Explore the field of engineering through on-demand learning. Taught by Penn Engineering faculty and offered in partnership with Coursera and edX, our noncredit courses and credentials are flexible, self-paced, open to everyone – and affordable.
Register for an On-Demand Course
Penn Engineering Alumni
If you are a Penn Engineering Alum who would like to register for free access to an on-demand course, please register by filling out a short application. Please note that you must use your alumni email address (how to activate your alumni email address).
General Public
If you are not a Penn Engineering Alum, please click “Enroll Today” under the course(s) you wish to join.
Current On-Demand Learning Options
General Courses
Computational Thinking for Problem Solving
Learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language.
- 4 Weeks
- 3 Hours per Week
- Self-paced
- Instructors: Chris Murphy and Susan Davidson
- Hosted on Coursera
Exploring Renewable Energy Schemes
Learn to integrate the scientific and technological principles that are necessary to assess and implement small-scale renewable energy schemes.
- 6 Weeks
- 3 Hours per Week
- Self-paced
- Instructor: Jorge Santiago-Aviles
- Hosted on Coursera
Urban Transit for Livable Cities
Learn to develop customized urban transit plans and improve city mobility by bridging technical knowledge with practical application.
- 8 Weeks
- 3-6 Hours per Week
- Self-paced
- Instructor: Vukan Vuchic
- Hosted on edX
Programming Courses
Earn a specialization certificate by completing the four courses listed here and paying the certificate fee.
Introduction to Python Programming
Explore core programming concepts like data structures, conditionals, loops, variables, and functions. This course will get you ready to code at a fast pace.
- 4 Weeks
- 6 Hours per Week
- Self-paced
- Instructor: Brandon Krakowsky
- Hosted on Coursera
Data Analysis Using Python
Discover core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. You’ll also get an overview of loading, inspecting, and querying real-world data.
- 3 Weeks
- 6 Hours per Week
- Self-paced
- Instructor: Brandon Krakowsky
- Hosted on Coursera
Introduction to Java and Object-Oriented Programming
Learn how to write custom Java classes and methods, and how to test code using unit testing and test-driven development. Topics include basic data structures like Arrays and ArrayLists and overloading methods.
- 3 Weeks
- 6 Hours per Week
- Self-paced
- Instructor: Brandon Krakowsky
- Hosted on Coursera
Inheritance and Data Structures in Java
Get a comprehensive look at Java inheritance, including access modifiers and overriding methods. Explore abstract classes and learn how to read and write to files, use regular expressions for parsing text, and how to leverage complex data structures like collections and maps.
- 4 Weeks
- 6 Hours per Week
- Self-paced
- Instructor: Brandon Krakowsky
- Hosted on Coursera
AI and Machine Learning Courses
Earn a specialization certificate by completing the four courses listed here and paying the certificate fee.
Artificial Intelligence Essentials
Take a look at artificial intelligence through philosophical and science fiction lenses, and review Python basics. Then explore AI algorithms through studying rational agents and common search algorithms like A* search. Complete short coding assignments in Python.
- 4 weeks
- 8 hours per week
- Self-paced
- Instructor: Chris Callison-Burch
Statistics Essentials
Review the basics of discrete math and probability before enhancing your probability skills and learning how to interpret data with tools such as the central limit theorem, confidence intervals and more. Complete short weekly mathematical assignments.
- 4 weeks
- 8 hours per week
- Self-paced
- Instructor: Hamed Hassani
Machine Learning Essentials
Use statistical learning techniques like linear regression and classification to solve common machine learning problems. Complete short coding assignments in Python.
- 4 weeks
- 8 hours per week
- Self-paced
- Instructor: Victor Preciado
Deep Learning Essentials
Delve into the history of deep learning, and explore neural networks like the perceptron, how they function, and what architectures underpin them. Complete short coding assignments in Python.
- 4 weeks
- 8 hours per week
- Self-paced
- Instructor: Pratik Chaudhari
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