Application Engineering Courses
Ph.D., MLT, and 5LT students must take at least one course that satisfies an Application Engineering requirement. Application Engineering courses provide experience using core language technologies to build software systems that tackle real-world applications. At least 50% of the course grade is based on homework assignments and projects that require significant software development.
Note for Ph.D. Students: Some Application Engineering courses may also fulfill a Breadth requirement. A single course is allowed to simultaneously fulfill a Ph.D. Breadth requirement and also the Application Engineering requirement.
The courses that satisfy the Application Engineering requirement are listed below.
| 11-642 | Search Engines | 12 | Fall/Spring |
| 11-667 | Large Language Models: Methods and Applications | 12 | Fall |
| 11-685 | Introduction to Deep Learning | 12 | Fall/Spring |
| 11-692 | Speech Technology for Conversational AI | 12 | Spring |
| 11-741 | Machine Learning with Graphs | 12 | Fall |
| 11-751 | Speech Recognition and Understanding | 12 | Fall |
| 11-755 | Machine Learning for Signal Processing | 12 | Fall |
| 11-767 | On-device Machine Learning | 12 | Fall |
| 11-775 | Large-Scale Multimedia Analysis | 12 | Fall |
| 11-777 | Multimodal Machine Learning | 12 | Spring |
| 11-785 | Introduction to Deep Learning | 12 | Fall/Spring |
| 11-797 | Question Answering | 12 | Spring |
| 11-851 | Talking to Robots (12-unit section only) | Fall | |
| 11-866 | Artificial Social Intelligence | 12 | Spring |
| 11-877 | Advanced Topics in Multimodal Machine Learning | 12 | Spring |
| 11-891 | Neural Code Generation | 12 | Fall |