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

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视频 2023-8-17 07:47 2024-11-20 21:53 177 18.36 GB 184
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GetFreeCourses Co-Udemy-Python for Finance 2021 Financial Analysis for Investing

文件列表
  1. 1. Introduction/1. One Question.mp443.21MB
  2. 1. Introduction/2. Get the most out of this course.mp475.17MB
  3. 10. Data Sources/1. Introduction.mp420.16MB
  4. 10. Data Sources/10. Exercises.mp457.07MB
  5. 10. Data Sources/11. Solutions.mp4166.28MB
  6. 10. Data Sources/12. What did we learn.mp425.04MB
  7. 10. Data Sources/2. What will we learn.mp465.9MB
  8. 10. Data Sources/3. Pandas Datareader - Remote Data Access for Pandas.mp432.91MB
  9. 10. Data Sources/4. Jupyter Notebook Pandas Datareader - Part I.mp4249.43MB
  10. 10. Data Sources/5. Jupyter Notebook Pandas Datareader - Part II.mp4121.68MB
  11. 10. Data Sources/6. The Yahoo! Finance API - read Financial Statements.mp453.56MB
  12. 10. Data Sources/7. Jupyter Notebook Yahoo! Finance - Financial Statements.mp4164.91MB
  13. 10. Data Sources/8. Web Scraping.mp458.62MB
  14. 10. Data Sources/9. Jupyter Notebook Web Scraping.mp4211.58MB
  15. 11. Time Series Data/1. Introduction.mp471.07MB
  16. 11. Time Series Data/2. Rate of Return, Percentage Change, and Normalization.mp4121.94MB
  17. 11. Time Series Data/3. Jupyter Notebook Rate of Return, Percentage Change, and Normalization.mp4136.02MB
  18. 11. Time Series Data/4. CAGR.mp441.45MB
  19. 11. Time Series Data/5. Jupyter Notebook CAGR.mp4103.37MB
  20. 11. Time Series Data/6. Jupyter Notebook Multiple Time Frames.mp4105.11MB
  21. 11. Time Series Data/7. Case Study DOW Theory.mp4323.58MB
  22. 11. Time Series Data/8. Jupyter Notebook Case Study DOW Theory.mp4193.72MB
  23. 11. Time Series Data/9. What did we learn.mp429.3MB
  24. 12. Technical Indicators/1. Introduction.mp453.82MB
  25. 12. Technical Indicators/10. Jupyter Notebook Exporting to Excel.mp4245.65MB
  26. 12. Technical Indicators/11. Jupyter Notebook Using our Excel Sheet.mp4143.37MB
  27. 12. Technical Indicators/12. Exercises.mp479.65MB
  28. 12. Technical Indicators/13. Solutions.mp4138.49MB
  29. 12. Technical Indicators/14. What did we learn.mp418.25MB
  30. 12. Technical Indicators/2. What is a Technical Indicator and Types of Indicators.mp4147.52MB
  31. 12. Technical Indicators/3. Indicator Moving Average.mp4103.25MB
  32. 12. Technical Indicators/4. Jupyter Notebook Simple Moving Average (MA).mp4184.47MB
  33. 12. Technical Indicators/5. Jupyter Notebook Exponential Moving Average (EMA).mp492.89MB
  34. 12. Technical Indicators/6. Indicator MACD.mp489.8MB
  35. 12. Technical Indicators/7. Jupyter Notebook MACD.mp4155.76MB
  36. 12. Technical Indicators/8. Indicator Stochastic Oscillator.mp478.8MB
  37. 12. Technical Indicators/9. Jupyter Notebook Stochastic Oscillator.mp4170.34MB
  38. 13. NumPy/1. Introduction.mp4121.09MB
  39. 13. NumPy/10. What did we learn.mp449.17MB
  40. 13. NumPy/2. Jupyter Notebook Introduction to NumPy.mp4154.96MB
  41. 13. NumPy/3. Jupyter Notebook Index, Slicing, and Views.mp4124.46MB
  42. 13. NumPy/4. Jupyter Notebook DataFrames and Series with NumPy.mp4172.53MB
  43. 13. NumPy/5. Jupyter Notebook Vectorization with NumPy.mp4139.81MB
  44. 13. NumPy/6. Jupyter Notebook Matplotlib and NumPy.mp4126.76MB
