Computers are incredibly dumb. However, they can be programmed to appear incredibly clever using some fancy mathematics.
This introductory course on Artificial Intelligence covers:
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Raj Venkat r.venkatesaramani@northeastern.edu Office Hours: Meserve 303, Monday & Friday 10:00 am - 12:30 pm (preferred) Online Office Hours: Campuswire, Wednesday, 11:00am - 12:00pm To request appointments outside of office hours, click here. If you decide to swing by on a whim, and my office door is open, feel free to bug me. |
Lectures | 3:25 pm - 5:05 pm, Tue & Fri | Shillman 135 |
Questions | 24/7 | Campuswire - CS5100 (Group Join Code - 7915) |
Written Submissions | until 11:59 pm, due day | Gradescope |
Code Submissions | until 11:59 pm, due day | Github (by invite) |
Day | Date | Topics | Readings | Assignments & Deadlines | Notes |
---|---|---|---|---|---|
Fri | 9/8 | Introduction, history of AI, some philosophy | Lecture 1 | ||
Tue | 9/12 | The vocabulary of AI, problem formulation, search | Computing Machinery and Intelligence, A. Turing, 1950 | Lecture 2 | |
Fri | 9/15 | Uniform cost search, heuristics, A*, beam | Uninformed Search, Artificial Intelligence 2E | ||
Tue | 9/19 | Local search, Hill Climbing, Genetic Algorithms | A Fast Exact Algorithm for the Resource Constrained Shortest Path Problem, Ahmadi et al. 2021 |
HW1 out | |
Fri | 9/22 | Games, minimax, alpha-beta pruning, Monte Carlo | |||
Tue | 9/26 | Constraint satisfaction problems, baacktracking | Deep Blue, Campbell et al. 2002, Artificial Intelligence | ||
Fri | 9/29 | Non-determininstic environments, expectimax | |||
Tue | 10/3 | Markov Decision Processes | HW1 due, HW2 out | ||
Fri | 10/6 | Markov Decision Processes (contd.) | |||
Tue | 10/10 | Reinforcement Learning | Project Title and Abstract | ||
Fri | 10/13 | Reinforcement Learning (contd.) | |||
Tue | 10/17 | Markov models | HW2 due, HW3 out | ||
Fri | 10/20 | Hidden Markov models | Project Proposal due | ||
Tue | 10/24 | Bayes networks | |||
Fri | 10/27 | Supervised ML | |||
Tue | 10/31 | Supervised ML (contd.) | |||
Fri | 11/3 | Unsupervised ML | |||
Tue | 11/7 | Natural language processing | HW3 due, HW4 out | ||
Fri | 11/10 | Deep learning, large language models | |||
Tue | 11/14 | Deep reinforcement learning | |||
Fri | 11/17 | Computer vision & adversarial ML | |||
Tue | 11/21 | Ethics in AI | HW4 due | ||
Fri | 11/24 | --- Day after Thanksgiving --- NO CLASS --- | |||
Tue | 11/28 | Ethics in AI (contd.) | |||
Fri | 12/1 | Project Presentations | |||
Tue | 12/5 | Project Presentations (contd.) | |||
Fri | 12/8 | Project Presentations (contd.) | |||
Tue | 12/12 | ---NO CLASS--- | Final Project Report due |
A | [93, 100] |
A- | [90, 93) |
B+ | [87, 90) |
B | [82, 87) |
B- | [80, 82) |
C+ | [77, 80) |
C | [72, 77) |
C- | [70, 72) |
F | [0, 70) |
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Mrudula Acharya acharya.mr@northeastern.edu Office Hours: Wed 5-6 pm, Thurs 11 am - 12 pm, Campuswire |
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Tarun Saxena saxena.ta@northeastern.edu Office Hours: Thurs 4-5 pm, Fri 1-2 pm, Campuswire |
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Sree Haritha Emani vempati.sr@northeastern.edu Office Hours: Tue 12-1 pm, Wed 1-2 pm, Campuswire |
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Sideeshwaran Lakkapuram Balasubramani lakkapurambalasubr.s@northeastern.edu Office Hours: Mon 5-6 pm, Wed 6-7 pm Campuswire |
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Anirudh Muthuswamy muthuswamy.a@northeastern.edu Office Hours: Tue & Thurs, 10-11 am, Campuswire |