GetFreeCourses.Co-Udemy-Python for Finance 2021 Financial Analysis for Investing

Creation Time	Oct. 11, 2023, 1:30 a.m.
Last Access Time	Nov. 6, 2024, 1:08 a.m.
File Size	18.4 GB
Keywords	Financial Finance for Investing Analysis GetFreeCourses 2021 Co-Udemy-Python
Total Requests	69
Total Files	403
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

11. Time Series Data/7. Case Study DOW Theory.mp4 323.6 MB
7. Intrinsic Value/9. Jupyter Notebook Debt-to-Equity ratio.mp4 278.3 MB
10. Data Sources/4. Jupyter Notebook Pandas Datareader - Part I.mp4 249.4 MB
9. Visualization and Excel Export of Financial Data/5. Export to Excel - Part II.mp4 249.2 MB
12. Technical Indicators/10. Jupyter Notebook Exporting to Excel.mp4 245.6 MB
16. Finish Line/2. 3 Books to Read.mp4 231.8 MB
7. Intrinsic Value/16. Jupyter Notebook Revenue.mp4 230.7 MB
14. Correlation and Linear Regression/4. Jupyter Notebook Volatility Calculations.mp4 213.3 MB
10. Data Sources/9. Jupyter Notebook Web Scraping.mp4 211.6 MB
7. Intrinsic Value/7. Evaluate Leadership.mp4 205.6 MB
9. Visualization and Excel Export of Financial Data/2. Matplotlib - Part I.mp4 200.6 MB
11. Time Series Data/8. Jupyter Notebook Case Study DOW Theory.mp4 193.7 MB
5. Lemonade Stand/5. Jupyter Notebook The Lemonade Stand.mp4 193.4 MB
8. Matplotlib/10. Solutions.mp4 188.5 MB
12. Technical Indicators/4. Jupyter Notebook Simple Moving Average (MA).mp4 184.5 MB
5. Lemonade Stand/11. Jupyter Notebook Dividend.mp4 180.8 MB
9. Visualization and Excel Export of Financial Data/3. Matplotlib - Part II.mp4 179.8 MB
13. NumPy/4. Jupyter Notebook DataFrames and Series with NumPy.mp4 172.5 MB
12. Technical Indicators/9. Jupyter Notebook Stochastic Oscillator.mp4 170.3 MB
14. Correlation and Linear Regression/8. Jupyter Notebook Linear Regression.mp4 169.4 MB
6. Pandas/4. DataFrames - Part I.mp4 167.2 MB
10. Data Sources/11. Solutions.mp4 166.3 MB
6. Pandas/9. Read and Write with Pandas - Part I.mp4 165.7 MB
10. Data Sources/7. Jupyter Notebook Yahoo! Finance - Financial Statements.mp4 164.9 MB
4. Python Crash Course/14. Solutions.mp4 164.7 MB
7. Intrinsic Value/12. Stable and predictable.mp4 160.7 MB
7. Intrinsic Value/20. Jupyter Notebook Book Value.mp4 160.5 MB
6. Pandas/3. Series.mp4 159.7 MB
5. Lemonade Stand/8. Jupyter Notebook Shares.mp4 158.2 MB
4. Python Crash Course/2. Variables and types.mp4 157.9 MB
15. Working with Portfolios and Monte Carlo Simulations/8. Jupyter Notebook Portfolios and Monte Carlo Simulations.mp4 157.8 MB
9. Visualization and Excel Export of Financial Data/4. Export to Excel - Part I.mp4 156.8 MB
6. Pandas/10. Read and Write with Pandas - Part II.mp4 156.6 MB
13. NumPy/7. Jupyter Notebook Dot product and Transpose.mp4 156.5 MB
6. Pandas/2. Introduction to Pandas - a small demonstration.mp4 156.5 MB
6. Pandas/11. Read and Write with Pandas - Part III.mp4 156.0 MB
12. Technical Indicators/7. Jupyter Notebook MACD.mp4 155.8 MB
15. Working with Portfolios and Monte Carlo Simulations/11. Solutions.mp4 155.1 MB
13. NumPy/2. Jupyter Notebook Introduction to NumPy.mp4 155.0 MB
15. Working with Portfolios and Monte Carlo Simulations/7. Jupyter Notebook Monte Carlo Simulations - Introduction.mp4 154.9 MB
7. Intrinsic Value/11. Jupyter Notebook - Current ratio.mp4 148.3 MB
12. Technical Indicators/2. What is a Technical Indicator and Types of Indicators.mp4 147.5 MB
