Python for Finance and Algorithmic Trading with QuantConnect
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Welcome to the ultimate online course to go from zero to hero in Python for Finance, including Algorithmic Trading with LEAN Engine!
This course will guide you through everything you need to know to use Python for Finance and conducting Algorithmic Trading on the QuantConnect platform with the powerful LEAN engine!
This course is specifically design to connect core financial concepts to clear Python code. You will learn about in-demand real world skills that are highly sought after in the fintech ecosystem.
We’ll cover the following topics used by financial professionals:
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Python Crash Course Fundamentals
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NumPy for High Speed Numerical Processing
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Pandas for Efficient Data Analysis
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Matplotlib for Data Visualization
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Stock Returns Analysis
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Cumulative Daily Returns
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Volatility and Securities Risk
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EWMA (Exponentially Weighted Moving Average)
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Sharpe Ratio
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Portfolio Allocation Optimization
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Efficient Frontier and Markowitz Optimization
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Types of Funds
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Order Books
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Short Selling
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Capital Asset Pricing Model
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Stock Splits and Dividends
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Efficient Market Hypothesis
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Algorithmic Trading with QuantConnect
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Futures Trading
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Options Trading
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and much more!
Why choose this specific course to learn Python, Finance, and Algorithmic Trading?
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This course starts by teaching you some of the most important and popular libraries in Python for Data Analysis and Visualization, includign NumPy, Pandas, and Matplotlib.
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Each lecture includes a high quality HD video with clear instructions and relevant theory slides as well as a full Jupyter Notebook with explanatory code and text.
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This course has complete coverage allowing you to actually implement your ideas as algorithms, other courses online never actually show you how to trade with your new knowledge!
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Powerful online community with our QA Forums with thousands of students and dedicated Teaching Assistants, as well as student interaction on our Discord Server.
All of this comes with a 30-day money back guarantee, so you can try out the course absolutely risk free!
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18Introduction to Core Pandas TopicsVídeo Aula
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19Pandas Series - Part OneVídeo Aula
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20Pandas Series - Part TwoVídeo Aula
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21Pandas DataFrames - Part One - Creating a DataFrameVídeo Aula
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22Pandas DataFrames - Part Two - Basic PropertiesVídeo Aula
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23Pandas DataFrames - Part Three - Working with ColumnsVídeo Aula
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24Pandas DataFrames - Part Four - Working with RowsVídeo Aula
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25Pandas - Conditional FilteringVídeo Aula
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26Pandas - Useful Methods - Apply on Single ColumnVídeo Aula
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27Pandas - Useful Methods - Apply on Multiple ColumnsVídeo Aula
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28Pandas - Useful Methods - Statistical InformationVídeo Aula
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29Pandas - Combining DataFrames - ConcatenationVídeo Aula
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30Pandas - Combining DataFrames - Inner MergeVídeo Aula
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31Pandas - Combining DataFrames - Left and Right MergeVídeo Aula
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32Pandas - Combining DataFrames - Outer MergeVídeo Aula
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33Pandas IO -CSV FilesVídeo Aula
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34Pandas IO - HTMLVídeo Aula
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35Pandas IO - Excel FilesVídeo Aula
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36Pandas IO - SQLVídeo Aula
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37Pandas Exercise ProjectVídeo Aula
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38Pandas Exercise Project SolutionsVídeo Aula
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39Introduction to MatplotlibVídeo Aula
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40Matplotlib BasicsVídeo Aula
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41Matplotlib - Understanding the Figure ObjectVídeo Aula
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42Matplotlib - Implementing Figures and AxesVídeo Aula
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43Matplotlib - Figure ParametersVídeo Aula
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44Matplotlib - Subplots FunctionalityVídeo Aula
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45Matplotlib Styling - LegendsVídeo Aula
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46Matplotlib Styling - Colors and StylesVídeo Aula
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47Advanced Matplotlib Commands (Optional)Vídeo Aula
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48Matplotlib Exercise Questions - OverviewVídeo Aula
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49Matplotlib Exercise Questions - SolutionsVídeo Aula
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50Introduction to Pandas and FinanceVídeo Aula
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51Core Pandas Time MethodsVídeo Aula
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52Pandas VisualizationsVídeo Aula
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53Visualizing Time Series Data with Pandas - Part OneVídeo Aula
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54Visualizing Time Series Data with Pandas - Part Two (Optional)Vídeo Aula
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55Pandas Rolling StatisticsVídeo Aula
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56Pandas Time Shifting and Row CalculationsVídeo Aula
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57Python API Based Data SourcesVídeo Aula
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58Alternative Data Sources and PlatformsVídeo Aula
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59Pandas and Finance - Exercise OverviewVídeo Aula
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60Pandas and Finance - Exercise SolutionsVídeo Aula
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61Introduction to Financial Concepts with PythonVídeo Aula
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62Efficient Market HypothesisVídeo Aula
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63Measurements of ReturnVídeo Aula
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64Measurements of RiskVídeo Aula
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65Sharpe Ratio - Theory and IntuitionVídeo Aula
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66Sharpe Ratio with PythonVídeo Aula
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67Sortino Ratio - Theory and IntuitionVídeo Aula
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68Sortino Ratio with PythonVídeo Aula
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69Probabilistic Sharpe Ratio - Theory and IntuitionVídeo Aula
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70Probabilistic Sharpe Ratio with PythonVídeo Aula
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71Modern Portfolio TheoryVídeo Aula
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72Equal Weighted Portfolio in PythonVídeo Aula
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73Log Returns - Theory and IntuitionVídeo Aula
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74Monte Carlo Simulation with PythonVídeo Aula
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75Minimization Search with SciPyVídeo Aula
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76Efficient Frontier in PythonVídeo Aula
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77Capital Asset Pricing ModelVídeo Aula
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78CAPM with Python - Part One - Exploring Data and MarketVídeo Aula
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79CAPM with Python - Part Two - Beta and AlphaVídeo Aula
