Course Overview: https://youtu.be/JgFV5qzAYno Python is now becoming the number 1 programming language for data science. Due to python鈥檚 simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data. By the end of the course, you can achieve the following using python: - Import, pre-process, save and visualize financial data into pandas Dataframe - Manipulate the existing financial data by generating new variables using multiple columns - Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts - Build a trading model using multiple linear regression model - Evaluate the performance of the trading model using different investment indicators Jupyter Notebook environment is configured in the course platform for practicing python coding without installing any client applications.
4.0 Introduction
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Skills You'll Learn
Financial Analysis, Data Manipulation, Regression Analysis, Probability & Statistics, Financial Modeling, Risk Analysis, Financial Trading, Financial Data, Jupyter, Pandas (Python Package), Statistical Inference, Data Visualization, Statistical Analysis, Statistical Methods, Python Programming
Reviews
4.4 (4,482 ratings)
- 5 stars59.10%
- 4 stars29.29%
- 3 stars7.85%
- 2 stars1.89%
- 1 star1.85%
YZ
Feb 2, 2025
This is an excellent explanation for applying Python to stock market data. As stated by the author, many terms are not explained in detail. I searched them in AI and gained an understanding.
GZ
Mar 26, 2020
Very clear explaining of the significant aspects when structuring a financial analysis, applicable in many forms of data if you don't want to make predictions only for the stock market.
Taught By
Xuhu Wan
Associate Professor