Python for Finance: Investment Fundamentals & Data Analytics
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Python for Finance: Investment Fundamentals & Data Analytics
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What you'll learn
Master the Python programming language and its application to financial data analysis.
Learn to calculate rates of return and measure investment risks using Python.
Apply Markowitz Portfolio Theory and the Capital Asset Pricing Model in portfolio optimization.
Understand and implement Monte Carlo simulations for financial forecasting and decision-making.
Skills you'll gain
- Investment Management
- General Finance
- Portfolio Risk
- Financial Data
- Return On Investment
- Financial Modeling
- Regression Analysis
- Risk Modeling
- Statistical Analysis
- Financial Forecasting
- Simulations
- Portfolio Management
- Risk Analysis
- Investments
- Correlation Analysis
- Simulation and Simulation Software
- Time Series Analysis and Forecasting
- Object Oriented Programming (OOP)
Tools you'll learn
Details to know
See how employees at top companies are mastering in-demand skills
There are 17 modules in 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.
In this module, we will introduce the course, outlining the main objectives and topics that will be covered. We’ll also introduce the instructors and explain who this course is designed for, providing a comprehensive overview of what to expect throughout the lessons.
What's included
1 video1 reading
1 video•Total 4 minutes
- What Does the Course Cover?•4 minutes
1 reading•Total 10 minutes
- Full Course Resources•10 minutes
In this module, we will break down the fundamentals of programming, focusing on Python's suitability for finance. You'll also learn about Jupyter Notebooks and how to install and set them up for an optimal coding experience. This section will equip you with the tools to begin your programming journey.
What's included
7 videos1 assignment
7 videos•Total 29 minutes
- Programming Explained in 5 Minutes•5 minutes
- Why Python•5 minutes
- Why Jupyter•3 minutes
- Installing Python and Jupyter•4 minutes
- Jupyter's Interface - the Dashboard•3 minutes
- Jupyter's Interface - Prerequisites for Coding•6 minutes
- Python 2 vs Python 3: What's the Difference?•3 minutes
1 assignment•Total 15 minutes
- Introduction to Jupyter and Programming with Python - Assessment•15 minutes
In this module, we will introduce you to Python variables and data types. You will learn how to work with different types of data, such as numbers and strings, and understand the role they play in programming. This foundation will help you handle more complex data operations as you progress.
What's included
5 videos1 assignment
5 videos•Total 20 minutes
- Python Variables•5 minutes
- Understanding Numbers and Boolean Values•3 minutes
- Strings•6 minutes
- Introduction to Anaconda AI•2 minutes
- Using the Anaconda Assistant: Strings•4 minutes
1 assignment•Total 15 minutes
- Python Variables and Data Types - Assessment•15 minutes
In this module, we will cover Python’s essential syntax elements, including operators, commenting, and the importance of indentation. You’ll learn techniques to enhance code readability and functionality, preparing you for more complex coding challenges.
What's included
7 videos1 assignment
7 videos•Total 11 minutes
- The Arithmetic Operators of Python•3 minutes
- What is the Double Equality Sign•2 minutes
- How to Reassign Values•1 minute
- How to Add Comments•2 minutes
- Understanding Line Continuation•1 minute
- How to Index Elements•1 minute
- How to Structure Your Code with Indentation•2 minutes
1 assignment•Total 15 minutes
- Basic Python Syntax - Assessment•15 minutes
In this module, we will dive deeper into Python operators, focusing on comparison, logical, and identity operators. You will enhance your ability to create expressions that drive decision-making in your code.
What's included
2 videos1 assignment
2 videos•Total 8 minutes
- Python Comparison Operators•2 minutes
- Python's Logical and Identity Operators•6 minutes
1 assignment•Total 15 minutes
- More on Python Operators - Assessment•15 minutes
In this module, we will explore conditional statements, such as IF, ELSE, and ELIF. You’ll learn how to build logic-driven code that can handle different scenarios and outcomes based on conditions.
What's included
4 videos1 assignment
4 videos•Total 14 minutes
- Getting to Know the IF Statement•3 minutes
- Adding an ELSE statement•3 minutes
- Else if, for Brief - ELIF•6 minutes
- An Additional Explanation of Boolean Values•2 minutes
1 assignment•Total 15 minutes
- Conditional Statements - Assessment•15 minutes
In this module, we will focus on Python functions—how to define them, use parameters, and combine them with other tools. You’ll also explore some of Python’s built-in functions to streamline your programming.
