. Measuring Stock Performance with MEAN Returns and STD of Returns.vtt 9.6 kB
  • 4. Pandas Intermediate Topics/29. Intro to NA Values missing Values.vtt 9.5 kB
  • 4. Pandas Intermediate Topics/8. Sorting of Series and Introduction to the inplace - parameter.vtt 9.5 kB
  • 19. Appendix 1 Python Crash Course (optional)/14. User Defined Functions (Part 1).vtt 9.4 kB
  • 11. Create and Analyze Financial Indexes/4. Price-Weighted Index - Theory.vtt 9.4 kB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/2. Mean-Variance Optimization (MVO).vtt 9.3 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/14. Coding Exercise 16 (Solution).vtt 9.3 kB
  • 5. Data Visualization with Matplotlib and Seaborn/10. Seaborn Heatmaps.vtt 9.3 kB
  • 8. Time Series Data in Pandas Introduction/12. Advanced Indexing with reindex().vtt 9.2 kB
  • 8. Time Series Data in Pandas Introduction/10. Downsampling Time Series with resample (Part 2).vtt 9.0 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/3. Importing Stock Price Data from Yahoo Finance (it still works!).vtt 9.0 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/9. Financial Time Series - Return and Risk.vtt 9.0 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/7. Generating Random Numbers.vtt 9.0 kB
  • 19. Appendix 1 Python Crash Course (optional)/2. First Steps.vtt 9.0 kB
  • 3. Pandas Basics/6. Built-in Functions, Attributes and Methods.vtt 8.9 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/2. Numpy Arrays Vectorization.vtt 8.9 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/3. Creating the equally-weighted Portfolio.vtt 8.9 kB
  • 11. Create and Analyze Financial Indexes/12. Creating a Market Value-Weighted Stock Index with Python (Part 1).vtt 8.9 kB
  • 3. Pandas Basics/4. First Steps (Inspection of Data, Part 2).vtt 8.9 kB
  • 11. Create and Analyze Financial Indexes/9. Creating an Equal-Weighted Stock Index with Python.vtt 8.8 kB
  • 6. Pandas Advanced Topics/13. Understanding the GroupBy Object.vtt 8.8 kB
  • 19. Appendix 1 Python Crash Course (optional)/6. Data Types Lists (Part 1).vtt 8.7 kB
  • 8. Time Series Data in Pandas Introduction/1. Importing Time Series Data from csv-files.vtt 8.7 kB
  • 4. Pandas Intermediate Topics/28. Coding Exercise 5 (Solution).vtt 8.6 kB
  • 3. Pandas Basics/9. Explore your own Dataset Coding Exercise 1 (Intro).vtt 8.6 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/10. The Timedelta Object.vtt 8.4 kB
  • 4. Pandas Intermediate Topics/24. Advanced Filtering with between(), isin() and ~.vtt 8.1 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/13. Coding Exercise 12 (Solution).vtt 8.1 kB
  • 11. Create and Analyze Financial Indexes/17. Coding Exercise 14 (Solution).vtt 8.1 kB
  • 3. Pandas Basics/11. Selecting Columns.vtt 8.0 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/1. Introduction to Numpy Arrays.vtt 8.0 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/17. Rolling Correlation.vtt 8.0 kB
  • 1. Getting Started/5. Installation of Anaconda.vtt 8.0 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/4. Momentum Trading Strategies with SMAs.vtt 7.9 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/9. Beta and Alpha.vtt 7.9 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/8. Financial Analyst Challenge (Solution Part 6).vtt 7.8 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/7. Capital Asset Pricing Model (CAPM) & Security Market Line (SLM).vtt 7.8 kB
  • 11. Create and Analyze Financial Indexes/13. Creating a Market Value-Weighted Stock Index with Python (Part 2).vtt 7.8 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/10. Redefining the Market Portfolio.vtt 7.8 kB
