FreeCourseSite com Udemy - Algorithmic Trading A-Z with Python Machine Learning & AWS

1. 1. Getting Started/1. What is Algorithmic Trading Course Overview.mp438.27MB
2. 1. Getting Started/2. How to get the best out of this course.mp437.57MB
3. 1. Getting Started/3. Did you know... (what Data can tell us about Day Trading).mp439.24MB
4. 10. Introduction to Time Series Data in Pandas/1. Importing Time Series Data from csv-files.mp434.42MB
5. 10. Introduction to Time Series Data in Pandas/2. Converting strings to datetime objects with pd.to_datetime().mp448.85MB
6. 10. Introduction to Time Series Data in Pandas/3. Indexing and Slicing Time Series.mp440.63MB
7. 10. Introduction to Time Series Data in Pandas/4. Downsampling Time Series with resample().mp472.18MB
8. 10. Introduction to Time Series Data in Pandas/5. Coding Exercise 1.mp435.91MB
9. 11. Financial Data Analysis with Pandas - an Introduction/1. Getting Ready (Installing required library).mp418.34MB
10. 11. Financial Data Analysis with Pandas - an Introduction/11. Simple Returns vs. Log Returns.mp432.65MB
11. 11. Financial Data Analysis with Pandas - an Introduction/12. Importing Financial Data from Excel.mp480.7MB
12. 11. Financial Data Analysis with Pandas - an Introduction/13. Simple Moving Averages (SMA) with rolling().mp440.98MB
13. 11. Financial Data Analysis with Pandas - an Introduction/14. Momentum Trading Strategies with SMAs.mp433.01MB
14. 11. Financial Data Analysis with Pandas - an Introduction/15. Exponentially-weighted Moving Averages (EWMA).mp423.79MB
15. 11. Financial Data Analysis with Pandas - an Introduction/16. Merging Aligning Financial Time Series (hands-on).mp425.9MB
16. 11. Financial Data Analysis with Pandas - an Introduction/2. Importing Stock Price Data from Yahoo Finance.mp458.5MB
17. 11. Financial Data Analysis with Pandas - an Introduction/3. Initial Inspection and Visualization.mp436.34MB
18. 11. Financial Data Analysis with Pandas - an Introduction/4. Normalizing Time Series to a Base Value (100).mp437.36MB
19. 11. Financial Data Analysis with Pandas - an Introduction/5. The shift() method.mp429.49MB
20. 11. Financial Data Analysis with Pandas - an Introduction/6. The methods diff() and pct_change().mp432.71MB
21. 11. Financial Data Analysis with Pandas - an Introduction/7. Measuring Stock Performance with MEAN Returns and STD of Returns.mp434.87MB
22. 11. Financial Data Analysis with Pandas - an Introduction/8. Financial Time Series - Return and Risk.mp444.93MB
23. 11. Financial Data Analysis with Pandas - an Introduction/9. Financial Time Series - Covariance and Correlation.mp421.04MB
24. 12. Advanced Topics/1. Helpful DatetimeIndex Attributes and Methods.mp437.38MB
25. 12. Advanced Topics/2. Filling NA Values with bfill, ffill and interpolation.mp468.43MB
26. 12. Advanced Topics/3. Timezones and Converting (Part 1).mp429.36MB
27. 12. Advanced Topics/4. Timezones and Converting (Part 2).mp436.91MB
28. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/1. Introduction to OOP and examples for Classes.mp463.75MB
29. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/10. The method set_ticker().mp425.15MB
30. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/11. Adding more methods and performance metrics.mp445.38MB
31. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/12. Inheritance.mp478.88MB
32. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/13. Inheritance and the super() Function.mp453.87MB
33. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/14. Adding meaningful Docstrings.mp450.03MB
34. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/15. Creating and Importing Python Modules (.py).mp420.8MB
35. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/16. Coding Exercise 3 Create your own Class.mp437.05MB
36. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/2. The Financial Analysis Class live in action (Part 1).mp427.26MB
37. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/3. The Financial Analysis Class live in action (Part 2).mp419.75MB
38. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/4. The special method __init__().mp435.03MB
39. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/5. The method get_data().mp442.74MB
40. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/6. The method log_returns().mp422.98MB
41. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/7. String representation and the special method __repr__().mp422.13MB
42. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/8. The methods plot_prices() and plot_returns().mp434.11MB
43. 13. Object Oriented Programming (OOP) Creating a Financial Analysis Class/9. Encapsulation and protected Attributes.mp424.06MB
44. 14. +++ PART 3 Defining and Testing Trading Strategies +++/1. Introduction to Part 3.mp441.33MB
45. 14. +++ PART 3 Defining and Testing Trading Strategies +++/2. Trading Strategies - an Overview.mp446.94MB
46. 14. +++ PART 3 Defining and Testing Trading Strategies +++/4. Getting the Data.mp420.26MB
47. 14. +++ PART 3 Defining and Testing Trading Strategies +++/5. A simple Buy and Hold Strategy.mp426.11MB
48. 14. +++ PART 3 Defining and Testing Trading Strategies +++/6. Performance Metrics.mp438.07MB
49. 15. Defining and Backtesting SMA Strategies/1. SMA Crossover Strategies - Overview.mp444.01MB
