Introduction to Portfolio Construction and Analysis with Python (Coursera)

Offered by EDHEC Business School,
Introduction to Portfolio Construction and Analysis with Python (Coursera)

The practice of investment management has been transformed in recent years by computational methods. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course is the first in a four course specialization in Data Science and Machine Learning in Asset Management but can be taken independently. In this course, we cover the basics of Investment Science, and we'll build practical implementations of each of the concepts along the way. We'll start with the very basics of risk and return and quickly progress to cover a range of topics including several Nobel Prize winning concepts. We'll cover some of the most popular practical techniques in modern, state of the art investment management and portfolio construction.
As we cover the theory and math in lecture videos, we'll also implement the concepts in Python, and you'll be able to code along with us so that you have a deep and practical understanding of how those methods work. By the time you are done, not only will you have a foundational understanding of modern computational methods in investment management, you'll have practical mastery in the implementation of those methods.
Course 1 of 4 in the Investment Management with Python and Machine Learning Specialization.

What You Will Learn

  • Gain an intuitive understanding for the underlying theory behind Modern Portfolio Construction Techniques
  • Write custom Python code to estimate risk and return parameters
  • Utilize powerful Python optimization libraries to build scientifically and systematically diversified portfolios
  • Build custom utilities in Python to test and compare portfolio strategies

Syllabus

WEEK 1: Analysing returns
WEEK 2: An Introduction to Portfolio Optimization
WEEK 3: Beyond Diversification
WEEK 4: Introduction to Asset-Liability Management

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Using Databases with Python (Coursera) Coursera
University of Michigan

Using Databases with Python (Coursera)

This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization.

Sep 28th 2026
5-12 Weeks
Foundations of Data Science: K-Means Clustering in Python (Coursera) Coursera
University of London,Goldsmiths, University of London

Foundations of Data Science: K-Means Clustering in Python (Coursera)

This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks.

Oct 5th 2026
5-12 Weeks
Applied Social Network Analysis in Python (Coursera) Coursera
University of Michigan

Applied Social Network Analysis in Python (Coursera)

This course will introduce the learner to network analysis through the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness.. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem.

Sep 28th 2026
4 Weeks
Python and Statistics for Financial Analysis (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Python and Statistics for Financial Analysis (Coursera)

Python is now becoming the number 1 programming language for data science. Due to python’s 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.

Oct 5th 2026
4 Weeks
Introduction to Linear Algebra and Python (Coursera) Coursera
Howard University

Introduction to Linear Algebra and Python (Coursera)

This course is the first of a series that is designed for beginners who want to learn how to apply basic data science concepts to real-world problems. You might be a student who is considering pursuing a career in data science and wanting to learn more, or you might be a business professional who wants to apply some data science principles to your work. Or, you might simply be a curious, lifelong learner intrigued by the powerful tools that data science and math provides. Regardless of your motivation, we’ll provide you with the support and information you need to get started.

Sep 28th 2026
4 Weeks
Global Warming II: Create Your Own Models in Python (Coursera) Coursera
University of Chicago

Global Warming II: Create Your Own Models in Python (Coursera)

This class provides a series of Python programming exercises intended to explore the use of numerical modeling in the Earth system and climate sciences. The scientific background for these models is presented in a companion class, Global Warming I: The Science and Modeling of Climate Change. This class assumes that you are new to Python programming (and this is indeed a great way to learn Python!), but that you will be able to pick up an elementary knowledge of Python syntax from another class or from on-line tutorials.

Oct 5th 2026
5-12 Weeks
Algorithmic Thinking (Part 2) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 2) (Coursera)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Oct 5th 2026
4 Weeks