  • 19. Appendix 1 Python Crash Course (optional)/4. Data Types Integers & Floats.vtt 7.8 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/9. Financial Analyst Challenge (Solution Part 7).vtt 7.7 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/9. Case Study Numpy vs. Python Standard Library.vtt 7.7 kB
  • 4. Pandas Intermediate Topics/6. Analyzing non-numerical Series with unique(), nunique(), value_counts().vtt 7.7 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/6. The shift() method.vtt 7.7 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/10. Summary Statistics.vtt 7.6 kB
  • 8. Time Series Data in Pandas Introduction/4. Indexing and Slicing Time Series.vtt 7.6 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/4. Financial Analyst Challenge (Solution Part 2).vtt 7.6 kB
  • 3. Pandas Basics/13. Selecting Rows with iloc (position-based indexing).vtt 7.6 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/7. The methods diff() and pct_change().vtt 7.6 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/8. Finding the Optimal Portfolio.vtt 7.5 kB
  • 5. Data Visualization with Matplotlib and Seaborn/12. Coding Exercise 7 (Solution).vtt 7.5 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/6. Portfolio Analysis and the Sharpe Ratio with Python.vtt 7.5 kB
  • 6. Pandas Advanced Topics/3. Removing Rows.vtt 7.4 kB
  • 5. Data Visualization with Matplotlib and Seaborn/6. Scatterplots.vtt 7.3 kB
  • 6. Pandas Advanced Topics/14. Splitting with many Keys.vtt 7.3 kB
  • 19. Appendix 1 Python Crash Course (optional)/3. Variables.vtt 7.3 kB
  • 4. Pandas Intermediate Topics/2. First Steps with Pandas Series.vtt 7.2 kB
  • 5. Data Visualization with Matplotlib and Seaborn/5. Histogramms (Part 2).vtt 7.2 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/3. Creating Offline Graphs in Jupyter Notebooks.vtt 7.1 kB
  • 3. Pandas Basics/22. Coding Exercise 2 (Solution).vtt 7.0 kB
  • 19. Appendix 1 Python Crash Course (optional)/13. Generating Random Numbers.vtt 7.0 kB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/4. Changing Expected Returns.vtt 7.0 kB
  • 19. Appendix 1 Python Crash Course (optional)/15. User Defined Functions (Part 2).vtt 6.9 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/5. Normalizing Time Series to a Base Value (100).vtt 6.9 kB
  • 11. Create and Analyze Financial Indexes/15. Price Index vs. PerformanceTotal Return Index.vtt 6.9 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/10. The S&P 500 Return Triangle (Part 1).vtt 6.9 kB
  • 19. Appendix 1 Python Crash Course (optional)/8. Data Types Tuples.vtt 6.9 kB
  • 6. Pandas Advanced Topics/17. Hierarchical Indexing with Groupby.vtt 6.8 kB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/3. It´s not that simple - Part 1 (Investments 101 vs. Real World).vtt 6.8 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/18. rollling() with fixed-sized time offsets.vtt 6.8 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/11. Cyclical vs. non-cyclical Stocks - another Intuition on Beta.vtt 6.8 kB
  • 6. Pandas Advanced Topics/21. Coding Exercise 9 (Solution).vtt 6.7 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/5. Upsampling with resample().vtt 6.6 kB
  • 6. Pandas Advanced Topics/11. Coding Exercise 8 (Solution).vtt 6.6 kB
  • 19. Appendix 1 Python Crash Course (optional)/12. Key words break, pass, continue.vtt 6.5 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/1. Helpful DatetimeIndex Attributes and Methods.vtt 6.4 kB
  • 4. Pandas Intermediate Topics/5. EXCURSUS Updating Pandas Anaconda.vtt 6.4 kB
  • 8. Time Series Data in Pandas Introduction/11. The PeriodIndex object.vtt 6.4 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/5. Financial Analyst Challenge (Solution Part 3).vtt 6.4 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/8. SMA and Bollinger Bands with Plotly.vtt 6.3 kB