8. Matplotlib/7. Jupyter Notebook Pandas and data structures.mp4 146.1 MB
13. NumPy/9. Solutions.mp4 144.5 MB
12. Technical Indicators/11. Jupyter Notebook Using our Excel Sheet.mp4 143.4 MB
7. Intrinsic Value/24. Jupyter Notebook Combine All Data.mp4 141.2 MB
7. Intrinsic Value/2. Outcome of section.mp4 141.0 MB
6. Pandas/19. Solutions.mp4 139.8 MB
13. NumPy/5. Jupyter Notebook Vectorization with NumPy.mp4 139.8 MB
7. Intrinsic Value/25. Calculate a Fair Price (Intrinsic Value).mp4 139.5 MB
12. Technical Indicators/13. Solutions.mp4 138.5 MB
6. Pandas/1. Introduction.mp4 137.6 MB
11. Time Series Data/3. Jupyter Notebook Rate of Return, Percentage Change, and Normalization.mp4 136.0 MB
7. Intrinsic Value/14. Jupyter Notebook Return of Investment.mp4 136.0 MB
15. Working with Portfolios and Monte Carlo Simulations/3. Jupyter Notebook Portfolio.mp4 135.9 MB
7. Intrinsic Value/28. Jupyter Notebook Calculate a Fair Price (Intrinsic Value).mp4 129.8 MB
7. Intrinsic Value/29. Compare it with Current Price.mp4 127.9 MB
13. NumPy/6. Jupyter Notebook Matplotlib and NumPy.mp4 126.8 MB
15. Working with Portfolios and Monte Carlo Simulations/5. Jupyter Notebook Sharpe Ratio Calculations.mp4 126.6 MB
9. Visualization and Excel Export of Financial Data/6. Export to Excel - Part III.mp4 126.3 MB
13. NumPy/3. Jupyter Notebook Index, Slicing, and Views.mp4 124.5 MB
11. Time Series Data/2. Rate of Return, Percentage Change, and Normalization.mp4 121.9 MB
10. Data Sources/5. Jupyter Notebook Pandas Datareader - Part II.mp4 121.7 MB
5. Lemonade Stand/7. Shares a story - Understand what they really are.mp4 121.2 MB
13. NumPy/1. Introduction.mp4 121.1 MB
8. Matplotlib/3. Jupyter Notebook Matplotlib basics.mp4 120.7 MB
7. Intrinsic Value/18. Jupyter Notebook Earnings Per Share (EPS).mp4 120.1 MB
6. Pandas/6. DataFrames - Part III.mp4 117.9 MB
5. Lemonade Stand/3. Introduction to the Lemonade Stand.mp4 117.9 MB
8. Matplotlib/4. Jupyter Notebook Work with Axis.mp4 115.4 MB
8. Matplotlib/8. Jupyter Notebook Bar plots.mp4 114.0 MB
6. Pandas/12. Merge - Join - Concatenate - Part I.mp4 112.6 MB
6. Pandas/16. Useful methods to know.mp4 111.3 MB
6. Pandas/14. Transpose and clean data.mp4 110.8 MB
4. Python Crash Course/12. Lambda functions.mp4 109.6 MB
14. Correlation and Linear Regression/10. Jupyter Notebook Beta Calculations.mp4 109.4 MB
6. Pandas/5. DataFrames - Part II.mp4 107.5 MB
14. Correlation and Linear Regression/14. Solutions.mp4 107.1 MB
14. Correlation and Linear Regression/3. Volatility of a Stock.mp4 106.6 MB
7. Intrinsic Value/13. Return of Investment (ROI) - Evaluation.mp4 105.9 MB
14. Correlation and Linear Regression/12. Jupyter Notebook CAPM Calculations.mp4 105.2 MB
11. Time Series Data/6. Jupyter Notebook Multiple Time Frames.mp4 105.1 MB
8. Matplotlib/5. Jupyter Notebook Title and Labels.mp4 104.8 MB
8. Matplotlib/2. Overview of section.mp4 104.6 MB
6. Pandas/8. DataFrames - Part V.mp4 104.4 MB
11. Time Series Data/5. Jupyter Notebook CAGR.mp4 103.4 MB
12. Technical Indicators/3. Indicator Moving Average.mp4 103.2 MB
5. Lemonade Stand/6. Shares.mp4 101.2 MB
7. Intrinsic Value/30. What did we learn.mp4 99.9 MB
5. Lemonade Stand/4. The Lemonade Stand - the easy to understand example.mp4 99.7 MB
6. Pandas/7. DataFrames - Part IV.mp4 98.7 MB
