CS50's Introduction to Artificial Intelligence with Python
The Foundation of Modern Artificial Intelligence
Join Harvard University Professor David J. Malan in this introductory online course on artificial intelligence to learn how to use machine learning in Python.
10-30 hours a week
What You'll Learn
AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.
CS50’s Introduction to Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
Enroll now to gain expertise in one of the fastest-growing domains of computer science from the creators of one of the most popular computer science courses ever, CS50. You’ll learn the theoretical frameworks that enable these new technologies while gaining practical experience in how to apply these powerful techniques in your work.
The course will be delivered via edX and connect learners around the world. By the end of the course, participants will understand the following concepts:
- graph search algorithms
- adversarial search
- knowledge representation
- logical inference
- probability theory
- Bayesian networks
- Markov models
- constraint satisfaction
- machine learning
- reinforcement learning
- neural networks
- natural language processing
Your Instructors
David J. Malan
Gordon McKay Professor of the Practice of Computer Science
at Harvard University
Read full bio.
Ways to take this course
When you enroll in this course, you will have the option of pursuing a Verified Certificate or Auditing the Course.
A Verified Certificate costs $299 and provides unlimited access to full course materials, activities, tests, and forums. At the end of the course, learners who earn a passing grade can receive a certificate.
Alternatively, learners can Audit the course for free and have access to select course material, activities, tests, and forums. Please note that this track does not offer a certificate for learners who earn a passing grade.