  45. 13. NumPy/7. Jupyter Notebook Dot product and Transpose.mp4156.52MB
  46. 13. NumPy/8. Exercises.mp485.88MB
  47. 13. NumPy/9. Solutions.mp4144.54MB
  48. 14. Correlation and Linear Regression/1. Introduction.mp430.77MB
  49. 14. Correlation and Linear Regression/10. Jupyter Notebook Beta Calculations.mp4109.41MB
  50. 14. Correlation and Linear Regression/11. CAPM.mp488.02MB
  51. 14. Correlation and Linear Regression/12. Jupyter Notebook CAPM Calculations.mp4105.22MB
  52. 14. Correlation and Linear Regression/13. Exercises.mp455.36MB
  53. 14. Correlation and Linear Regression/14. Solutions.mp4107.06MB
  54. 14. Correlation and Linear Regression/15. What did we learn.mp439.55MB
  55. 14. Correlation and Linear Regression/2. Adjusted Close.mp447.95MB
  56. 14. Correlation and Linear Regression/3. Volatility of a Stock.mp4106.65MB
  57. 14. Correlation and Linear Regression/4. Jupyter Notebook Volatility Calculations.mp4213.26MB
  58. 14. Correlation and Linear Regression/5. Correlation Between Securities.mp445.22MB
  59. 14. Correlation and Linear Regression/6. Jupyter Notebook Correlation Calculations.mp493.97MB
  60. 14. Correlation and Linear Regression/7. Linear Regression.mp472.35MB
  61. 14. Correlation and Linear Regression/8. Jupyter Notebook Linear Regression.mp4169.36MB
  62. 14. Correlation and Linear Regression/9. Beta.mp442.59MB
  63. 15. Working with Portfolios and Monte Carlo Simulations/1. Introduction.mp430.75MB
  64. 15. Working with Portfolios and Monte Carlo Simulations/10. Exercises.mp458.58MB
  65. 15. Working with Portfolios and Monte Carlo Simulations/11. Solutions.mp4155.06MB
  66. 15. Working with Portfolios and Monte Carlo Simulations/12. What did we learn.mp432.42MB
  67. 15. Working with Portfolios and Monte Carlo Simulations/2. Portfolios.mp428.6MB
  68. 15. Working with Portfolios and Monte Carlo Simulations/3. Jupyter Notebook Portfolio.mp4135.94MB
  69. 15. Working with Portfolios and Monte Carlo Simulations/4. Sharpe Ratio.mp454.2MB
  70. 15. Working with Portfolios and Monte Carlo Simulations/5. Jupyter Notebook Sharpe Ratio Calculations.mp4126.59MB
  71. 15. Working with Portfolios and Monte Carlo Simulations/6. Monte Carlo Simulations.mp478.1MB
  72. 15. Working with Portfolios and Monte Carlo Simulations/7. Jupyter Notebook Monte Carlo Simulations - Introduction.mp4154.87MB
  73. 15. Working with Portfolios and Monte Carlo Simulations/8. Jupyter Notebook Portfolios and Monte Carlo Simulations.mp4157.84MB
  74. 15. Working with Portfolios and Monte Carlo Simulations/9. Jupyter Notebook The Efficient Frontier.mp463.97MB
  75. 16. Finish Line/1. Introduction.mp419.97MB
  76. 16. Finish Line/2. 3 Books to Read.mp4231.77MB
  77. 16. Finish Line/3. Goodbye.mp444.94MB
  78. 2. Setup/1. Introduction.mp410.86MB
  79. 2. Setup/2. Download Anaconda (includes Python and Jupyter notebook).mp423.63MB
  80. 2. Setup/3. Resources and setup environment in Jupyter notebook.mp474.25MB
  81. 2. Setup/4. Prompt rating.mp412.18MB
  82. 3. Jupyter Notebook guide/1. Introduction.mp420.12MB
  83. 3. Jupyter Notebook guide/3. Jupyter Notebook The Dashboard.mp456.08MB
  84. 3. Jupyter Notebook guide/4. Jupyter Notebook Run and restart a Notebook.mp453.53MB
  85. 3. Jupyter Notebook guide/5. Jupyter Notebook Copy and reorganize code.mp427.42MB