8. Matplotlib/6. Jupyter Notebook Matplotlib and Pandas.mp4 97.0 MB
7. Intrinsic Value/15. Revenue - Evaluation.mp4 94.7 MB
14. Correlation and Linear Regression/6. Jupyter Notebook Correlation Calculations.mp4 94.0 MB
7. Intrinsic Value/8. Debt-to-Equity ration - Evaluation.mp4 93.7 MB
7. Intrinsic Value/3. Understand Risk - Part I.mp4 93.6 MB
12. Technical Indicators/5. Jupyter Notebook Exponential Moving Average (EMA).mp4 92.9 MB
12. Technical Indicators/6. Indicator MACD.mp4 89.8 MB
5. Lemonade Stand/9. Dividend.mp4 89.4 MB
14. Correlation and Linear Regression/11. CAPM.mp4 88.0 MB
13. NumPy/8. Exercises.mp4 85.9 MB
7. Intrinsic Value/19. Book Value - Evaluation.mp4 84.2 MB
4. Python Crash Course/4. Boolean expressions.mp4 82.6 MB
3. Jupyter Notebook guide/7. Jupyter Notebook Tab + Tab + Shift & Tab.mp4 82.2 MB
12. Technical Indicators/12. Exercises.mp4 79.7 MB
12. Technical Indicators/8. Indicator Stochastic Oscillator.mp4 78.8 MB
15. Working with Portfolios and Monte Carlo Simulations/6. Monte Carlo Simulations.mp4 78.1 MB
6. Pandas/17. Apply - an awesome method to master.mp4 77.9 MB
5. Lemonade Stand/2. Intrinsic Value.mp4 77.6 MB
5. Lemonade Stand/10. Dividend a story - an easy way to understand them.mp4 76.9 MB
6. Pandas/15. Views.mp4 76.6 MB
8. Matplotlib/9. Exercises.mp4 76.1 MB
1. Introduction/2. Get the most out of this course.mp4 75.2 MB
7. Intrinsic Value/10. Current ratio - Evaluation.mp4 74.6 MB
6. Pandas/18. Exercises.mp4 74.3 MB
2. Setup/3. Resources and setup environment in Jupyter notebook.mp4 74.2 MB
4. Python Crash Course/5. If statements.mp4 74.1 MB
7. Intrinsic Value/27. Jupyter Notebook Price-to-Earnings (PE) ratio.mp4 73.4 MB
4. Python Crash Course/13. Exercises.mp4 72.7 MB
14. Correlation and Linear Regression/7. Linear Regression.mp4 72.4 MB
4. Python Crash Course/15. New to Python We have all been there.mp4 72.2 MB
4. Python Crash Course/6. Python lists.mp4 71.7 MB
11. Time Series Data/1. Introduction.mp4 71.1 MB
7. Intrinsic Value/23. Combine All Data.mp4 69.2 MB
6. Pandas/13. Merge - Join - Concatenate - Part II.mp4 68.4 MB
7. Intrinsic Value/22. Jupyter Notebook Free Cash Flow (FCF).mp4 66.1 MB
10. Data Sources/2. What will we learn.mp4 65.9 MB
7. Intrinsic Value/4. Understand Risk - Part II.mp4 64.2 MB
15. Working with Portfolios and Monte Carlo Simulations/9. Jupyter Notebook The Efficient Frontier.mp4 64.0 MB
4. Python Crash Course/7. For-loops.mp4 62.4 MB
7. Intrinsic Value/5. Understand Rik - Part III.mp4 61.8 MB
4. Python Crash Course/11. Functions.mp4 59.7 MB
10. Data Sources/8. Web Scraping.mp4 58.6 MB
15. Working with Portfolios and Monte Carlo Simulations/10. Exercises.mp4 58.6 MB
10. Data Sources/10. Exercises.mp4 57.1 MB
7. Intrinsic Value/6. Understand Risk - All put together.mp4 57.0 MB
3. Jupyter Notebook guide/3. Jupyter Notebook The Dashboard.mp4 56.1 MB
5. Lemonade Stand/12. What did we learn.mp4 55.7 MB
14. Correlation and Linear Regression/13. Exercises.mp4 55.4 MB
7. Intrinsic Value/26. Price-to-Earnings (PE) ratio.mp4 55.2 MB
15. Working with Portfolios and Monte Carlo Simulations/4. Sharpe Ratio.mp4 54.2 MB
4. Python Crash Course/9. Python Dictionaries (dict).mp4 54.0 MB
4. Python Crash Course/10. Other types.mp4 53.9 MB
12. Technical Indicators/1. Introduction.mp4 53.8 MB
10. Data Sources/6. The Yahoo! Finance API - read Financial Statements.mp4 53.6 MB