50. 15. Defining and Backtesting SMA Strategies/10. Creating the Class (Part 5).mp421.08MB
51. 15. Defining and Backtesting SMA Strategies/11. Creating the Class (Part 6).mp436.35MB
52. 15. Defining and Backtesting SMA Strategies/12. Creating the Class (Part 7).mp425.1MB
53. 15. Defining and Backtesting SMA Strategies/13. Creating the Class (Part 8).mp432.75MB
54. 15. Defining and Backtesting SMA Strategies/2. Defining an SMA Crossover Strategy.mp443.69MB
55. 15. Defining and Backtesting SMA Strategies/3. Vectorized Strategy Backtesting.mp458.33MB
56. 15. Defining and Backtesting SMA Strategies/4. Finding the optimal SMA Strategy.mp482.77MB
57. 15. Defining and Backtesting SMA Strategies/5. Generalization with OOP An SMA Backtesting Class in action.mp473.61MB
58. 15. Defining and Backtesting SMA Strategies/6. Creating the Class (Part 1).mp420.26MB
59. 15. Defining and Backtesting SMA Strategies/7. Creating the Class (Part 2).mp465.52MB
60. 15. Defining and Backtesting SMA Strategies/8. Creating the Class (Part 3).mp439.38MB
61. 15. Defining and Backtesting SMA Strategies/9. Creating the Class (Part 4).mp438.46MB
62. 16. Defining and Backtesting simple MomentumContrarian Strategies/1. Simple ContrarianMomentum Strategies - Overview.mp419.97MB
63. 16. Defining and Backtesting simple MomentumContrarian Strategies/10. OOP Challenge Create the Contrarian Backtesting Class (incl. Solution).mp437.69MB
64. 16. Defining and Backtesting simple MomentumContrarian Strategies/2. Getting the Data.mp415.39MB
65. 16. Defining and Backtesting simple MomentumContrarian Strategies/3. Excursus Your FAQs answered.mp431.16MB
66. 16. Defining and Backtesting simple MomentumContrarian Strategies/4. Defining a simple Contrarian Strategy.mp421.46MB
67. 16. Defining and Backtesting simple MomentumContrarian Strategies/5. Vectorized Strategy Backtesting.mp428.93MB
68. 16. Defining and Backtesting simple MomentumContrarian Strategies/6. Changing the Window Parameter.mp439.18MB
69. 16. Defining and Backtesting simple MomentumContrarian Strategies/7. Trades and Trading Costs (Part 1).mp459.04MB
70. 16. Defining and Backtesting simple MomentumContrarian Strategies/8. Trades and Trading Costs (Part 2).mp421.94MB
71. 16. Defining and Backtesting simple MomentumContrarian Strategies/9. Generalization with OOP A Contrarian Backtesting Class in action.mp460.65MB
72. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/1. Mean-Reversion Strategies - Overview.mp451.41MB
73. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/2. Getting the Data.mp411.62MB
74. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/3. Defining a Bollinger Bands Mean-Reversion Strategy (Part 1).mp429.79MB
75. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/4. Defining a Bollinger Bands Mean-Reversion Strategy (Part 2).mp470.65MB
76. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/5. Vectorized Strategy Backtesting.mp440.2MB
77. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/6. Generalization with OOP A Bollinger Bands Backtesting Class in action.mp450.74MB
78. 17. Defining and Backtesting Mean-Reversion Strategies (Bollinger)/7. OOP Challenge Create the Bollinger Bands Backtesting Class (incl. Solution).mp435.29MB
79. 18. Trading Strategies powered by Machine Learning - Regression/1. Machine Learning - an Overview.mp442.53MB
80. 18. Trading Strategies powered by Machine Learning - Regression/10. In-Sample Backtesting and the Look-ahead-bias.mp420.18MB
81. 18. Trading Strategies powered by Machine Learning - Regression/11. Out-Sample Forward Testing.mp430.44MB
82. 18. Trading Strategies powered by Machine Learning - Regression/2. Linear Regression with scikit-learn - a simple Introduction.mp448.3MB
83. 18. Trading Strategies powered by Machine Learning - Regression/3. Making Predictions with Linear Regression.mp416.24MB
84. 18. Trading Strategies powered by Machine Learning - Regression/4. Overfitting.mp438.4MB
85. 18. Trading Strategies powered by Machine Learning - Regression/5. Underfitting.mp423.56MB
86. 18. Trading Strategies powered by Machine Learning - Regression/6. Getting the Data.mp49.5MB
87. 18. Trading Strategies powered by Machine Learning - Regression/7. A simple Linear Model to predict Financial Returns (Part 1).mp417.79MB
88. 18. Trading Strategies powered by Machine Learning - Regression/8. A simple Linear Model to predict Financial Returns (Part 2).mp442.74MB
89. 18. Trading Strategies powered by Machine Learning - Regression/9. A Multiple Regression Model to predict Financial Returns.mp436.68MB
90. 19. Trading Strategies powered by Machine Learning - Classification/1. Logistic Regression with scikit-learn - a simple Introduction (Part 1).mp427.92MB
91. 19. Trading Strategies powered by Machine Learning - Classification/2. Logistic Regression with scikit-learn - a simple Introduction (Part 2).mp435.79MB
92. 19. Trading Strategies powered by Machine Learning - Classification/3. Getting and Preparing the Data.mp417.03MB
93. 19. Trading Strategies powered by Machine Learning - Classification/4. Predicting Market Direction with Logistic Regression.mp427.44MB
94. 19. Trading Strategies powered by Machine Learning - Classification/5. In-Sample Backtesting and the Look-ahead-bias.mp414.19MB