  • 11. Create and Analyze Financial Indexes/7. Equal-Weighted Index - Theory.vtt 6.3 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/6. Numpy Arrays Boolean Indexing.vtt 6.3 kB
  • 5. Data Visualization with Matplotlib and Seaborn/7. First Steps with Seaborn.vtt 6.3 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/4. Numpy Arrays Shape and Dimensions.vtt 6.2 kB
  • 20. Appendix 2 Numpy Crash Course (optional)/8. Performance Issues.vtt 6.2 kB
  • 8. Time Series Data in Pandas Introduction/3. Initial Analysis Visualization of Time Series.vtt 6.1 kB
  • 11. Create and Analyze Financial Indexes/14. Comparison of weighting methods.vtt 6.1 kB
  • 3. Pandas Basics/3. First Steps (Inspection of Data, Part 1).vtt 6.1 kB
  • 4. Pandas Intermediate Topics/12. First Steps with Pandas Index Objects.vtt 6.0 kB
  • 1. Getting Started/2. Tips How to get the most out of this Course.vtt 6.0 kB
  • 3. Pandas Basics/16. Selecting Rows with loc (label-based indexing).vtt 5.8 kB
  • 4. Pandas Intermediate Topics/20. nunique() and nlargest() nsmallest() with DataFrames.vtt 5.7 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/6. Interactive Histograms with Plotly.vtt 5.6 kB
  • 8. Time Series Data in Pandas Introduction/8. Coding Exercise 10 (Solution).vtt 5.6 kB
  • 1. Getting Started/4. FAQ Important Information.html 5.6 kB
  • 8. Time Series Data in Pandas Introduction/14. Coding Exercise 11 (Solution).vtt 5.5 kB
  • 3. Pandas Basics/14. Slicing Rows and Columns with iloc (position-based indexing).vtt 5.5 kB
  • 3. Pandas Basics/1. Intro to Tabular Data Pandas.vtt 5.5 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/4. Initial Inspection and Visualization.vtt 5.5 kB
  • 6. Pandas Advanced Topics/2. Removing Columns.vtt 5.4 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/9. Sharpe Ratio - visualized and explained.vtt 5.4 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/19. Merging Aligning Financial Time Series (hands-on).vtt 5.3 kB
  • 4. Pandas Intermediate Topics/11. Coding Exercise 3 (Solution).vtt 5.3 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/3. resample() and agg().vtt 5.3 kB
  • 4. Pandas Intermediate Topics/23. Filtering DataFrames by many Conditions (OR).vtt 5.2 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/16. Expanding Windows.vtt 5.2 kB
  • 14. Forward-looking Mean-Variance Optimization & Asset Allocation/1. Intro.vtt 5.1 kB
  • 3. Pandas Basics/10. Explore your own Dataset Coding Exercise 1 (Solution).vtt 5.1 kB
  • 6. Pandas Advanced Topics/9. Manipulating Elements in a DataFrame.vtt 5.1 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/7. Financial Analyst Challenge (Solution Part 5).vtt 5.1 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/15. Exponentially-weighted Moving Averages (EWMA).vtt 5.1 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/5. Customizing Plotly Charts.vtt 5.0 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/11. Financial Time Series - Covariance and Correlation.vtt 5.0 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/5. What is the Sharpe Ratio and a Risk Free Asset.vtt 4.9 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/7. Timezones and Converting (Part 2).vtt 4.9 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/4. Interactive Price Charts with Plotly.vtt 4.9 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/6. Financial Analyst Challenge (Solution Part 4).vtt 4.9 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/8. Shifting Dates with pd.DateOffset().vtt 4.8 kB