3. Jupyter Notebook guide/4. Jupyter Notebook Run and restart a Notebook.mp4 53.5 MB
13. NumPy/10. What did we learn.mp4 49.2 MB
14. Correlation and Linear Regression/2. Adjusted Close.mp4 48.0 MB
6. Pandas/20. What did we learn.mp4 47.1 MB
14. Correlation and Linear Regression/5. Correlation Between Securities.mp4 45.2 MB
16. Finish Line/3. Goodbye.mp4 44.9 MB
9. Visualization and Excel Export of Financial Data/7. What did we learn.mp4 44.1 MB
1. Introduction/1. One Question.mp4 43.2 MB
7. Intrinsic Value/17. Earnings Per Share (EPS) - Evaluation.mp4 43.2 MB
14. Correlation and Linear Regression/9. Beta.mp4 42.6 MB
11. Time Series Data/4. CAGR.mp4 41.5 MB
14. Correlation and Linear Regression/15. What did we learn.mp4 39.6 MB
4. Python Crash Course/3. The print statement.mp4 39.4 MB
7. Intrinsic Value/21. Free Cash Flow (FCF) - Evaluation.mp4 39.0 MB
4. Python Crash Course/8. While loops.mp4 35.6 MB
9. Visualization and Excel Export of Financial Data/1. Introduction.mp4 33.2 MB
3. Jupyter Notebook guide/6. Jupyter Notebook Comment and markdown.mp4 33.1 MB
10. Data Sources/3. Pandas Datareader - Remote Data Access for Pandas.mp4 32.9 MB
15. Working with Portfolios and Monte Carlo Simulations/12. What did we learn.mp4 32.4 MB
8. Matplotlib/11. What did we learn.mp4 31.5 MB
14. Correlation and Linear Regression/1. Introduction.mp4 30.8 MB
15. Working with Portfolios and Monte Carlo Simulations/1. Introduction.mp4 30.8 MB
11. Time Series Data/9. What did we learn.mp4 29.3 MB
5. Lemonade Stand/1. Introduction.mp4 28.9 MB
15. Working with Portfolios and Monte Carlo Simulations/2. Portfolios.mp4 28.6 MB
3. Jupyter Notebook guide/5. Jupyter Notebook Copy and reorganize code.mp4 27.4 MB
4. Python Crash Course/16. What did we learn.mp4 27.0 MB
7. Intrinsic Value/1. Introduction.mp4 26.7 MB
10. Data Sources/12. What did we learn.mp4 25.0 MB
4. Python Crash Course/1. Introduction.mp4 24.8 MB
2. Setup/2. Download Anaconda (includes Python and Jupyter notebook).mp4 23.6 MB
8. Matplotlib/1. Introduction.mp4 20.9 MB
10. Data Sources/1. Introduction.mp4 20.2 MB
3. Jupyter Notebook guide/1. Introduction.mp4 20.1 MB
16. Finish Line/1. Introduction.mp4 20.0 MB
3. Jupyter Notebook guide/8. What did we learn.mp4 19.8 MB
2. Setup/3.1 PyFinance.zip 19.0 MB
12. Technical Indicators/14. What did we learn.mp4 18.2 MB
2. Setup/4. Prompt rating.mp4 12.2 MB
2. Setup/1. Introduction.mp4 10.9 MB
3. Jupyter Notebook guide/2.2 Jupyter Cheat Sheet - PC.pdf 555.8 KB
3. Jupyter Notebook guide/2.1 Jupyter Cheat Sheet - MAC.pdf 555.4 KB
6. Pandas/1.1 Pandas_Cheat_Sheet.pdf 337.8 KB
6. Pandas/12.1 Pandas_Cheat_Sheet.pdf 337.8 KB
4. Python Crash Course/16.1 04 - Python Cheat Sheet.pdf 135.6 KB
7. Intrinsic Value/9. Jupyter Notebook Debt-to-Equity ratio.srt 28.3 KB
14. Correlation and Linear Regression/4. Jupyter Notebook Volatility Calculations.srt 27.7 KB
12. Technical Indicators/10. Jupyter Notebook Exporting to Excel.srt 27.3 KB
10. Data Sources/4. Jupyter Notebook Pandas Datareader - Part I.srt 26.5 KB
9. Visualization and Excel Export of Financial Data/5. Export to Excel - Part II.srt 26.4 KB
11. Time Series Data/7. Case Study DOW Theory.srt 24.9 KB
7. Intrinsic Value/16. Jupyter Notebook Revenue.srt 24.1 KB
10. Data Sources/9. Jupyter Notebook Web Scraping.srt 23.3 KB
