On-Demand Learning

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

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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

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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

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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

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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

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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

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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

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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

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

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

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

How can we create agile micro aerial vehicles that can operate autonomously in cluttered indoor and outdoor environments? In this course you’ll explore the mechanics of flight and the design of quadrotor flying robots and learn to develop dynamic models, derive controllers, and synthesize planners for operating in 3D environments.

• 4 Weeks
• 4 Hours per Week
• Self-paced
• Instructor: Vijay Kumar
• Hosted on Coursera

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Robotic systems include three components: a mechanism for exerting forces and torques on the environment, a perception system for sensing the world, and a decision and control system that modulates the robot’s behavior to achieve a particular goal. In this course, you’ll explore how a robot decides what to do to achieve its goals.

• 4 Weeks
• 3 Hours per Week
• Self-paced
• Instructor: C.J. Taylor
• Hosted on Coursera

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How can robots use their motors and sensors to move around in an unstructured environment? Learn to design robot bodies and behaviors that recruit appendages to apply physical forces that confer reliable mobility in a complex and dynamic world.

• 4 Weeks
• 2-4 Hours per Week
• Self-paced
• Instructor: Daniel E. Koditschek
• Hosted on Coursera

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How can robots perceive the world and their own movements so that they accomplish navigation and manipulation tasks? In this course, you will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow.

• 4 Weeks
• 3-5 Hours per Week
• Self-paced
• Instructors: Kostas Daniilidis Jianbo Shi
• Hosted on Coursera

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How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this course you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world.

• 4 Weeks
• 3-4 Hours per Week
• Self-paced
• Instructor: Daniel Lee
• Hosted on Coursera

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The six-week Robotics Capstone gives you the opportunity to implement a solution for a real-world problem based on what you’ve learned in the robotics specialization. It also offers a chance to use the mathematical and programming methods that researchers use in robotics labs.

• 6 Weeks
• 2-4 Hours per Week
• Self-paced
• Instructors: Kostas Daniilidis and Sid Deliwala
• Hosted on Coursera

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