07-280 AI & ML I
New in Spring 2026!
This course provides an integrated introduction to artificial intelligence and machine learning that bridges core AI methods with modern approaches. Students develop both theoretical mastery and practical expertise by combining foundational concepts with the construction of influential AI systems.
The curriculum covers foundational materials in search, machine learning, reinforcement learning, and probability. Students then build on these to construct detailed implementations of landmark AI systems such as AlexNet, GPT-2, and AlphaZero. This rigorous approach develops the analytical skills needed to build the future AI. Finally, as an essential component, this course will address the ethics and responsible development of AI/ML technology and products.
The course emphasizes both technical excellence and ethical considerations in AI development. It serves as the foundation for 07-380 Artificial Intelligence and Machine Learning II, which explores advanced topics, research methods, and specialized applications.
Frequently Asked Questions
- How does this compare to 10-301?
- Why this course?
- Will 15-281 and 10-315 continue to be offered?
- Who will teach the new courses?
- How often will 07-280 and 07-380 be offered?
- What topics will be covered in 07-380 AI & ML II?
- Are the prereq and coreqs strict requirements?
Question not answered here? Please fill out this form.
How does this compare to 10-301?
Both courses cover sufficient material for an intro machine learning course 07-280 includes non-ML AI techniques, while 10-301 focuses only on ML, naturally reaching a few additional ML topics.
| 07-280 | 10-301 | |
|---|---|---|
| Prereqs (see course description for detailed course numbers) |
Prereq: 15-122 Coreq: Probability Prereq: Linear Algebra Prereq: 15-151/Concepts Coreq: Calc 2 |
Prereq: 15-122 or 15-121 Prereq: Probability Prereq: (Linear Algebra or Calc 3 or 151/Concepts) |
| Fulfills the Intro ML prereq for later ML (10-XXX) courses | check_circle | check_circle |
| Fulfills the 07-280 prereq for 07-380 AI/ML II | check_circle | No, but 10-301 + 16-350 Planning Techniques for Robotics does. |
| Fulfills the 07-280 requirement for the AI Major, Additional Major, and Minor |
check_circle | No, but 10-301 + 16-350 Planning Techniques for Robotics does. |
| Fulfills the Intro ML prereq for the ML Concentration Minor | check_circle | check_circle |
| Fulfills the Intro ML prereq for the 5th year ML Master's | check_circle | check_circle |
| Topics: ML fundamentals from decision trees to neural networks | check_circle | check_circle |
| Topics: Transformer networks and Large Language Models | check_circle | check_circle |
| Topics: Reinforcement Learning | check_circle | check_circle |
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| TA mascot | 🤷 | Neural the Narwhal |
Why this course?
The goal is to replace the older AI and ML courses, 15-281 and 10-315, with two sequenced courses, 07-280 and 07-380, covering the breadth and depth required by the AI majors, with the first of the two courses covering core AI and ML concepts for SCS students taking only one AI course, as well as anyone at CMU who wants a good technical introduction to the field.
This restructure will provide the following benefits:
- Flexibility to grow two AI courses
- Adapting topics
- Building on first course in the second course
- Better single AI course for non-AI majors
- First course as accessible as 15-281 is now
- First course includes core ML topics in addition to AI breadth
Will 15-281 and 10-315 continue to be offered?
No, 15-281 and 10-315 are being retired and will not be offered in the future.
Who will teach the new courses?
The new courses will be taught by a mix of faculty, primarily from the Machine Learning and Computer Science Departments.
In Spring 2026, 07-280 will be taught by Nihar Shah (CSD/MLD) and Pat Virtue (CSD/MLD), and 10-301 will be taught by Matt Gormley (MLD) and Pat Virtue (CSD/MLD).
How often will 07-280 and 07-380 be offered?
Both courses, 07-280 and 07-380, will be offered every semester (Fall and Spring), with 07-380 first being offered in Fall 2026.
What topics will be covered in 07-380 AI & ML II?
07-380 is designed to be more flexible in its topics from semester to semester, adapting based on our faculty's best understanding of what additional/advanced AI/ML topics students need to learn, especially those graduating with a major/minor in AI. It builds upon 07-280, so we'll be able to explore more advanced topics in greater depth, while also increasing the breadth of topics across all of AI.
Potential topics include: Deeper AI/ML Ethics, MAP, ML Theory: PAC Learning, PCA, Clustering and K-means, Ensemble Methods: Bagging and Boosting, Recommender Systems, Linear programming, Integer programming, Propositional Logic, SAT, and Logical Agents, Classical Planning, Bayes' Nets: Representation, Bayes' Nets: Inference, Bayes' Nets: Sampling, HMMs, Game Theory: Equilibrium, Game Theory: Social Choice, Vision Transformers, Variational Autoencoders, Diffusion, Text to Image Generation, Distributed Deep Learning, Optimization: RMS, Momentum, Stability, RLHF and DPO.
Are the prereq and coreqs strict requirements?
Yes, the prerequisites and corequisites are strict requirements for enrollment in 07-280.