95. 19. Trading Strategies powered by Machine Learning - Classification/6. Out-Sample Forward Testing.mp420.11MB
96. 19. Trading Strategies powered by Machine Learning - Classification/7. Generalization with OOP A Classification Backtesting Class in action.mp473.47MB
97. 19. Trading Strategies powered by Machine Learning - Classification/8. The Classification Backtesting Class explained (Part 1).mp454.45MB
98. 19. Trading Strategies powered by Machine Learning - Classification/9. The Classification Backtesting Class explained (Part 2).mp435.22MB
99. 2. +++ PART 1 Day Trading, Online Brokers and APIs +++/1. Our very first Trade.mp413.9MB
100. 2. +++ PART 1 Day Trading, Online Brokers and APIs +++/2. Long Term Investing vs. (Algorithmic) Day Trading.mp430.9MB
101. 2. +++ PART 1 Day Trading, Online Brokers and APIs +++/3. Spot Trading vs. Derivatives Trading (Part 1).mp457.79MB
102. 2. +++ PART 1 Day Trading, Online Brokers and APIs +++/4. Spot Trading vs. Derivatives Trading (Part 2).mp467.47MB
103. 2. +++ PART 1 Day Trading, Online Brokers and APIs +++/5. Overview & the Brokers OANDA and FXCM.mp430.27MB
104. 20. Advanced Backtesting Techniques/1. Introduction to Iterative Backtesting (event-driven).mp430.12MB
105. 20. Advanced Backtesting Techniques/10. Creating an Iterative Base Class (Part 7).mp450.4MB
106. 20. Advanced Backtesting Techniques/11. Creating an Iterative Base Class (Part 8).mp456.36MB
107. 20. Advanced Backtesting Techniques/12. Adding the Iterative Backtest Child Class for SMA (Part 1).mp453.08MB
108. 20. Advanced Backtesting Techniques/13. Adding the Iterative Backtest Child Class for SMA (Part 2).mp478.37MB
109. 20. Advanced Backtesting Techniques/14. Using Modules and adding Docstrings.mp438.88MB
110. 20. Advanced Backtesting Techniques/15. OOP Challenge Add Contrarian and Bollinger Strategies.mp465.82MB
111. 20. Advanced Backtesting Techniques/2. A first Intuition on Iterative Backtesting (Part 1).mp434.82MB
112. 20. Advanced Backtesting Techniques/3. A first Intuition on Iterative Backtesting (Part 2).mp438.02MB
113. 20. Advanced Backtesting Techniques/4. Creating an Iterative Base Class (Part 1).mp427.18MB
114. 20. Advanced Backtesting Techniques/5. Creating an Iterative Base Class (Part 2).mp416.92MB
115. 20. Advanced Backtesting Techniques/6. Creating an Iterative Base Class (Part 3).mp415.15MB
116. 20. Advanced Backtesting Techniques/7. Creating an Iterative Base Class (Part 4).mp449.37MB
117. 20. Advanced Backtesting Techniques/8. Creating an Iterative Base Class (Part 5).mp439.36MB
118. 20. Advanced Backtesting Techniques/9. Creating an Iterative Base Class (Part 6).mp433.79MB
119. 21. +++ PART 4 Real-time Implementation and Automation of Strategies +++/1. Introduction and Overview.mp410.78MB
120. 22. Implementation and Automation with OANDA (UPDATED!)/10. Storing and resampling real-time tick data (Part 4).mp464.12MB
121. 22. Implementation and Automation with OANDA (UPDATED!)/11. Storing and resampling real-time tick data (Part 5).mp430.87MB
122. 22. Implementation and Automation with OANDA (UPDATED!)/12. Working with historical data and real-time tick data (Part 1).mp449.43MB
123. 22. Implementation and Automation with OANDA (UPDATED!)/13. Working with historical data and real-time tick data (Part 2).mp449.06MB
124. 22. Implementation and Automation with OANDA (UPDATED!)/14. Working with historical data and real-time tick data (Part 3).mp430.04MB
125. 22. Implementation and Automation with OANDA (UPDATED!)/15. Defining a simple Contrarian Strategy.mp451.66MB
126. 22. Implementation and Automation with OANDA (UPDATED!)/16. Placing Orders and Executing Trades.mp457.49MB
127. 22. Implementation and Automation with OANDA (UPDATED!)/17. Trade Monitoring and Reporting.mp484.56MB
128. 22. Implementation and Automation with OANDA (UPDATED!)/18. Trading other Strategies - Coding Challenge.mp412.56MB
129. 22. Implementation and Automation with OANDA (UPDATED!)/19. Implementing an SMA Crossover Strategy (Solution).mp437.04MB
130. 22. Implementation and Automation with OANDA (UPDATED!)/2. Updating the Wrapper Package (Part 2).mp425.41MB
131. 22. Implementation and Automation with OANDA (UPDATED!)/20. Implementing a Bollinger Bands Strategy (Solution).mp430.4MB
132. 22. Implementation and Automation with OANDA (UPDATED!)/21. Machine Learning Strategies (1) - Model Fitting.mp433.75MB
133. 22. Implementation and Automation with OANDA (UPDATED!)/22. Machine Learning Strategies (2) - Implementation.mp461.58MB
134. 22. Implementation and Automation with OANDA (UPDATED!)/23. Importing a Trader Module Class.mp419.19MB
135. 22. Implementation and Automation with OANDA (UPDATED!)/25. Running a Python Trader Script.mp458.72MB
136. 22. Implementation and Automation with OANDA (UPDATED!)/4. Historical Data, real-time Data and Orders (Recap).mp472.76MB
137. 22. Implementation and Automation with OANDA (UPDATED!)/5. Preview A Trader Class live in action.mp447.96MB
138. 22. Implementation and Automation with OANDA (UPDATED!)/6. How to collect and store real-time tick data.mp440.41MB
139. 22. Implementation and Automation with OANDA (UPDATED!)/7. Storing and resampling real-time tick data (Part 1).mp459.83MB
