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⇱ Python for Finance: Investment Fundamentals & Data Analytics | Coursera


Python for Finance: Investment Fundamentals & Data Analytics

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Python for Finance: Investment Fundamentals & Data Analytics

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Gain insight into a topic and learn the fundamentals.
4.5

12 reviews

Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
4.5

12 reviews

Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

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.

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Assessments

18 assignments

Taught in English

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 videoTotal 4 minutes
  • What Does the Course Cover?4 minutes
1 readingTotal 10 minutes
  • Full Course Resources10 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 videosTotal 29 minutes
  • Programming Explained in 5 Minutes5 minutes
  • Why Python5 minutes
  • Why Jupyter3 minutes
  • Installing Python and Jupyter4 minutes
  • Jupyter's Interface - the Dashboard3 minutes
  • Jupyter's Interface - Prerequisites for Coding6 minutes
  • Python 2 vs Python 3: What's the Difference?3 minutes
1 assignmentTotal 15 minutes
  • Introduction to Jupyter and Programming with Python - Assessment15 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 videosTotal 20 minutes
  • Python Variables5 minutes
  • Understanding Numbers and Boolean Values3 minutes
  • Strings6 minutes
  • Introduction to Anaconda AI2 minutes
  • Using the Anaconda Assistant: Strings4 minutes
1 assignmentTotal 15 minutes
  • Python Variables and Data Types - Assessment15 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 videosTotal 11 minutes
  • The Arithmetic Operators of Python3 minutes
  • What is the Double Equality Sign2 minutes
  • How to Reassign Values1 minute
  • How to Add Comments2 minutes
  • Understanding Line Continuation1 minute
  • How to Index Elements1 minute
  • How to Structure Your Code with Indentation2 minutes
1 assignmentTotal 15 minutes
  • Basic Python Syntax - Assessment15 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 videosTotal 8 minutes
  • Python Comparison Operators2 minutes
  • Python's Logical and Identity Operators6 minutes
1 assignmentTotal 15 minutes
  • More on Python Operators - Assessment15 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 videosTotal 14 minutes
  • Getting to Know the IF Statement3 minutes
  • Adding an ELSE statement3 minutes
  • Else if, for Brief - ELIF6 minutes
  • An Additional Explanation of Boolean Values2 minutes
1 assignmentTotal 15 minutes
  • Conditional Statements - Assessment15 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 videosTotal 19 minutes
  • How to Define a Function in Python2 minutes
  • How to Create a Function with a Parameter4 minutes
  • Another Way to Define a Function3 minutes
  • How to Use a Function within a Function2 minutes
  • Use Conditional Statements and Functions Together3 minutes
  • How to Create Functions that Contain a Few Arguments1 minute
  • Built-In Functions in Python Worth Knowing4 minutes
1 assignmentTotal 15 minutes
  • Python Functions - Assessment15 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 videosTotal 19 minutes
  • Introduction to Lists4 minutes
  • Using Methods in Python3 minutes
  • What is List Slicing5 minutes
  • Working with Tuples3 minutes
  • Python Dictionaries4 minutes
1 assignmentTotal 15 minutes
  • Python Sequences - Assessment15 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 videosTotal 26 minutes
  • Using For Loops3 minutes
  • Using While Loops and Incrementing2 minutes
  • Use the range() Function to Create Lists4 minutes
  • Combine Conditional Statements and Loops3 minutes
  • All In - Conditional Statements, Functions, and Loops2 minutes
  • Using the Anaconda Assistant: Several Python Tools6 minutes
  • How to Iterate over Dictionaries3 minutes
  • Using the Anaconda Assistant: Dictionaries2 minutes
1 assignmentTotal 15 minutes
  • Using Iterations in Python - Assessment15 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 videosTotal 65 minutes
  • Object Oriented Programming5 minutes
  • Modules, Packages, and the Standard Library4 minutes
  • Importing Modules4 minutes
  • Must-have packages for Finance and Data Science5 minutes
  • Working with arrays6 minutes
  • Generating Random Numbers3 minutes
  • A Note on Using Financial Data in Python3 minutes
  • Sources of Financial Data7 minutes
  • Accessing the Notebook Files3 minutes