5. Lemonade Stand/5. Jupyter Notebook The Lemonade Stand.srt 23.3 KB
11. Time Series Data/8. Jupyter Notebook Case Study DOW Theory.srt 22.0 KB
9. Visualization and Excel Export of Financial Data/2. Matplotlib - Part I.srt 21.5 KB
9. Visualization and Excel Export of Financial Data/3. Matplotlib - Part II.srt 21.3 KB
15. Working with Portfolios and Monte Carlo Simulations/7. Jupyter Notebook Monte Carlo Simulations - Introduction.srt 21.2 KB
13. NumPy/2. Jupyter Notebook Introduction to NumPy.srt 21.1 KB
12. Technical Indicators/4. Jupyter Notebook Simple Moving Average (MA).srt 20.3 KB
13. NumPy/4. Jupyter Notebook DataFrames and Series with NumPy.srt 20.2 KB
8. Matplotlib/10. Solutions.srt 19.9 KB
14. Correlation and Linear Regression/8. Jupyter Notebook Linear Regression.srt 19.7 KB
15. Working with Portfolios and Monte Carlo Simulations/8. Jupyter Notebook Portfolios and Monte Carlo Simulations.srt 19.4 KB
4. Python Crash Course/14. Solutions.srt 19.0 KB
5. Lemonade Stand/11. Jupyter Notebook Dividend.srt 19.0 KB
10. Data Sources/7. Jupyter Notebook Yahoo! Finance - Financial Statements.srt 18.9 KB
5. Lemonade Stand/8. Jupyter Notebook Shares.srt 18.9 KB
15. Working with Portfolios and Monte Carlo Simulations/11. Solutions.srt 18.7 KB
16. Finish Line/2. 3 Books to Read.srt 18.5 KB
12. Technical Indicators/9. Jupyter Notebook Stochastic Oscillator.srt 18.2 KB
6. Pandas/4. DataFrames - Part I.srt 17.6 KB
7. Intrinsic Value/20. Jupyter Notebook Book Value.srt 17.6 KB
12. Technical Indicators/7. Jupyter Notebook MACD.srt 17.5 KB
6. Pandas/3. Series.srt 17.5 KB
9. Visualization and Excel Export of Financial Data/4. Export to Excel - Part I.srt 17.0 KB
10. Data Sources/11. Solutions.srt 16.7 KB
6. Pandas/2. Introduction to Pandas - a small demonstration.srt 16.5 KB
6. Pandas/10. Read and Write with Pandas - Part II.srt 16.3 KB
15. Working with Portfolios and Monte Carlo Simulations/5. Jupyter Notebook Sharpe Ratio Calculations.srt 15.8 KB
4. Python Crash Course/2. Variables and types.srt 15.8 KB
13. NumPy/7. Jupyter Notebook Dot product and Transpose.srt 15.7 KB
7. Intrinsic Value/24. Jupyter Notebook Combine All Data.srt 15.7 KB
15. Working with Portfolios and Monte Carlo Simulations/3. Jupyter Notebook Portfolio.srt 15.4 KB
12. Technical Indicators/11. Jupyter Notebook Using our Excel Sheet.srt 15.4 KB
7. Intrinsic Value/14. Jupyter Notebook Return of Investment.srt 15.1 KB
13. NumPy/3. Jupyter Notebook Index, Slicing, and Views.srt 15.0 KB
10. Data Sources/5. Jupyter Notebook Pandas Datareader - Part II.srt 15.0 KB
7. Intrinsic Value/11. Jupyter Notebook - Current ratio.srt 14.9 KB
6. Pandas/9. Read and Write with Pandas - Part I.srt 14.9 KB
11. Time Series Data/3. Jupyter Notebook Rate of Return, Percentage Change, and Normalization.srt 14.7 KB
13. NumPy/9. Solutions.srt 14.7 KB
13. NumPy/5. Jupyter Notebook Vectorization with NumPy.srt 14.6 KB
6. Pandas/19. Solutions.srt 14.1 KB
7. Intrinsic Value/18. Jupyter Notebook Earnings Per Share (EPS).srt 14.0 KB
6. Pandas/11. Read and Write with Pandas - Part III.srt 14.0 KB
9. Visualization and Excel Export of Financial Data/6. Export to Excel - Part III.srt 13.6 KB
14. Correlation and Linear Regression/10. Jupyter Notebook Beta Calculations.srt 13.6 KB
8. Matplotlib/8. Jupyter Notebook Bar plots.srt 13.6 KB