140. 22. Implementation and Automation with OANDA (UPDATED!)/8. Storing and resampling real-time tick data (Part 2).mp445.99MB
141. 22. Implementation and Automation with OANDA (UPDATED!)/9. Storing and resampling real-time tick data (Part 3).mp432.13MB
142. 23. Implementation and Automation with FXCM (Updated!)/10. Working with historical data and real-time tick data (Part 1).mp434.52MB
143. 23. Implementation and Automation with FXCM (Updated!)/11. Working with historical data and real-time tick data (Part 2).mp449.57MB
144. 23. Implementation and Automation with FXCM (Updated!)/12. Working with historical data and real-time tick data (Part 3).mp429.94MB
145. 23. Implementation and Automation with FXCM (Updated!)/13. Defining a Simple Contrarian Trading Strategy.mp442.25MB
146. 23. Implementation and Automation with FXCM (Updated!)/14. Placing Orders and Executing Trades.mp458.21MB
147. 23. Implementation and Automation with FXCM (Updated!)/15. Trade Monitoring and Reporting.mp456.16MB
148. 23. Implementation and Automation with FXCM (Updated!)/16. Trading other Strategies - Coding Challenge.mp414.07MB
149. 23. Implementation and Automation with FXCM (Updated!)/17. SMA Crossover and Bollinger Bands (Solution).mp441.79MB
150. 23. Implementation and Automation with FXCM (Updated!)/18. Machine Learning Strategies (1) - Model Fitting.mp433.86MB
151. 23. Implementation and Automation with FXCM (Updated!)/19. Machine Learning Strategies (2) - Implementation.mp453.91MB
152. 23. Implementation and Automation with FXCM (Updated!)/2. Historical Data, real-time Data and Orders (Recap).mp465.82MB
153. 23. Implementation and Automation with FXCM (Updated!)/21. Running a Python Script.mp447.66MB
154. 23. Implementation and Automation with FXCM (Updated!)/4. Preview A Trader Class live in action.mp450.8MB
155. 23. Implementation and Automation with FXCM (Updated!)/5. Collecting and storing real-time tick data.mp453.99MB
156. 23. Implementation and Automation with FXCM (Updated!)/6. Storing and resampling real-time tick data (Part 1).mp464.55MB
157. 23. Implementation and Automation with FXCM (Updated!)/7. A Trader Class.mp439.47MB
158. 23. Implementation and Automation with FXCM (Updated!)/8. Storing and resampling real-time tick data (Part 2).mp468.17MB
159. 23. Implementation and Automation with FXCM (Updated!)/9. Storing and resampling real-time tick data (Part 3).mp425.25MB
160. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/1. Introduction and Motivation.mp420.22MB
161. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/10. How to schedule Trading sessions with the Task Scheduler.mp439.23MB
162. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/11. How to stop Trading Sessions (OANDA).mp449.48MB
163. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/12. How to stop Trading Sessions (FXCM).mp445.87MB
164. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/2. Demonstration AWS EC2 for Algorithmic Trading live in action.mp454.72MB
165. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/3. Amazon Web Services (AWS) - Overview and how to create a Free Trial Account.mp418.24MB
166. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/4. How to create an EC2 Instance.mp471.79MB
167. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/5. How to connect to your EC2 Instance.mp433.13MB
168. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/6. Getting the Instance Ready for Algorithmic Trading.mp460.04MB
169. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/8. How to run Python Scripts in a Windows Command Prompt.mp429.98MB
170. 24. Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/9. How to start Trading sessions with Batch (.bat) Files.mp431.63MB
171. 25. +++ PART 5 Expert Tips & Tricks, Case Studies and more +++/1. Overview.mp410.23MB
172. 26. Trading Hours, Spreads and Granularity - control and limit Trading Costs!/1. Introduction and Preparing the Data.mp436.83MB
173. 26. Trading Hours, Spreads and Granularity - control and limit Trading Costs!/2. The best time to trade (Part 1).mp419.04MB
174. 26. Trading Hours, Spreads and Granularity - control and limit Trading Costs!/3. The best time to trade (Part 2).mp419.06MB
175. 26. Trading Hours, Spreads and Granularity - control and limit Trading Costs!/4. Spreads during the busy hours.mp413.24MB
176. 26. Trading Hours, Spreads and Granularity - control and limit Trading Costs!/5. The Impact of Granularity.mp428.19MB
177. 26. Trading Hours, Spreads and Granularity - control and limit Trading Costs!/6. Conclusions.mp418.02MB
178. 27. Working with two or many Strategies (Combination)/1. Introduction.mp411.47MB
179. 27. Working with two or many Strategies (Combination)/2. Strategy 1 SMA.mp413.27MB
180. 27. Working with two or many Strategies (Combination)/3. Strategy 2 Mean Reversion.mp414.55MB
181. 27. Working with two or many Strategies (Combination)/4. Combining both Strategies - Alternative 1.mp437.47MB
182. 27. Working with two or many Strategies (Combination)/5. Taking into account busy Trading Hours.mp415.21MB
183. 27. Working with two or many Strategies (Combination)/6. Strategy Backtesting.mp410.87MB
184. 27. Working with two or many Strategies (Combination)/7. Combining both Strategies - Alternative 2.mp422.17MB
185. 27. Working with two or many Strategies (Combination)/8. Strategy Optimization.mp468.54MB