  • Importing and Organizing Data in Python – Part I4 minutes
  • Importing and Organizing Data in Python – Part II.A7 minutes
  • Importing and Organizing Data in Python – Part II.B5 minutes
  • Importing and Organizing Data in Python – Part III4 minutes
  • Changing the Index of Your Time-Series Data3 minutes
  • Restarting the Jupyter Kernel2 minutes
1 assignmentTotal 15 minutes
  • Advanced Python Tools - Assessment15 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 videosTotal 43 minutes
  • Considering Both Risk and Return2 minutes
  • What are We Going to See Next?3 minutes
  • Calculating a Security's Rate of Return6 minutes
  • Simple Returns Part I5 minutes
  • Simple Returns Part II3 minutes
  • Log Returns4 minutes
  • Portfolio of Securities and Calculating Rate of Return3 minutes
  • Calculating the Rate of Return of a Portfolio of Securities9 minutes
  • Popular Stock Indices4 minutes
  • Calculating the Return of Indices5 minutes
1 assignmentTotal 15 minutes
  • PART II FINANCE - Calculating and Comparing Rates of Return in Python - Assessment15 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 videosTotal 41 minutes
  • How Do We Measure a Security's Risk?6 minutes
  • Calculating a Security's Risk in Python6 minutes
  • The Benefits of Portfolio Diversification3 minutes
  • Calculating the Covariance between Securities4 minutes
  • Measuring the Correlation between Securities4 minutes
  • Calculating Covariance and Correlation5 minutes
  • Considering the Risk of Multiple Securities3 minutes
  • Calculating Portfolio Risk3 minutes
  • Understanding Systematic Versus Idiosyncratic Risk3 minutes
  • Calculating Diversifiable and NonDiversifiable Risk4 minutes
1 assignmentTotal 15 minutes
  • PART II Finance - Measuring Investment Risk - Assessment15 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 videosTotal 22 minutes
  • Simple Regression Analysis4 minutes
  • Running a Regression in Python7 minutes
  • How to Distinguish Good Regressions5 minutes
  • Computing Alpha, Beta, and R2 in Python6 minutes
1 assignmentTotal 15 minutes
  • PART II Finance - Using Regressions for Financial Analysis - Assessment15 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 videosTotal 20 minutes
  • Markowitz Portfolio Theory7 minutes
  • Obtaining the Efficient Frontier Part I6 minutes
  • Obtaining the Efficient Frontier Part II5 minutes
  • Obtaining the Efficient Frontier Part III2 minutes
1 assignmentTotal 15 minutes
  • PART II Finance - Markowitz Portfolio Optimization - Assessment15 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 videosTotal 27 minutes
  • The Intuition Behind the CAPM5 minutes
  • Understanding and Calculating Beta4 minutes
  • Calculating the Beta of a Stock4 minutes
  • The CAPM Formula4 minutes
  • Calculating the Expected Return of a Stock2 minutes
  • Introducing the Sharpe Ratio2 minutes
  • Obtaining the Sharpe Ratio in Python1 minute
  • Measuring Alpha4 minutes
1 assignmentTotal 15 minutes
  • PART II Finance - The Capital Asset Pricing Model - Assessment15 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 videosTotal 12 minutes
  • Multivariate Regression Analysis6 minutes
  • Running a Multivariate Regression in Python6 minutes
1 assignmentTotal 15 minutes
  • PART II Finance - Multivariate Regression Analysis - Assessment15 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 videosTotal 57 minutes
  • The Essence of Monte Carlo Simulations3 minutes
  • Monte Carlo in Corporate Finance3 minutes
  • MC Predicting Gross Profit Part I6 minutes
  • MC Predicting Gross Profit Part II3 minutes
  • Forecasting Stock Prices with an MC Simulation4 minutes
  • MC Forecasting Stock Prices Part I4 minutes
  • MC Forecasting Stock Prices Part II5 minutes
  • MC Forecasting Stock Prices Part III4 minutes
  • An Introduction to Derivative Contracts7 minutes
  • The Black Scholes Formula5 minutes
  • MC Black Scholes Merton Updated6 minutes
  • MC Euler Discretization Part I6 minutes
  • MC Euler Discretization Part II2 minutes
3 assignmentsTotal 90 minutes
  • PART II Finance - Monte Carlo Simulations as a Decision-Making Tool - Assessment15 minutes
  • Full Course Assessment60 minutes
  • Full Course Practice Assessment15 minutes

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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.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

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Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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