13. NumPy/6. Jupyter Notebook Matplotlib and NumPy.srt 13.5 KB
8. Matplotlib/7. Jupyter Notebook Pandas and data structures.srt 13.4 KB
8. Matplotlib/3. Jupyter Notebook Matplotlib basics.srt 13.3 KB
7. Intrinsic Value/7. Evaluate Leadership.srt 13.3 KB
7. Intrinsic Value/29. Compare it with Current Price.srt 13.2 KB
12. Technical Indicators/13. Solutions.srt 13.1 KB
7. Intrinsic Value/28. Jupyter Notebook Calculate a Fair Price (Intrinsic Value).srt 12.9 KB
8. Matplotlib/5. Jupyter Notebook Title and Labels.srt 12.4 KB
8. Matplotlib/4. Jupyter Notebook Work with Axis.srt 12.4 KB
14. Correlation and Linear Regression/12. Jupyter Notebook CAPM Calculations.srt 12.3 KB
11. Time Series Data/5. Jupyter Notebook CAGR.srt 11.9 KB
7. Intrinsic Value/12. Stable and predictable.srt 11.8 KB
14. Correlation and Linear Regression/6. Jupyter Notebook Correlation Calculations.srt 11.6 KB
6. Pandas/16. Useful methods to know.srt 11.6 KB
6. Pandas/12. Merge - Join - Concatenate - Part I.srt 11.4 KB
11. Time Series Data/6. Jupyter Notebook Multiple Time Frames.srt 11.3 KB
6. Pandas/8. DataFrames - Part V.srt 11.1 KB
6. Pandas/7. DataFrames - Part IV.srt 11.1 KB
14. Correlation and Linear Regression/14. Solutions.srt 10.9 KB
4. Python Crash Course/12. Lambda functions.srt 10.8 KB
6. Pandas/5. DataFrames - Part II.srt 10.6 KB
6. Pandas/6. DataFrames - Part III.srt 10.6 KB
12. Technical Indicators/5. Jupyter Notebook Exponential Moving Average (EMA).srt 10.3 KB
6. Pandas/14. Transpose and clean data.srt 10.2 KB
8. Matplotlib/6. Jupyter Notebook Matplotlib and Pandas.srt 10.0 KB
7. Intrinsic Value/25. Calculate a Fair Price (Intrinsic Value).srt 9.8 KB
6. Pandas/1. Introduction.srt 9.7 KB
12. Technical Indicators/2. What is a Technical Indicator and Types of Indicators.srt 9.7 KB
5. Lemonade Stand/7. Shares a story - Understand what they really are.srt 9.5 KB
13. NumPy/8. Exercises.srt 9.5 KB
7. Intrinsic Value/2. Outcome of section.srt 9.4 KB
3. Jupyter Notebook guide/7. Jupyter Notebook Tab + Tab + Shift & Tab.srt 9.4 KB
12. Technical Indicators/12. Exercises.srt 9.0 KB
5. Lemonade Stand/10. Dividend a story - an easy way to understand them.srt 8.4 KB
11. Time Series Data/2. Rate of Return, Percentage Change, and Normalization.srt 8.3 KB
5. Lemonade Stand/3. Introduction to the Lemonade Stand.srt 8.2 KB
13. NumPy/1. Introduction.srt 7.9 KB
5. Lemonade Stand/4. The Lemonade Stand - the easy to understand example.srt 7.9 KB
7. Intrinsic Value/13. Return of Investment (ROI) - Evaluation.srt 7.9 KB
4. Python Crash Course/4. Boolean expressions.srt 7.9 KB
6. Pandas/17. Apply - an awesome method to master.srt 7.7 KB
6. Pandas/18. Exercises.srt 7.6 KB
4. Python Crash Course/13. Exercises.srt 7.5 KB
8. Matplotlib/9. Exercises.srt 7.4 KB
6. Pandas/15. Views.srt 7.4 KB
14. Correlation and Linear Regression/3. Volatility of a Stock.srt 7.3 KB
7. Intrinsic Value/27. Jupyter Notebook Price-to-Earnings (PE) ratio.srt 7.2 KB
4. Python Crash Course/6. Python lists.srt 7.1 KB
15. Working with Portfolios and Monte Carlo Simulations/10. Exercises.srt 7.1 KB
7. Intrinsic Value/15. Revenue - Evaluation.srt 7.1 KB
12. Technical Indicators/3. Indicator Moving Average.srt 7.0 KB
15. Working with Portfolios and Monte Carlo Simulations/9. Jupyter Notebook The Efficient Frontier.srt 6.9 KB
7. Intrinsic Value/30. What did we learn.srt 6.8 KB