  • 4. Pandas Intermediate Topics/15. Renaming Index & Column Labels with rename().vtt 4.8 kB
  • 5. Data Visualization with Matplotlib and Seaborn/4. Histogramms (Part 1).vtt 4.8 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/6. Timezones and Converting (Part 1).vtt 4.8 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/14. The S&P 500 Weather Radar.vtt 4.7 kB
  • 4. Pandas Intermediate Topics/7. The copy() method.vtt 4.7 kB
  • 4. Pandas Intermediate Topics/22. Filtering DataFrames by many Conditions (AND).vtt 4.7 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/7. Candle-Stick and OHLC Charts with Plotly.vtt 4.6 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/13. The S&P 500 Dollar Triangle.vtt 4.3 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/1. Intro.vtt 4.3 kB
  • 4. Pandas Intermediate Topics/25. any() and all().vtt 4.2 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/2. Financial Analyst Challenge (Instruction & Hints).vtt 4.1 kB
  • 3. Pandas Basics/12. Selecting Rows with Square Brackets (not advisable).vtt 4.1 kB
  • 4. Pandas Intermediate Topics/18. Coding Exercise 4 (Solution).vtt 4.0 kB
  • 4. Pandas Intermediate Topics/33. The agg() method.vtt 3.8 kB
  • 11. Create and Analyze Financial Indexes/3. Getting the Data.vtt 3.6 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/2. Capital Market Line (CML) & Two-Fund-Theorem.vtt 3.6 kB
  • 4. Pandas Intermediate Topics/14. Changing Column Labels.vtt 3.6 kB
  • 6. Pandas Advanced Topics/4. Adding new Columns to a DataFrame.vtt 3.5 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/9. Advanced Date Shifting.vtt 3.5 kB
  • 1. Getting Started/3. Did you know that....vtt 3.4 kB
  • 8. Time Series Data in Pandas Introduction/6. More on pd.date_range().vtt 3.2 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/11. Coding Exercise 15 (Intro).vtt 3.1 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/20. Coding Exercise 13 (intro).vtt 2.9 kB
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/1. Intro.vtt 2.8 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/13. Coding Exercise 16 (Intro).vtt 2.8 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/12. Coding Exercise 12 (intro).vtt 2.7 kB
  • 19. Appendix 1 Python Crash Course (optional)/1. Intro.vtt 2.6 kB
  • 4. Pandas Intermediate Topics/31. Exporting DataFrames to csv.vtt 2.5 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/2. Getting Ready (Installing required library).vtt 2.5 kB
  • 6. Pandas Advanced Topics/12. Introduction to GroupBy Operations.vtt 2.4 kB
  • 12. Create, Analyze and Optimize Financial Portfolios/2. Getting the Data.vtt 2.2 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/3. Financial Analyst Challenge (Solution Part 1).vtt 2.2 kB
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/1. Intro.vtt 2.1 kB
  • 4. Pandas Intermediate Topics/34. Coding Exercise 6 (Intro).vtt 2.0 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/9. More Technical Indicators with Plotly (Volume, MACD, DMI).vtt 1.9 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/1. Intro.vtt 1.8 kB
  • 15. Interactive Financial Charts with Plotly and Cufflinks/2. Getting Ready (Installing required libraries).vtt 1.6 kB
  • 11. Create and Analyze Financial Indexes/16. Coding Exercise 14 (intro).vtt 1.6 kB
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/1. Financial Analyst Challenge (Intro).vtt 1.6 kB
  • 4. Pandas Intermediate Topics/10. Coding Exercise 3 (Intro).vtt 1.6 kB
  • 3. Pandas Basics/21. Coding Exercise 2 (Intro).vtt 1.5 kB
  • 17. ---------- PART 4 ADVANCED TOPICS ----------------/4. resample() and OHLC().vtt 1.5 kB
  • 4. Pandas Intermediate Topics/27. Coding Exercise 5 (Intro).vtt 1.4 kB