186. 28. A Machine Learning-powered Strategy A-Z (DNN)/1. Project Overview.mp423.79MB
187. 28. A Machine Learning-powered Strategy A-Z (DNN)/10. Prediction & Out-Sample Forward Testing.mp448.27MB
188. 28. A Machine Learning-powered Strategy A-Z (DNN)/11. Saving Model and Parameters.mp418.24MB
189. 28. A Machine Learning-powered Strategy A-Z (DNN)/13. Implementation (Oanda & FXCM).mp4112.43MB
190. 28. A Machine Learning-powered Strategy A-Z (DNN)/3. Installation of Tensorflow & Keras (Part 2).mp449.81MB
191. 28. A Machine Learning-powered Strategy A-Z (DNN)/4. Getting and Preparing the Data.mp48.43MB
192. 28. A Machine Learning-powered Strategy A-Z (DNN)/5. Adding LabelsFeatures.mp437.73MB
193. 28. A Machine Learning-powered Strategy A-Z (DNN)/6. Adding lags.mp419.23MB
194. 28. A Machine Learning-powered Strategy A-Z (DNN)/7. Splitting into Train and Test Set.mp49.83MB
195. 28. A Machine Learning-powered Strategy A-Z (DNN)/8. Feature ScalingEngineering.mp426.39MB
196. 28. A Machine Learning-powered Strategy A-Z (DNN)/9. Creating and Fitting the DNN Model.mp447.63MB
197. 29. Error Handling How to make your Trading Bot more stable and reliable/1. Introduction.mp419.55MB
198. 29. Error Handling How to make your Trading Bot more stable and reliable/10. How to limit the number of retries.mp413.68MB
199. 29. Error Handling How to make your Trading Bot more stable and reliable/11. Waiting periods between re-tries.mp425.86MB
200. 29. Error Handling How to make your Trading Bot more stable and reliable/12. Implementation with Oanda V20 Connection Issues.mp436.15MB
201. 29. Error Handling How to make your Trading Bot more stable and reliable/13. Oanda Error Handling (Part 1).mp444.54MB
202. 29. Error Handling How to make your Trading Bot more stable and reliable/14. Oanda Error Handling (Part 2).mp464.14MB
203. 29. Error Handling How to make your Trading Bot more stable and reliable/15. Oanda Error Handling (Part 3).mp434.55MB
204. 29. Error Handling How to make your Trading Bot more stable and reliable/16. Implementation with FXCM APIServer Issues.mp420.83MB
205. 29. Error Handling How to make your Trading Bot more stable and reliable/17. FXCM Error Handling (Part 1).mp441.84MB
206. 29. Error Handling How to make your Trading Bot more stable and reliable/18. FXCM Error Handling (Part 2).mp438.16MB
207. 29. Error Handling How to make your Trading Bot more stable and reliable/3. Python Errors (Exceptions).mp46.83MB
208. 29. Error Handling How to make your Trading Bot more stable and reliable/4. try and except.mp48.89MB
209. 29. Error Handling How to make your Trading Bot more stable and reliable/5. Catching specific Errors.mp47.56MB
210. 29. Error Handling How to make your Trading Bot more stable and reliable/6. The Exception class.mp45.67MB
211. 29. Error Handling How to make your Trading Bot more stable and reliable/7. try, except, else.mp425.15MB
212. 29. Error Handling How to make your Trading Bot more stable and reliable/8. finally.mp420.12MB
213. 29. Error Handling How to make your Trading Bot more stable and reliable/9. Try again (...until it works).mp421.27MB
214. 3. Day Trading with OANDA A-Z a Deep Dive/1. OANDA at a first glance.mp465.91MB
215. 3. Day Trading with OANDA A-Z a Deep Dive/10. Our third Trade A-Z - Going Short EURUSD.mp461.88MB
216. 3. Day Trading with OANDA A-Z a Deep Dive/11. Netting vs. Hedging.mp460.84MB
217. 3. Day Trading with OANDA A-Z a Deep Dive/12. Market, Limit and Stop Orders.mp439.27MB
218. 3. Day Trading with OANDA A-Z a Deep Dive/13. Take-Profit and Stop-Loss Orders.mp424.44MB
219. 3. Day Trading with OANDA A-Z a Deep Dive/14. A more general Example.mp430.79MB
220. 3. Day Trading with OANDA A-Z a Deep Dive/2. How to create an Account.mp448.28MB
221. 3. Day Trading with OANDA A-Z a Deep Dive/3. FOREX Currency Exchange Rates explained.mp459.54MB
222. 3. Day Trading with OANDA A-Z a Deep Dive/4. Our second Trade - EURUSD FOREX Trading.mp442.93MB
223. 3. Day Trading with OANDA A-Z a Deep Dive/5. How to calculate Profit & Loss of a Trade.mp448.85MB
224. 3. Day Trading with OANDA A-Z a Deep Dive/6. Trading Costs and Performance Attribution.mp469.54MB
225. 3. Day Trading with OANDA A-Z a Deep Dive/7. Margin and Leverage.mp470.56MB
226. 3. Day Trading with OANDA A-Z a Deep Dive/8. Margin Closeout and more.mp441.31MB
227. 3. Day Trading with OANDA A-Z a Deep Dive/9. Introduction to Charting.mp439.66MB
228. 30. +++ APPENDIX Python Crash Course +++/1. Overview.mp46.85MB
229. 31. Appendix 1 Python (& Finance) Basics/10. More on Variables and Memory.mp422.22MB
230. 31. Appendix 1 Python (& Finance) Basics/11. Variables - Dos, Don´ts and Conventions.mp417.06MB
231. 31. Appendix 1 Python (& Finance) Basics/12. The print() Function.mp417.42MB
232. 31. Appendix 1 Python (& Finance) Basics/13. Coding Exercise 1.mp446.77MB
233. 31. Appendix 1 Python (& Finance) Basics/14. TVM Problems with many Cashflows.mp410.47MB
234. 31. Appendix 1 Python (& Finance) Basics/15. Intro to Python Lists.mp47.77MB
235. 31. Appendix 1 Python (& Finance) Basics/16. Zero-based Indexing and negative Indexing in Python (Theory).mp47.44MB
236. 31. Appendix 1 Python (& Finance) Basics/17. Indexing Lists.mp413.87MB