What's included
7 videos1 assignment
7 videos•Total 19 minutes
- How to Define a Function in Python•2 minutes
- How to Create a Function with a Parameter•4 minutes
- Another Way to Define a Function•3 minutes
- How to Use a Function within a Function•2 minutes
- Use Conditional Statements and Functions Together•3 minutes
- How to Create Functions that Contain a Few Arguments•1 minute
- Built-In Functions in Python Worth Knowing•4 minutes
1 assignment•Total 15 minutes
- Python Functions - Assessment•15 minutes
In this module, we will cover Python’s sequence types, including lists, tuples, and dictionaries. You’ll learn how to store, slice, and manage data effectively within these structures.
What's included
5 videos1 assignment
5 videos•Total 19 minutes
- Introduction to Lists•4 minutes
- Using Methods in Python•3 minutes
- What is List Slicing•5 minutes
- Working with Tuples•3 minutes
- Python Dictionaries•4 minutes
1 assignment•Total 15 minutes
- Python Sequences - Assessment•15 minutes
In this module, we will explore how to use iterations to process and analyze data in Python. You’ll learn how to work with loops and conditionals together to automate tasks, enhancing the functionality of your code.
What's included
8 videos1 assignment
8 videos•Total 26 minutes
- Using For Loops•3 minutes
- Using While Loops and Incrementing•2 minutes
- Use the range() Function to Create Lists•4 minutes
- Combine Conditional Statements and Loops•3 minutes
- All In - Conditional Statements, Functions, and Loops•2 minutes
- Using the Anaconda Assistant: Several Python Tools•6 minutes
- How to Iterate over Dictionaries•3 minutes
- Using the Anaconda Assistant: Dictionaries•2 minutes
1 assignment•Total 15 minutes
- Using Iterations in Python - Assessment•15 minutes
In this module, we will delve into more advanced Python concepts, such as object-oriented programming and using external libraries. You’ll also learn which Python packages are essential for data analysis and finance, helping you work more efficiently.
What's included
15 videos1 assignment
15 videos•Total 65 minutes
- Object Oriented Programming•5 minutes
- Modules, Packages, and the Standard Library•4 minutes
- Importing Modules•4 minutes
- Must-have packages for Finance and Data Science•5 minutes
- Working with arrays•6 minutes
- Generating Random Numbers•3 minutes
- A Note on Using Financial Data in Python•3 minutes
- Sources of Financial Data•7 minutes
- Accessing the Notebook Files•3 minutes
- Importing and Organizing Data in Python – Part I•4 minutes
- Importing and Organizing Data in Python – Part II.A•7 minutes
- Importing and Organizing Data in Python – Part II.B•5 minutes
- Importing and Organizing Data in Python – Part III•4 minutes
- Changing the Index of Your Time-Series Data•3 minutes
- Restarting the Jupyter Kernel•2 minutes
1 assignment•Total 15 minutes
- Advanced Python Tools - Assessment•15 minutes
In this module, we will explore the foundational concepts of calculating and comparing rates of return. You’ll learn how to apply these concepts in Python to compute the returns of individual securities, portfolios, and stock indices, providing key insights into risk and performance.
What's included
10 videos1 assignment
10 videos•Total 43 minutes
- Considering Both Risk and Return•2 minutes
- What are We Going to See Next?•3 minutes
- Calculating a Security's Rate of Return•6 minutes
- Simple Returns Part I•5 minutes
- Simple Returns Part II•3 minutes
- Log Returns•4 minutes
- Portfolio of Securities and Calculating Rate of Return•3 minutes
- Calculating the Rate of Return of a Portfolio of Securities•9 minutes
- Popular Stock Indices•4 minutes
- Calculating the Return of Indices•5 minutes
1 assignment•Total 15 minutes
- PART II FINANCE - Calculating and Comparing Rates of Return in Python - Assessment•15 minutes
In this module, we will dive into risk measurement in finance. You’ll learn how to quantify the risk of securities and portfolios, calculate covariance and correlation, and use Python tools to analyze the risks associated with investment decisions.