  • 5. Data Visualization with Matplotlib and Seaborn/1. Intro.html 1.4 kB
  • 8. Time Series Data in Pandas Introduction/7. Coding Exercise 10 (intro).vtt 1.4 kB
  • 4. Pandas Intermediate Topics/17. Coding Exercise 4 (Intro).vtt 1.2 kB
  • 8. Time Series Data in Pandas Introduction/13. Coding Exercise 11 (intro).vtt 1.2 kB
  • 7. ----- PART 2 FINANCIAL DATA ANALYSIS ------/1. Welcome.html 1.1 kB
  • 6. Pandas Advanced Topics/7. Adding new Rows (Hands-on).html 1.1 kB
  • 6. Pandas Advanced Topics/20. Coding Exercise 9 (Intro).vtt 1.0 kB
  • 5. Data Visualization with Matplotlib and Seaborn/11. Coding Exercise 7 (Intro).vtt 1.0 kB
  • 6. Pandas Advanced Topics/10. Coding Exercise 8 (Intro).vtt 1.0 kB
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/1. Intro.html 969 Bytes
  • 16. ----- PART 3 THE FINANCIAL ANALYST CHALLENGE (FINAL PROJECT) ----/10. Additional Bonus Question.html 957 Bytes
  • 2. -- PART 1 DATA ANALYSIS WITH PYTHON & PANDAS FROM ZERO TO HERO --/1. Welcome to Part 1 Intro.html 757 Bytes
  • 4. Pandas Intermediate Topics/1. Intro.html 708 Bytes
  • 3. Pandas Basics/15. Position-based Indexing Cheat Sheets.html 700 Bytes
  • 3. Pandas Basics/18. Label-based Indexing Cheat Sheets.html 700 Bytes
  • 6. Pandas Advanced Topics/1. Intro.html 423 Bytes
  • 15. Interactive Financial Charts with Plotly and Cufflinks/10. Coding Exercise 17.html 407 Bytes
  • 3. Pandas Basics/2. Tabular Data Cheat Sheets.html 383 Bytes
  • 4. Pandas Intermediate Topics/4. UPDATE Pandas Version 0.24.0 (Jan 2019).html 369 Bytes
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/12. Interpreting the Return Triangle.html 146 Bytes
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/5. Trading Strategies.html 146 Bytes
  • 10. Financial Data - Advanced Techniques (Rolling Statistics & Reporting)/9. Simple Returns vs. Log Returns.html 146 Bytes
  • 11. Create and Analyze Financial Indexes/11. VWI.html 146 Bytes
  • 11. Create and Analyze Financial Indexes/2. Financial Indexes.html 146 Bytes
  • 11. Create and Analyze Financial Indexes/5. PWI.html 146 Bytes
  • 11. Create and Analyze Financial Indexes/8. EWI.html 146 Bytes
  • 12. Create, Analyze and Optimize Financial Portfolios/10. Portfolios.html 146 Bytes
  • 12. Create, Analyze and Optimize Financial Portfolios/7. Sharpe Ratio and Risk Free Asset.html 146 Bytes
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/12. Beta and Alpha.html 146 Bytes
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/3. Two-Fund-Theorem.html 146 Bytes
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/6. Risk Diversification.html 146 Bytes
  • 13. Modern Portfolio Theory & Asset Pricing (CAPM, Beta, Alpha, SLM & Risk divers.)/8. CAPM.html 146 Bytes
  • 19. Appendix 1 Python Crash Course (optional)/18. Python Basics.html 146 Bytes
  • 20. Appendix 2 Numpy Crash Course (optional)/12. Numpy.html 146 Bytes
  • 3. Pandas Basics/20. Indexing and Slicing.html 146 Bytes
  • 3. Pandas Basics/8. First Steps.html 146 Bytes
  • 4. Pandas Intermediate Topics/16. Pandas Index Objects.html 146 Bytes
  • 4. Pandas Intermediate Topics/26. Sorting and Filtering.html 146 Bytes
  • 4. Pandas Intermediate Topics/9. Pandas Series.html 146 Bytes
  • 6. Pandas Advanced Topics/19. GroupBy.html 146 Bytes
  • 9. Financial Data - Essential Workflows (Risk, Return & Correlation)/10. Risk & Return.html 146 Bytes
  • 0. Websites you may like/[FCS Forum].url 133 Bytes
  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 0. Websites you may like/[CourseClub.ME].url 122 Bytes
  • 18. ------------------ APPENDIX -------------------/1. Welcome to the Appendix.html 66 Bytes
  • 21. Bonus/1. Bonus Lecture.html 66 Bytes

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