237. 31. Appendix 1 Python (& Finance) Basics/18. For Loops - Iterating over Lists.mp429.91MB
238. 31. Appendix 1 Python (& Finance) Basics/19. The range Object - another Iterable.mp417.08MB
239. 31. Appendix 1 Python (& Finance) Basics/2. Intro to the Time Value of Money (TVM) Concept (Theory).mp416.49MB
240. 31. Appendix 1 Python (& Finance) Basics/20. Calculate FV and PV for many Cashflows.mp433.52MB
241. 31. Appendix 1 Python (& Finance) Basics/21. The Net Present Value - NPV (Theory).mp433.29MB
242. 31. Appendix 1 Python (& Finance) Basics/22. Calculate an Investment Project´s NPV.mp414.34MB
243. 31. Appendix 1 Python (& Finance) Basics/23. Coding Exercise 2.mp437.98MB
244. 31. Appendix 1 Python (& Finance) Basics/24. Data Types in Action.mp424.33MB
245. 31. Appendix 1 Python (& Finance) Basics/25. The Data Type Hierarchy (Theory).mp410.78MB
246. 31. Appendix 1 Python (& Finance) Basics/26. Excursus Dynamic Typing in Python.mp45.2MB
247. 31. Appendix 1 Python (& Finance) Basics/27. Build-in Functions.mp425.39MB
248. 31. Appendix 1 Python (& Finance) Basics/28. Integers.mp410.97MB
249. 31. Appendix 1 Python (& Finance) Basics/29. Floats.mp424.33MB
250. 31. Appendix 1 Python (& Finance) Basics/3. Calculate Future Values (FV) with Python Compounding.mp412.76MB
251. 31. Appendix 1 Python (& Finance) Basics/30. How to round Floats (and Integers) with round().mp420.91MB
252. 31. Appendix 1 Python (& Finance) Basics/31. More on Lists.mp424.59MB
253. 31. Appendix 1 Python (& Finance) Basics/32. Lists and Element-wise Operations.mp417.58MB
254. 31. Appendix 1 Python (& Finance) Basics/33. Slicing Lists.mp420.13MB
255. 31. Appendix 1 Python (& Finance) Basics/35. Changing Elements in Lists.mp410.12MB
256. 31. Appendix 1 Python (& Finance) Basics/36. Sorting and Reversing Lists.mp413.19MB
257. 31. Appendix 1 Python (& Finance) Basics/37. Adding and removing Elements fromto Lists.mp438.54MB
258. 31. Appendix 1 Python (& Finance) Basics/38. Mutable vs. immutable Objects (Part 1).mp434.5MB
259. 31. Appendix 1 Python (& Finance) Basics/39. Mutable vs. immutable Objects (Part 2).mp421.86MB
260. 31. Appendix 1 Python (& Finance) Basics/4. Calculate Present Values (FV) with Python Discounting.mp410.06MB
261. 31. Appendix 1 Python (& Finance) Basics/40. Coding Exercise 3.mp453.8MB
262. 31. Appendix 1 Python (& Finance) Basics/41. Tuples.mp429.79MB
263. 31. Appendix 1 Python (& Finance) Basics/42. Dictionaries.mp431.03MB
264. 31. Appendix 1 Python (& Finance) Basics/43. Intro to Strings.mp440.83MB
265. 31. Appendix 1 Python (& Finance) Basics/44. String Replacement.mp417.31MB
266. 31. Appendix 1 Python (& Finance) Basics/45. Booleans.mp48.89MB
267. 31. Appendix 1 Python (& Finance) Basics/46. Operators (Theory).mp411.7MB
268. 31. Appendix 1 Python (& Finance) Basics/47. Comparison, Logical and Membership Operators in Action.mp435.53MB
269. 31. Appendix 1 Python (& Finance) Basics/48. Coding Exercise 4.mp442.3MB
270. 31. Appendix 1 Python (& Finance) Basics/49. Conditional Statements.mp438.63MB
271. 31. Appendix 1 Python (& Finance) Basics/5. Interest Rates and Returns (Theory).mp414.19MB
272. 31. Appendix 1 Python (& Finance) Basics/50. Keywords pass, continue and break.mp439.39MB
273. 31. Appendix 1 Python (& Finance) Basics/51. Calculate a Project´s Payback Period.mp421.87MB
274. 31. Appendix 1 Python (& Finance) Basics/52. Introduction to while loops.mp435.65MB
275. 31. Appendix 1 Python (& Finance) Basics/6. Calculate Interest Rates and Returns with Python.mp419.26MB
276. 31. Appendix 1 Python (& Finance) Basics/7. Introduction to Variables.mp418.13MB
277. 31. Appendix 1 Python (& Finance) Basics/8. Excursus How to add inline comments.mp411.25MB
278. 31. Appendix 1 Python (& Finance) Basics/9. Variables and Memory (Theory).mp45.47MB
279. 32. Appendix 2 User-defined Functions (required for OOP)/2. Defining your first user-defined Function.mp427.36MB
280. 32. Appendix 2 User-defined Functions (required for OOP)/3. What´s the difference between Positional Arguments vs. Keyword Arguments.mp436.34MB
281. 32. Appendix 2 User-defined Functions (required for OOP)/4. How to work with Default Arguments.mp428.48MB
282. 32. Appendix 2 User-defined Functions (required for OOP)/5. The Default Argument None.mp426.79MB
283. 32. Appendix 2 User-defined Functions (required for OOP)/6. How to unpack Iterables.mp418.62MB
284. 32. Appendix 2 User-defined Functions (required for OOP)/7. Sequences as arguments and args.mp426.28MB
285. 32. Appendix 2 User-defined Functions (required for OOP)/8. How to return many results.mp413.44MB
286. 32. Appendix 2 User-defined Functions (required for OOP)/9. Scope - easily explained.mp435.26MB
287. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/10. Boolean Arrays and Conditional Filtering.mp418.14MB
288. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/11. Advanced Filtering & Bitwise Operators.mp428.18MB
289. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/12. Determining a Project´s Payback Period with np.where().mp422.54MB
290. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/13. Creating Numpy Arrays from Scratch.mp437.87MB
291. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/15. How to work with nested Lists.mp418.24MB
292. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/16. 2-dimensional Numpy Arrays.mp416.13MB
293. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/17. How to slice 2-dim Numpy Arrays (Part 1).mp428.93MB
294. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/18. How to slice 2-dim Numpy Arrays (Part 2).mp48.75MB
295. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/19. Recap Changing Elements in a Numpy Array slice.mp416.51MB
296. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/2. Modules, Packages and Libraries - No need to reinvent the Wheel.mp432.02MB
297. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/20. How to perform row-wise and column-wise Operations.mp422.47MB
298. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/22. Intro to Tabular Data Pandas.mp418.08MB
299. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/23. Create your very first Pandas DataFrame (from csv).mp462.52MB
300. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/24. Pandas Display Options and the methods head() & tail().mp440.48MB
301. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/25. First Data Inspection.mp456.02MB
302. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/27. Selecting Columns.mp426.63MB
303. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/28. Selecting one Column with the dot notation.mp48.55MB
304. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/29. Zero-based Indexing and Negative Indexing.mp410.18MB
305. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/3. Numpy Arrays.mp435.7MB
306. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/30. Selecting Rows with iloc (position-based indexing).mp465.01MB
307. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/31. Slicing Rows and Columns with iloc (position-based indexing).mp424.28MB
308. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/33. Selecting Rows with loc (label-based indexing).mp421.32MB
309. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/34. Slicing Rows and Columns with loc (label-based indexing).mp477.57MB
310. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/36. Summary, Best Practices and Outlook.mp442.02MB
311. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/38. First Steps with Pandas Series.mp418.99MB
312. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/39. Analyzing Numerical Series with unique(), nunique() and value_counts().mp467.14MB
313. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/4. Indexing and Slicing Numpy Arrays.mp413.67MB
314. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/40. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp436.17MB
315. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/41. The copy() method.mp420.78MB
316. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/42. Sorting of Series and Introduction to the inplace - parameter.mp433.42MB
317. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/43. First Steps with Pandas Index Objects.mp437.14MB
318. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/44. Changing Row Index with set_index() and reset_index().mp463.07MB
319. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/45. Changing Column Labels.mp417.97MB
320. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/46. Renaming Index & Column Labels with rename().mp427.99MB
321. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/47. Filtering DataFrames (one Condition).mp444.85MB
322. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/48. Filtering DataFrames by many Conditions (AND).mp421.23MB
323. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/49. Filtering DataFrames by many Conditions (OR).mp425.79MB
324. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/5. Vectorized Operations with Numpy Arrays.mp418.73MB
325. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/50. Advanced Filtering with between(), isin() and ~.mp454.43MB
326. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/51. Intro to NA Values missing Values.mp438.16MB
327. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/52. Handling NA Values missing Values.mp456.25MB
328. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/53. Exporting DataFrames to csv.mp410.59MB
329. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/54. Summary Statistics and Accumulations.mp446.93MB
330. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/55. Visualization with Matplotlib (Intro).mp459.12MB
331. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/56. Customization of Plots.mp484.12MB
332. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/57. Histogramms (Part 1).mp420.46MB
333. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/58. Histogramms (Part 2).mp428.85MB
334. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/59. Scatterplots.mp429.46MB
335. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/6. Changing Elements in Numpy Arrays & Mutability.mp424.52MB
336. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/60. First Steps with Seaborn.mp418.25MB
337. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/61. Categorical Seaborn Plots.mp470.72MB
338. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/62. Seaborn Regression Plots.mp466.52MB
339. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/63. Seaborn Heatmaps.mp435.71MB
340. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/64. Removing Columns.mp429.62MB
341. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/65. Introduction to GroupBy Operations.mp48.09MB
342. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/66. Understanding the GroupBy Object.mp439.43MB
343. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/67. Splitting with many Keys.mp442.24MB
344. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/68. split-apply-combine.mp440.1MB
345. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/7. View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp419.26MB
346. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/8. Numpy Array Methods and Attributes.mp421.98MB
347. 33. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/9. Numpy Universal Functions.mp417.77MB
348. 4. FOREX Day Trading with FXCM/1. FXCM at a first glance.mp467.52MB
349. 4. FOREX Day Trading with FXCM/2. How to create an Account.mp453.89MB
350. 4. FOREX Day Trading with FXCM/3. Example Trade Buying EURUSD.mp424.42MB
351. 4. FOREX Day Trading with FXCM/4. Trade Analysis.mp418.81MB
352. 4. FOREX Day Trading with FXCM/5. Charting.mp413.7MB
353. 4. FOREX Day Trading with FXCM/6. Closing Positions vs. Hedging Positions.mp418.49MB
354. 4. FOREX Day Trading with FXCM/7. Order Types at a glance.mp427.53MB
355. 5. Installing Python and Jupyter Notebooks/1. Introduction.mp48.91MB
356. 5. Installing Python and Jupyter Notebooks/2. Download and Install Anaconda.mp460.88MB
357. 5. Installing Python and Jupyter Notebooks/3. How to open Jupyter Notebooks.mp450.92MB
358. 5. Installing Python and Jupyter Notebooks/4. How to work with Jupyter Notebooks.mp453.46MB
359. 5. Installing Python and Jupyter Notebooks/5. Tips for Python Beginners.mp46.2MB
360. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/1. Introduction.mp417.15MB
361. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/10. Getting help on StackOverflow.com.mp439.52MB
362. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/11. How to traceback more complex Errors.mp496.84MB
363. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/12. Problems with the Python Installation.mp434MB
364. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/13. External Factors and Issues.mp417.43MB
365. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/14. Errors related to the course content (Transcription Errors).mp416.4MB
366. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/15. Summary and Debugging Flow-Chart.mp426.36MB
367. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/2. Test your debugging skills!.mp458.59MB
368. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/3. Major reasons for Coding Errors.mp45.39MB
369. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/4. The most commonly made Errors at a glance.mp435.49MB
370. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/5. Omitting cells, changing the sequence and more.mp450.01MB
371. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/6. IndexErrors.mp431.09MB
372. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/7. Indentation Errors.mp412.21MB
373. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/8. Misuse of function names and keywords.mp412.37MB
374. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/9. TypeErrors and ValueErrors.mp416.75MB
375. 7. Trading with Python and OANDAFXCM - an Introduction/10. OANDA How to place Orders and execute Trades.mp485.46MB
376. 7. Trading with Python and OANDAFXCM - an Introduction/13. FXCM How to install the FXCM API Wrapper.mp432.54MB
377. 7. Trading with Python and OANDAFXCM - an Introduction/14. FXCM Getting the Access Token & other Preparations.mp421.07MB
378. 7. Trading with Python and OANDAFXCM - an Introduction/15. FXCM Connecting to the APIServer.mp442.81MB
379. 7. Trading with Python and OANDAFXCM - an Introduction/17. FXCM How to load Historical Price Data (Part 1).mp451.78MB
380. 7. Trading with Python and OANDAFXCM - an Introduction/18. FXCM How to load Historical Price Data (Part 2).mp443.26MB
381. 7. Trading with Python and OANDAFXCM - an Introduction/19. FXCM Streaming high-frequency real-time Data.mp447.68MB
382. 7. Trading with Python and OANDAFXCM - an Introduction/2. Overview.mp44.52MB
383. 7. Trading with Python and OANDAFXCM - an Introduction/20. FXCM How to place Orders and execute Trades.mp445.97MB
384. 7. Trading with Python and OANDAFXCM - an Introduction/4. OANDA How to install the OANDA API Wrapper.mp428.38MB
385. 7. Trading with Python and OANDAFXCM - an Introduction/5. OANDA Getting the API Key & other Preparations.mp431.49MB
386. 7. Trading with Python and OANDAFXCM - an Introduction/6. OANDA Connecting to the APIServer.mp448.32MB
387. 7. Trading with Python and OANDAFXCM - an Introduction/7. OANDA How to load Historical Price Data (Part 1).mp457.36MB
388. 7. Trading with Python and OANDAFXCM - an Introduction/8. OANDA How to load Historical Price Data (Part 2).mp433.46MB
389. 7. Trading with Python and OANDAFXCM - an Introduction/9. OANDA Streaming high-frequency real-time Data.mp425.8MB
390. 8. Conclusion and Outlook/1. Conclusion and Outlook.mp43.95MB
391. 9. +++ PART 2 Pandas for Financial Data Analysis and Introduction to OOP +++/1. Introduction and Downloads Part 2.mp417.93MB