What's included
10 videos1 assignment
10 videos•Total 41 minutes
- How Do We Measure a Security's Risk?•6 minutes
- Calculating a Security's Risk in Python•6 minutes
- The Benefits of Portfolio Diversification•3 minutes
- Calculating the Covariance between Securities•4 minutes
- Measuring the Correlation between Securities•4 minutes
- Calculating Covariance and Correlation•5 minutes
- Considering the Risk of Multiple Securities•3 minutes
- Calculating Portfolio Risk•3 minutes
- Understanding Systematic Versus Idiosyncratic Risk•3 minutes
- Calculating Diversifiable and NonDiversifiable Risk•4 minutes
1 assignment•Total 15 minutes
- PART II Finance - Measuring Investment Risk - Assessment•15 minutes
In this module, we will cover regression analysis and its application in finance. You will learn how to run regressions in Python, interpret the results, and use key indicators such as Alpha and Beta to assess financial performance.
What's included
4 videos1 assignment
4 videos•Total 22 minutes
- Simple Regression Analysis•4 minutes
- Running a Regression in Python•7 minutes
- How to Distinguish Good Regressions•5 minutes
- Computing Alpha, Beta, and R2 in Python•6 minutes
1 assignment•Total 15 minutes
- PART II Finance - Using Regressions for Financial Analysis - Assessment•15 minutes
In this module, we will introduce Markowitz Portfolio Optimization, focusing on building efficient portfolios. You’ll learn to calculate the efficient frontier in Python and optimize asset allocation to achieve the best balance between risk and return.
What's included
4 videos1 assignment
4 videos•Total 20 minutes
- Markowitz Portfolio Theory•7 minutes
- Obtaining the Efficient Frontier Part I•6 minutes
- Obtaining the Efficient Frontier Part II•5 minutes
- Obtaining the Efficient Frontier Part III•2 minutes
1 assignment•Total 15 minutes
- PART II Finance - Markowitz Portfolio Optimization - Assessment•15 minutes
In this module, we will examine the Capital Asset Pricing Model (CAPM), its calculation, and its significance in finance. You’ll use Python to calculate Beta, expected returns, and performance metrics like the Sharpe Ratio and Alpha to evaluate investments.
What's included
8 videos1 assignment
8 videos•Total 27 minutes
- The Intuition Behind the CAPM•5 minutes
- Understanding and Calculating Beta•4 minutes
- Calculating the Beta of a Stock•4 minutes
- The CAPM Formula•4 minutes
- Calculating the Expected Return of a Stock•2 minutes
- Introducing the Sharpe Ratio•2 minutes
- Obtaining the Sharpe Ratio in Python•1 minute
- Measuring Alpha•4 minutes
1 assignment•Total 15 minutes
- PART II Finance - The Capital Asset Pricing Model - Assessment•15 minutes
In this module, we will focus on multivariate regression analysis, applying it in the context of finance. You’ll learn to run multivariate regressions in Python and analyze the relationships between multiple variables affecting asset performance.
What's included
2 videos1 assignment
2 videos•Total 12 minutes
- Multivariate Regression Analysis•6 minutes
- Running a Multivariate Regression in Python•6 minutes
1 assignment•Total 15 minutes
- PART II Finance - Multivariate Regression Analysis - Assessment•15 minutes
In this module, we will delve into Monte Carlo simulations and their powerful applications in finance. You’ll use Python to simulate future profits, forecast stock prices, and apply the Black Scholes formula, enhancing your ability to make informed investment decisions.
What's included
13 videos3 assignments
13 videos•Total 57 minutes
- The Essence of Monte Carlo Simulations•3 minutes
- Monte Carlo in Corporate Finance•3 minutes
- MC Predicting Gross Profit Part I•6 minutes
- MC Predicting Gross Profit Part II•3 minutes
- Forecasting Stock Prices with an MC Simulation•4 minutes
- MC Forecasting Stock Prices Part I•4 minutes
- MC Forecasting Stock Prices Part II•5 minutes
- MC Forecasting Stock Prices Part III•4 minutes
- An Introduction to Derivative Contracts•7 minutes
- The Black Scholes Formula•5 minutes
- MC Black Scholes Merton Updated•6 minutes
- MC Euler Discretization Part I•6 minutes
- MC Euler Discretization Part II•2 minutes
3 assignments•Total 90 minutes
- PART II Finance - Monte Carlo Simulations as a Decision-Making Tool - Assessment•15 minutes
- Full Course Assessment•60 minutes
- Full Course Practice Assessment•15 minutes
Instructor
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Reviewed on Nov 13, 2025
the course files or support files like csv were not provided, which the intructer keeps reffering to.
Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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