  86. 3. Jupyter Notebook guide/6. Jupyter Notebook Comment and markdown.mp433.08MB
  87. 3. Jupyter Notebook guide/7. Jupyter Notebook Tab + Tab + Shift & Tab.mp482.17MB
  88. 3. Jupyter Notebook guide/8. What did we learn.mp419.77MB
  89. 4. Python Crash Course/1. Introduction.mp424.77MB
  90. 4. Python Crash Course/10. Other types.mp453.86MB
  91. 4. Python Crash Course/11. Functions.mp459.73MB
  92. 4. Python Crash Course/12. Lambda functions.mp4109.56MB
  93. 4. Python Crash Course/13. Exercises.mp472.71MB
  94. 4. Python Crash Course/14. Solutions.mp4164.74MB
  95. 4. Python Crash Course/15. New to Python We have all been there.mp472.23MB
  96. 4. Python Crash Course/16. What did we learn.mp427MB
  97. 4. Python Crash Course/2. Variables and types.mp4157.86MB
  98. 4. Python Crash Course/3. The print statement.mp439.35MB
  99. 4. Python Crash Course/4. Boolean expressions.mp482.59MB
  100. 4. Python Crash Course/5. If statements.mp474.06MB
  101. 4. Python Crash Course/6. Python lists.mp471.68MB
  102. 4. Python Crash Course/7. For-loops.mp462.36MB
  103. 4. Python Crash Course/8. While loops.mp435.63MB
  104. 4. Python Crash Course/9. Python Dictionaries (dict).mp453.99MB
  105. 5. Lemonade Stand/1. Introduction.mp428.94MB
  106. 5. Lemonade Stand/10. Dividend a story - an easy way to understand them.mp476.94MB
  107. 5. Lemonade Stand/11. Jupyter Notebook Dividend.mp4180.79MB
  108. 5. Lemonade Stand/12. What did we learn.mp455.7MB
  109. 5. Lemonade Stand/2. Intrinsic Value.mp477.57MB
  110. 5. Lemonade Stand/3. Introduction to the Lemonade Stand.mp4117.85MB
  111. 5. Lemonade Stand/4. The Lemonade Stand - the easy to understand example.mp499.67MB
  112. 5. Lemonade Stand/5. Jupyter Notebook The Lemonade Stand.mp4193.4MB
  113. 5. Lemonade Stand/6. Shares.mp4101.17MB
  114. 5. Lemonade Stand/7. Shares a story - Understand what they really are.mp4121.18MB
  115. 5. Lemonade Stand/8. Jupyter Notebook Shares.mp4158.17MB
  116. 5. Lemonade Stand/9. Dividend.mp489.41MB
  117. 6. Pandas/1. Introduction.mp4137.59MB
  118. 6. Pandas/10. Read and Write with Pandas - Part II.mp4156.61MB
  119. 6. Pandas/11. Read and Write with Pandas - Part III.mp4155.98MB
  120. 6. Pandas/12. Merge - Join - Concatenate - Part I.mp4112.59MB
  121. 6. Pandas/13. Merge - Join - Concatenate - Part II.mp468.43MB
  122. 6. Pandas/14. Transpose and clean data.mp4110.79MB
  123. 6. Pandas/15. Views.mp476.58MB
  124. 6. Pandas/16. Useful methods to know.mp4111.34MB
  125. 6. Pandas/17. Apply - an awesome method to master.mp477.88MB
  126. 6. Pandas/18. Exercises.mp474.33MB
  127. 6. Pandas/19. Solutions.mp4139.83MB
  128. 6. Pandas/2. Introduction to Pandas - a small demonstration.mp4156.46MB
  129. 6. Pandas/20. What did we learn.mp447.15MB
  130. 6. Pandas/3. Series.mp4159.69MB
  131. 6. Pandas/4. DataFrames - Part I.mp4167.25MB
  132. 6. Pandas/5. DataFrames - Part II.mp4107.46MB
  133. 6. Pandas/6. DataFrames - Part III.mp4117.88MB
  134. 6. Pandas/7. DataFrames - Part IV.mp498.67MB
  135. 6. Pandas/8. DataFrames - Part V.mp4104.4MB
  136. 6. Pandas/9. Read and Write with Pandas - Part I.mp4165.71MB
  137. 7. Intrinsic Value/1. Introduction.mp426.71MB
  138. 7. Intrinsic Value/10. Current ratio - Evaluation.mp474.59MB
  139. 7. Intrinsic Value/11. Jupyter Notebook - Current ratio.mp4148.28MB
