Master of Computer Science - Data Science Applicant Community (Coursera)

Master of Computer Science - Data Science Applicant Community (Coursera)

With a full tuition under $20K, the University of Illinois Master of Computer Science - Data Science (MCS-DS) is the most affordable gateway to one of the most lucrative and fastest growing careers of the new millennium. The MCS-DS builds expertise in four core areas of computer science: data visualization, machine learning, data mining and cloud computing, in addition to building valuable skill sets in statistics and information science with courses taught in collaboration with the University’s Statistics Department and ISchool (ranked #1 among Library and Information Studies Schools.)

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

The purpose of this community is to provide you with resources and support during the application process for the MCS-DS. You can post questions, discuss with fellow students who are also considering applying, and read about latest updates of the program. Admission officers from the University of Illinois will also be active in the forums and answer questions.
If you have any questions/feedback please post them in the forums!

Syllabus

WEEK 1
Welcome!
Welcome to the applicant forums for the Master of Computer Science in Data Science! Please find below helpful information on the program and the application process. If you have more questions you are very welcome to post them in the Discussion Forums.

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

Related Courses

Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Nov 9th 2026
4 Weeks
Data Science in Stratified Healthcare and Precision Medicine (Coursera) Coursera
University of Edinburgh

Data Science in Stratified Healthcare and Precision Medicine (Coursera)

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine.

Nov 2nd 2026
5-12 Weeks
Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera) Coursera
Duke University

Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera)

In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space.

Nov 2nd 2026
5-12 Weeks
Applied Plotting, Charting & Data Representation in Python (Coursera) Coursera
University of Michigan

Applied Plotting, Charting & Data Representation in Python (Coursera)

This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework.

Nov 2nd 2026
4 Weeks
Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera) Coursera
IBM

Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera)

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.

Nov 9th 2026
4 Weeks
Introduction to TCP/IP (Coursera) Coursera
Yonsei University

Introduction to TCP/IP (Coursera)

You use the Internet through your PC (Personal Computer), laptop, tablet, smartpad, and smartphone every day in everything you do. Through your own PC/laptop, you can easily learn everything about the Internet, and that is what this course is focused on. In this course ‘Introduction to TCP/IP,’ you will learn the operational functions of Internet technologies (which include IPv4, IPv6, TCP, UDP, addressing, routing, domain names, etc.) and your PC/laptop's security and gateway Internet setup and basic principles.

Nov 9th 2026
5-12 Weeks
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Nov 9th 2026
5-12 Weeks