23-1-Math and Stat for Data Science-Schedule

	B	C	D	E	F	G	H	I
1
2	Week	Lecture	Date	Day	Topic	HW Coverage	HW out/due date	Chapters from textbook
3	Week1	1	3/6	Mon	Course intro, Linear algebra I	HW1		mml 2.1~2.3
4		2	3/8	Wed	Linear Algebra II			mml 2.4~2.7
5	Week2	3	3/13	Mon	Analytic Geometry I		HW1 out	mml 3.1~3.4
6		4	3/15	Wed	Analytic Geometry II		Paper 1 (backpropagation) out	mml 3.5~3.9
7	Week3	5	3/20	Mon	Matrix Decomposition I	HW2		mml 4.1~4.2
8		6	3/22	Wed	Matrix Decomposition II			mml 4.3~4.5
9	Week4	7	3/27	Mon	Vector Calculus I		HW1 due	mml 5.1~5.5
10		8	3/29	Wed	Vector Calculus II		Paper 1 (backpropagation) due, HW2 out	mml 5.6~5.8
11	Week5	9	4/3	Mon	Probability I			aos 1.1~1.5
12		10	4/5	Wed	Probability II		Paper 2 (Monty Hall) out	aos 1.6~1.7
13	Week6	11	4/10	Mon	Random Variable I	HW3		aos 2.1~2.4
14		12	4/12	Wed	Random Variable II		HW2 due (4/15)	aos 2.5~2.12
15	Week7	13	4/17	Mon	Midterm
16		14	4/19	Wed	Expectation, Variance I			aos 3.1~3.4
17	Week8	15	4/24	Mon	Expectation, Variance II, Convergence I		Paper 2 (Monty Hall) due (4/23)	aos 3.5~3.6, aos 4
18		16	4/26	Wed	Convergence II			aos 5
19	Week9	17	5/1	Mon	Statistical Inference I		HW3 out/ Paper 3 (error estimation) out	aos 6.1~6.3.1
20		18	5/3	Wed	Statistical Inference II			aos 6.3.2~6.3.3
21	Week10	19	5/8	Mon	CDF	HW4		aos 7.1~7.2
22		20	5/10	Wed	Bootstrap			aos 8
23	Week11	21	5/15	Mon	Parametric Inference I			aos 9.1~9.6
24		22	5/17	Wed	Parametric Inference II		HW3 due	aos 9.7~9.8
25	Week12	23	5/22	Mon	Parametric Inference III		Paper 3 (error estimation) due (5/23)	aos 9.9~9.11
26		24	5/24	Wed	Hypothesis Testing and p-value I		HW4 out	aos 10.1~10.4, 10.6
27	Week13	25	5/29	Mon	Hypothesis Testing and p-value II			aos 10.5, 10.7
28		26	5/31	Wed	Bayesian Inference I			aos 11.1~11.5
29	Week14	27	6/5	Mon	Bayesian Inference II		HW4 Due (6/6)	aos 11.6~11.9
30		28	6/7	Wed	Bayesian Inference II (cont')
31	Week15	29	6/12	Mon	No Class
32		30	6/14	Wed	Final
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34	* This schedule may be subject to change.
35	** mml: Math for Machine Learning (https://mml-book.github.io/)
36	*** aos: All of Statistics (https://link.springer.com/book/10.1007/978-0-387-21736-9)
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