7. Intrinsic Value/22. Jupyter Notebook Free Cash Flow (FCF).srt 6.8 KB
8. Matplotlib/2. Overview of section.srt 6.6 KB
5. Lemonade Stand/6. Shares.srt 6.5 KB
4. Python Crash Course/7. For-loops.srt 6.5 KB
6. Pandas/13. Merge - Join - Concatenate - Part II.srt 6.4 KB
4. Python Crash Course/5. If statements.srt 6.2 KB
14. Correlation and Linear Regression/13. Exercises.srt 6.1 KB
14. Correlation and Linear Regression/11. CAPM.srt 6.0 KB
12. Technical Indicators/6. Indicator MACD.srt 6.0 KB
7. Intrinsic Value/3. Understand Risk - Part I.srt 6.0 KB
7. Intrinsic Value/8. Debt-to-Equity ration - Evaluation.srt 5.8 KB
2. Setup/3. Resources and setup environment in Jupyter notebook.srt 5.7 KB
1. Introduction/2. Get the most out of this course.srt 5.5 KB
4. Python Crash Course/9. Python Dictionaries (dict).srt 5.5 KB
10. Data Sources/10. Exercises.srt 5.4 KB
7. Intrinsic Value/19. Book Value - Evaluation.srt 5.4 KB
12. Technical Indicators/8. Indicator Stochastic Oscillator.srt 5.4 KB
4. Python Crash Course/11. Functions.srt 5.3 KB
11. Time Series Data/1. Introduction.srt 5.3 KB
5. Lemonade Stand/9. Dividend.srt 5.1 KB
4. Python Crash Course/10. Other types.srt 5.1 KB
15. Working with Portfolios and Monte Carlo Simulations/6. Monte Carlo Simulations.srt 5.0 KB
5. Lemonade Stand/2. Intrinsic Value.srt 5.0 KB
7. Intrinsic Value/23. Combine All Data.srt 4.8 KB
14. Correlation and Linear Regression/7. Linear Regression.srt 4.8 KB
3. Jupyter Notebook guide/3. Jupyter Notebook The Dashboard.srt 4.8 KB
4. Python Crash Course/15. New to Python We have all been there.srt 4.6 KB
3. Jupyter Notebook guide/4. Jupyter Notebook Run and restart a Notebook.srt 4.6 KB
7. Intrinsic Value/10. Current ratio - Evaluation.srt 4.4 KB
10. Data Sources/2. What will we learn.srt 4.2 KB
7. Intrinsic Value/5. Understand Rik - Part III.srt 4.2 KB
7. Intrinsic Value/4. Understand Risk - Part II.srt 4.0 KB
10. Data Sources/8. Web Scraping.srt 4.0 KB
10. Data Sources/6. The Yahoo! Finance API - read Financial Statements.srt 3.9 KB
7. Intrinsic Value/6. Understand Risk - All put together.srt 3.8 KB
4. Python Crash Course/3. The print statement.srt 3.8 KB
15. Working with Portfolios and Monte Carlo Simulations/4. Sharpe Ratio.srt 3.7 KB
12. Technical Indicators/1. Introduction.srt 3.6 KB
14. Correlation and Linear Regression/2. Adjusted Close.srt 3.5 KB
4. Python Crash Course/8. While loops.srt 3.5 KB
7. Intrinsic Value/26. Price-to-Earnings (PE) ratio.srt 3.3 KB
3. Jupyter Notebook guide/6. Jupyter Notebook Comment and markdown.srt 3.3 KB
1. Introduction/1. One Question.srt 3.1 KB
13. NumPy/10. What did we learn.srt 3.1 KB
7. Intrinsic Value/17. Earnings Per Share (EPS) - Evaluation.srt 3.1 KB
9. Visualization and Excel Export of Financial Data/7. What did we learn.srt 3.0 KB
5. Lemonade Stand/12. What did we learn.srt 3.0 KB
6. Pandas/20. What did we learn.srt 2.9 KB
16. Finish Line/3. Goodbye.srt 2.9 KB
14. Correlation and Linear Regression/9. Beta.srt 2.9 KB
3. Jupyter Notebook guide/5. Jupyter Notebook Copy and reorganize code.srt 2.8 KB
11. Time Series Data/4. CAGR.srt 2.8 KB
14. Correlation and Linear Regression/5. Correlation Between Securities.srt 2.8 KB
14. Correlation and Linear Regression/15. What did we learn.srt 2.5 KB
7. Intrinsic Value/21. Free Cash Flow (FCF) - Evaluation.srt 2.5 KB
