In this course, I learnt many useful package in python that frquently used in quantitative finance field, including:

1.NumPy for High Speed Numerical Processing

2.Pandas for Efficient Data Analysis

3.Matplotlib for Data Visualization

4.Using pandas-datareader and Quandl for data ingestion

Also this course covers many classic financial analytic methods:

1.Pandas Time Series Analysis Techniques

2.Stock Returns Analysis

3.Cumulative Daily Returns

4.Volatility and Securities Risk

5.EWMA (Exponentially Weighted Moving Average)

6.Statsmodels

7.ETS (Error-Trend-Seasonality)

8.ARIMA (Auto-regressive Integrated Moving Averages)

9.Auto Correlation Plots and Partial Auto Correlation Plots

10.Sharpe Ratio

11.Portfolio Allocation Optimization

12.Efficient Frontier and Markowitz Optimization

13.Capital Asset Pricing Model

14.Stock Splits and Dividends

15.Efficient Market Hypothesis

And finally, it teaches how to implement the above algorithms and fit them into Quantopian.