TTh 10:10am–11:25am · TTh 11:40am–12:55pm · TTh 7:10pm–8:25pm +1 more
4 distinct times across 5 sections.
2 of 5 sections have room
Prerequisites Prerequisites: (COMS W3134 or COMS W3136 or COMS W3137) and COMS W3134 OR COMS W3136 OR COMS W3137; Any course on probability
Description
CC/GS: Partial Fulfillment of Science Requirement Prior knowledge of Python is recommended. Provides a broad understanding of the basic techniques for building intelligent computer systems. Topics include state-space problem representations, problem reduction and and-or graphs, game playing and heuristic search, predicate calculus, and resolution theorem proving, AI systems and languages for knowledge representation, machine learning and concept formation and other topics such as natural language processing may be included as time permits
Reviews
Course experience
n=58, 2000–2025
Aggregated across everyone who has taught this course.
Teaching quality
3.8 / 5
Grading fairness
No signal
Workload
4.0 / 5 · Heavy
Difficulty
3.0 / 5 · Moderate
Overall sentiment
Mixed
Would take again
Majority say yes
Sections5
- TTh 10:10am–11:25am · FAIRCHILD LIFE SCIENCES BLDG FLS 601Full
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- Full
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- 111 of 150 seats left
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- Full
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- 73 of 99 seats left
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
In your week
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
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