Lectures

Cogs 138 Sp23

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Click the links in the topics column to download pdf of lecture notes.

Current week is highlighted in yellow. Topics may change slightly (or order of topics).

Week	Lecture #	Date	Topics	Description	Section topics	Assignments
wk1	1	4/4	Lecture 1 L1_Podcast	Introductory lecture and welcome to COGS138!	None this week	Assigned: Readings/survey-quiz1, Assignment 0 assigned
wk1	2	4/6	Lecture 2 L2_Podcast	Programming, python, juypter notebooks Intro notebook Python intro notebook jupyter notebooks notebook python checkpoint notebook	--
wk2	3	4/11	Lecture 3 L3_Podcast	MNE, NLTK, EEG/MEG analysis	Previous week review, assignment 0/1, getting all the machinery working	Assigned: Reading 1 assigned Assigned: Lecture 3 - class survey/quiz
wk2	4	4/13	Lecture 4 L4_Podcast	MOCAP, PyMO, Eye tracking, Data science questions		DUE 4/15: Assignment 0 due Friday at 11:59pm PST
wk3	5	4/18	Lecture 5 L5_Podcast	Questions, LISC, BIDS, NWB, DANDI	Lectures, Reading 1, A1, BIDS, NWB, DANDI setup	Assignment 1 Assigned, Due Tues 4/25 at 11:59pm
wk3	6	4/20	Lecture 6 L6_Podcast	NWB, BIDS, DANDI, OpenNeuro, Git, Github, