Master_AC295_fall

	A	B	C	D	E
1	AC295 FALL 2020 SCHEDULE
2	Week	Date	Lecture #	Topics	Exercise
3	1	9/3	1	Introduction: Virtual Enviroments and Virtual Boxes
4	2	9/8	2	Containers	EX1
5		9/10		Use Case: Dockers in a real setting
6	3	9/15	3	Kubernetes	EX2
7		9/17		Use Case: Kubernetes in a real setting
8	4	9/22	4	Dask	EX3
9		9/24		Use Case: Dask in a real setting
10	5	9/29		Practicum 1: End to end art search engine	Practicum 1
11		10/1		Practicum 1
12	6	10/6	5	Intro to Transfer Learning: basics and CNNs review	EX4
13		10/8		Journal Discussion: Transfer Learning (Statistical approaches to Transfer Learning)
14	7	10/13	6	Transfer Learning for Images and SOTA Models	EX5
15		10/15		Journal Discussion:
16	8	10/20	7	Language Models and Transfer Learning for Text	EX6
17		10/22		Journal Discussion
18	9	10/27	8	Attention and Transformers	EX7
19		10/29		Journal Discussion	FP Project Proposal
20	10	11/3	9	Distillation and Compression	EX8
21		11/5		Journal Discussion
22	11	11/10		Practicum 2	Practicum 2
23		11/12		Practicum 2
24	12	11/17	10	Introduction and Overview of Viz for Deep Models: lime and shapley	FP Scope of Work
25		11/19	11	CNNs for Image Data, Activation Maximization and Saliency Maps
26	13	11/24	12	Attention for Debugging Language Models
27		11/26
28	14	12/1		Project
29		12/3		Project	FP Project Review
30	15	12/8		Project
31		12/10		Project
32	16	12/15		Final projects presentation	FP Presentation
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