Python for Finance: Investment Fundamentals & Data Analytics
About this course
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course provides a solid foundation in using Python for financial analysis and investment decision-making. You'll learn to apply Python programming and data analysis tools to solve financial problems, from basic calculations to advanced portfolio optimization. The course starts with Python programming basics, including the installation of Jupyter and Anaconda, and progresses to key financial concepts such as calculating rates of return, measuring investment risk, and handling time-series data. As you advance, you’ll gain hands-on experience using Python libraries tailored for financial modeling and analysis. Topics like the Capital Asset Pricing Model (CAPM), Markowitz Portfolio Theory, and Monte Carlo simulations will help you optimize portfolios and evaluate risk. By the end, you’ll be equipped to analyze financial data, perform regression analysis, and apply Python to real-world investment challenges. This course is perfect for finance enthusiasts and those looking to merge finance with programming and data analysis. Basic finance knowledge is helpful, but no prior Python experience is required.
75/100
CourseAsk score
- What the provider tells you
- 39/45
- Who stands behind it
- 20/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- Install and use Jupyter and Anaconda for Python programming
- Calculate rates of return and measure investment risk using Python
- Work with financial time-series data
- Apply the Capital Asset Pricing Model (CAPM) to evaluate investments
- Optimize portfolios using Markowitz Portfolio Theory
- Run Monte Carlo simulations for financial modeling
- Perform regression analysis on financial data
- Use Python libraries designed for financial analysis
Course objectives
- Provide a foundation in Python programming for finance professionals
- Teach application of data analysis tools to financial problems
- Enable students to optimize portfolios and evaluate investment risk
- Prepare learners to analyze financial data and solve real-world investment challenges
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