14. Correlation and Linear Regression/1. Introduction.srt 2.4 KB
15. Working with Portfolios and Monte Carlo Simulations/12. What did we learn.srt 2.2 KB
11. Time Series Data/9. What did we learn.srt 2.2 KB
10. Data Sources/3. Pandas Datareader - Remote Data Access for Pandas.srt 2.2 KB
2. Setup/2. Download Anaconda (includes Python and Jupyter notebook).srt 2.1 KB
8. Matplotlib/11. What did we learn.srt 2.1 KB
9. Visualization and Excel Export of Financial Data/1. Introduction.srt 2.0 KB
15. Working with Portfolios and Monte Carlo Simulations/2. Portfolios.srt 2.0 KB
15. Working with Portfolios and Monte Carlo Simulations/1. Introduction.srt 1.9 KB
4. Python Crash Course/16. What did we learn.srt 1.8 KB
10. Data Sources/12. What did we learn.srt 1.7 KB
4. Python Crash Course/1. Introduction.srt 1.6 KB
5. Lemonade Stand/1. Introduction.srt 1.6 KB
7. Intrinsic Value/1. Introduction.srt 1.4 KB
16. Finish Line/1. Introduction.srt 1.3 KB
3. Jupyter Notebook guide/1. Introduction.srt 1.2 KB
10. Data Sources/1. Introduction.srt 1.2 KB
3. Jupyter Notebook guide/8. What did we learn.srt 1.2 KB
12. Technical Indicators/14. What did we learn.srt 1.1 KB
8. Matplotlib/1. Introduction.srt 1013 bytes
2. Setup/4. Prompt rating.srt 986 bytes
2. Setup/1. Introduction.srt 594 bytes
12. Technical Indicators/How you can help GetFreeCourses.Co.txt 182 bytes
4. Python Crash Course/How you can help GetFreeCourses.Co.txt 182 bytes
8. Matplotlib/How you can help GetFreeCourses.Co.txt 182 bytes
How you can help GetFreeCourses.Co.txt 182 bytes
2. Setup/3.2 Link to PyFinance.zip on Google Drive.html 143 bytes
6. Pandas/11.1 httpsen.wikipedia.orgwikiList_of_countries_by_past_and_projected_GDP_(PPP).html 140 bytes
8. Matplotlib/5.1 Matplotlib Overview.html 129 bytes
7. Intrinsic Value/26.1 Investopedia - Price-to-Earnings (PE) ratio.html 121 bytes
7. Intrinsic Value/13.1 Investopedia - Return of Investment (ROI).html 120 bytes
7. Intrinsic Value/8.1 Investopedia - Debt-to-equity ratio.html 117 bytes
12. Technical Indicators/Download Paid Udemy Courses For Free.url 116 bytes
12. Technical Indicators/GetFreeCourses.Co.url 116 bytes
4. Python Crash Course/Download Paid Udemy Courses For Free.url 116 bytes
4. Python Crash Course/GetFreeCourses.Co.url 116 bytes
8. Matplotlib/Download Paid Udemy Courses For Free.url 116 bytes
8. Matplotlib/GetFreeCourses.Co.url 116 bytes
Download Paid Udemy Courses For Free.url 116 bytes
GetFreeCourses.Co.url 116 bytes
7. Intrinsic Value/10.1 Investopedia - Current Ratio.html 114 bytes
7. Intrinsic Value/21.1 Investopeida - Free Cash Flow (FCF).html 114 bytes
7. Intrinsic Value/19.1 Investopedia - Book Value.html 111 bytes
7. Intrinsic Value/15.1 Investopedia - Revenue.html 109 bytes
7. Intrinsic Value/16.1 Investopedia - CAGR.html 106 bytes
7. Intrinsic Value/16.2 Investopedia - AAGR.html 106 bytes
9. Visualization and Excel Export of Financial Data/4.1 XLSX Writer - Format.html 106 bytes
2. Setup/2.2 Download link to Anaconda.html 105 bytes
7. Intrinsic Value/17.1 Investopedia - Earnings Per Share (EPS).html 105 bytes
2. Setup/2.1 Installation guides.html 104 bytes
3. Jupyter Notebook guide/2. Jupyter Notebook Cheat Sheet..html 77 bytes

GetFreeCourses.Co-Udemy-Python for Finance 2021 Financial Analysis for Investing

File List

Download Torrent

Related Resources

Copyright Infringement