Jan. 6

Jan. 8

Introduction to machine intelligence

3

Jan. 13

Handling uncertainty using Bayesian framework-I

Jan. 15

Handling uncertainty using Bayesian framework-II

5

Jan. 16

Project Selection Deadline

Jan. 20

Handling uncertainty using Bayesian framework-III

Jan. 22

Guest Lecture: Speech Recognition by Dr. Colin Wightman, CTO, Vestec Inc.

Jan. 27

Dealing with vagueness using fuzzy logic-I

Jan. 29

Dealing with vagueness using fuzzy logic-II

10

Feb. 2

SOW due date

11

Feb. 3

Problem solving via trajectory-based metaheuristics

12

Feb. 5

Problem solving via population-based metaheuristics-I

13

Feb. 6

Quiz #1

14

Feb. 10

Problem solving via population-based metaheuristics-II

15

Feb. 12

Problem solving via population-based metaheuristics-III

16

Feb. 16-20

Reading Week

17

Feb. 24

Problem solving via population-based metaheuristics-IV

18

Feb. 26

Making decisions under uncertainty using decision trees

19

Feb. 27

Mid-term report submission

20

Mar. 3

Decision tree learning

21

Mar. 5

Learning from Examples using neural networks-I

22

Mar. 6

Quiz #2

23

Mar. 10

Learning from Examples using neural networks-II

24

Mar. 12

Learning from Examples using neural networks-III

25

Mar. 17

Learning from Observation using reinforcement learning-I

26

Mar. 19

Learning from Observation using reinforcement learning-II

27

Mar. 24

Guest Lecture- Support Vector Machines: The Triumph of Mathematics by
Professor Hamid R. Tizhoosh, Systems Design Engineering - University of Waterloo

28

Mar. 26

Hybrid intelligent systems

29

Mar. 27

Quiz #3

30

Mar. 29

Coure Project Paper Submission

31

Mar. 31

Project Presentations

32

Apr. 2

Project Presentations

33

Apr. 6 [Last Class]

Lectures/classes end

34

Apr. 7-9

Pre-examination study days

35

Apr. 10-25

On-campus examinations begin

36

Apr. 27

Unofficial Grades begin to appear