Computational Machine Learning

Learn to harness the power of machine learning in your daily work.

Expand your knowledge of computational machine learning with this online course created by leading experts from Michigan Engineering.

Learn More About the Course

Immediately apply new techniques and tools to your work.

Experience hands-on learning with a cloud-based interactive computational textbook.

Learn at your own pace.

Fully online and self-paced with instructor support available.

Elevate your professional skill set.

Earn a respected certification from the University of Michigan.

I wanted to learn how machine learning works and how it could be applied in my sphere of influence to improve my work products and how it could be used at home as well. I can honestly say that I can see potential for ML all around me! I would often find myself saying, “This would be a great use for ML. How would I build the network?” I understand now how deep networks work, how generative networks work, and how people are using ML in all areas of business, science, and technology.

- Past Participant

My primary goal in this course was twofold: to obtain an overview of the extensive field of deep neural networks and to gain hands-on experience designing and evaluating some of the particular techniques. This course has enabled me to achieve my goal and more.

- Past Participant

I started out with a decent coding foundation but absolutely no understanding of ML outside of buzz and articles meant for the general public. I was hoping to learn details about several different classes of ML algorithms and the problems that they can be applied to, and how to implement them. I feel confident that I can now apply various forms of neural nets to solve many different problems.

- Past Participant

Raj Rao Nadakuditi, PhD

Associate Professor, Electrical Engineering and Computer Science (EECS)

Professor Raj Rao Nadakuditi, PhD is an award-winning researcher and teacher dedicated to making machine learning accessible to individuals from all disciplines. In addition to receiving the Jon R. and Beverly S. Holt Award for Excellence in Teaching, Prof. Nadakuditi has received the DARPA Directors Award, DARPA Young Faculty Award, IEEE Signal Processing Society Best Young Author Paper Award, Office of Naval Research Young Investigator Award, and the Air Force Research Laboratory Young Faculty Award.

Frequently Asked Questions (FAQ)

Is this course offered online?

Yes, this course is self-paced and fully online. You will have access to the course for 13 weeks and will participate in an average of 5-6 hours of coursework and instruction per week.

What if I have questions about the course material?

Instructors and support staff are available through the course’s learning management system to assist you with any questions or issues that arise during your study.

Are there any prerequisites for course registration?

You will be required to submit an application that includes a pre-test before registration. After being admitted, you can enroll in the course at any time.

How is this course different from other online machine learning courses?

This course features a unique cloud-based interactive computational textbook, real-world datasets, and personalized support from expert instructors. It also emphasizes both the practical and theoretical aspects of machine learning.

Do you have to be a data scientist or engineer to attend this course?

Your title does not have to be data scientist or engineer to enroll. However, the course is highly technical and intended for those with existing programming and math skills. A pre-test is required during the application process to ensure you have the foundational knowledge needed for success.