📆 Course Schedule#
Note
This schedule is subject to change as appropriate.
Last Updated: 17 Aug 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 |
HW4(L9-10) |
12 |
Growth of Functions & Basic Complexity |
3.2-3.3 |
Q1(L2-10) |
13 |
Divisibility and Integers |
4.1-4.2 |
|
14 |
Mathematical Induction |
5.1 |
HW5(L11-13) |
15 |
Strong Induction & Recursion |
5.2-5.2.3, 5.3.2 |
|
16 |
Introduction to Graphs |
10.1-10.2 |
Q2(L11-15) |
17 |
Graph Representations & Connectivity |
10.3-10.4 |
HW6(L14-15) |
18 |
GR1 (L1-L15) |
||
19 |
Euler and Hamilton Paths |
10.5 |
|
20 |
Shortest-Path |
10.6 |
HW7(L16-19) |
21 |
Probability Models, Conditional Probability |
1.2-1.3 |
|
22 |
Bayes’ rule, Independence of Events |
1.4-1.5 |
HW8(L20-21) |
23 |
Discrete Random Variables |
2.1-2.2 |
|
24 |
Expectation, Mean, Variance |
2.3-2.4 |
HW9(L22-23) |
25 |
Joint PMFs |
2.5 |
Q3(L16-L23) |
26 |
Conditioning and Independence |
2.6-2.7 |
|
27 |
Continuous RVs, PDFs, CDFs |
3.1-3.2 |
HW10(L24-26) |
28 |
Normal Random Variables |
3.3 |
|
29 |
Joint PDFs of Continuous RVs, Conditioning |
3.4-3.5 |
HW11(L27-28) |
30 |
Continuous Bayes’ Rule |
3.6 |
|
31 |
Derived Distributions |
4.1 |
|
32 |
Covariance and Correlation |
4.2 |
Q4(L24-31) |
33 |
Conditional Expectation and Variance |
4.3 |
HW12(L29-31) |
34 |
GR2 (L15-L31) |
||
35 |
Bayesian Inference |
8.1 |
|
36 |
MAP Estimation, Bayesian LMS Estimation |
8.2-8.3 |
HW13(L32-35) |
37 |
Bayesian Linear LMS Estimation |
8.4 |
|
38 |
Linear Regression |
9.1-9.2 |
|
39 |
Hypothesis Testing |
9.3 |
HW14(L36-38) |
40 |
Review |
9.3 |
Q5(32-39) |
Final Exam (L1-L40) |