  140. 7. Intrinsic Value/12. Stable and predictable.mp4160.68MB
  141. 7. Intrinsic Value/13. Return of Investment (ROI) - Evaluation.mp4105.9MB
  142. 7. Intrinsic Value/14. Jupyter Notebook Return of Investment.mp4135.97MB
  143. 7. Intrinsic Value/15. Revenue - Evaluation.mp494.66MB
  144. 7. Intrinsic Value/16. Jupyter Notebook Revenue.mp4230.69MB
  145. 7. Intrinsic Value/17. Earnings Per Share (EPS) - Evaluation.mp443.19MB
  146. 7. Intrinsic Value/18. Jupyter Notebook Earnings Per Share (EPS).mp4120.1MB
  147. 7. Intrinsic Value/19. Book Value - Evaluation.mp484.2MB
  148. 7. Intrinsic Value/2. Outcome of section.mp4141.02MB
  149. 7. Intrinsic Value/20. Jupyter Notebook Book Value.mp4160.54MB
  150. 7. Intrinsic Value/21. Free Cash Flow (FCF) - Evaluation.mp438.95MB
  151. 7. Intrinsic Value/22. Jupyter Notebook Free Cash Flow (FCF).mp466.14MB
  152. 7. Intrinsic Value/23. Combine All Data.mp469.22MB
  153. 7. Intrinsic Value/24. Jupyter Notebook Combine All Data.mp4141.16MB
  154. 7. Intrinsic Value/25. Calculate a Fair Price (Intrinsic Value).mp4139.51MB
  155. 7. Intrinsic Value/26. Price-to-Earnings (PE) ratio.mp455.15MB
  156. 7. Intrinsic Value/27. Jupyter Notebook Price-to-Earnings (PE) ratio.mp473.37MB
  157. 7. Intrinsic Value/28. Jupyter Notebook Calculate a Fair Price (Intrinsic Value).mp4129.82MB
  158. 7. Intrinsic Value/29. Compare it with Current Price.mp4127.87MB
  159. 7. Intrinsic Value/3. Understand Risk - Part I.mp493.63MB
  160. 7. Intrinsic Value/30. What did we learn.mp499.88MB
  161. 7. Intrinsic Value/4. Understand Risk - Part II.mp464.16MB
  162. 7. Intrinsic Value/5. Understand Rik - Part III.mp461.79MB
  163. 7. Intrinsic Value/6. Understand Risk - All put together.mp457.04MB
  164. 7. Intrinsic Value/7. Evaluate Leadership.mp4205.56MB
  165. 7. Intrinsic Value/8. Debt-to-Equity ration - Evaluation.mp493.65MB
  166. 7. Intrinsic Value/9. Jupyter Notebook Debt-to-Equity ratio.mp4278.31MB
  167. 8. Matplotlib/1. Introduction.mp420.95MB
  168. 8. Matplotlib/10. Solutions.mp4188.52MB
  169. 8. Matplotlib/11. What did we learn.mp431.51MB
  170. 8. Matplotlib/2. Overview of section.mp4104.6MB
  171. 8. Matplotlib/3. Jupyter Notebook Matplotlib basics.mp4120.74MB
  172. 8. Matplotlib/4. Jupyter Notebook Work with Axis.mp4115.37MB
  173. 8. Matplotlib/5. Jupyter Notebook Title and Labels.mp4104.81MB
  174. 8. Matplotlib/6. Jupyter Notebook Matplotlib and Pandas.mp496.98MB
  175. 8. Matplotlib/7. Jupyter Notebook Pandas and data structures.mp4146.08MB
  176. 8. Matplotlib/8. Jupyter Notebook Bar plots.mp4114.01MB
  177. 8. Matplotlib/9. Exercises.mp476.14MB
  178. 9. Visualization and Excel Export of Financial Data/1. Introduction.mp433.21MB
  179. 9. Visualization and Excel Export of Financial Data/2. Matplotlib - Part I.mp4200.63MB
  180. 9. Visualization and Excel Export of Financial Data/3. Matplotlib - Part II.mp4179.81MB
  181. 9. Visualization and Excel Export of Financial Data/4. Export to Excel - Part I.mp4156.78MB
  182. 9. Visualization and Excel Export of Financial Data/5. Export to Excel - Part II.mp4249.24MB
  183. 9. Visualization and Excel Export of Financial Data/6. Export to Excel - Part III.mp4126.31MB
  184. 9. Visualization and Excel Export of Financial Data/7. What did we learn.mp444.05MB
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