πŸ“† Course Schedule

πŸ“† Course Schedule#

Note

This schedule is subject to change as appropriate.

Last Updated: 7 Sep 2025

Lsn

Topic

Reading

Due

1

Course Intro

2

Propositional Logic

1.1-1.2.5

3

Logical Equivalence

1.3.1-1.3.4

4

Predicates & Quantifiers

1.4-1.5

HW1(L2-3)

5

Rules of Inference

1.6

6

Intro to Proofs

1.7

HW2(L4-5)

7

M-day: no class, T-day: review

8

Sets & Set Operations

2.1-2.2

9

Functions

2.3

HW3(L6-8)

10

Sequences and Summations

2.4

11

Algorithms

3.1-3.1.5

HW4(L9-10)

12

Growth of Functions

3.2

Q1(L2-10)

13

Complexity of Algorithms

3.3-3.3.3

14

Mathematical Induction

5.1

HW5(L11-12)

15

Graphs

10.1-10.2.2,10.3-10.3.3,10.4.2

16

Shortest Path

10.6

HW6(L13-15)

17

Probability Models

B&T 1.2

Q2(L11-15)

18

GR1 (L1-L15)

19

Conditional Probability

1.3

20

Bayes’ rule, Independence of Events

1.4-1.5

HW7(L16-L19)

21

Discrete Random Variables

2.1-2.2

22

Expectation, Mean, Variance

2.3-2.4

HW8(L20-21)

23

Joint PMFs

2.5

24

Conditioning and Independence

2.6-2.7

HW9(L22-24)

25

Continuous RVs, PDFs, CDFs

3.1-3.2

Q3

26

Normal Random Variables

3.3

HW10(L25-26)

27

Joint PDFs of Continuous RVs, Conditioning

3.4-3.5

28

Continuous Bayes’ Rule

3.6

HW11(L27-28)

29

Derived Distributions

4.1

30

Covariance and Correlation

4.2

HW12(L29-30)

31

Conditional Expectation and Variance

4.3

32

Bayesian Inference

8.1

HW13(L31-32)

33

MAP Estimation, Bayesian LMS Estimation

8.2-8.3

34

TBD

Q4(L22-32)

35

GR2 (L15-L32)

36

Bayesian Linear LMS Estimation

8.4

37

Linear Regression

9.1-9.2

HW14(L33-36)

38

Hypothesis Testing

9.3

39

Hypothesis Testing

9.3

HW15(L37-38)

40

Review

9.3

Q5(30-39)

Final Exam (L1-L40)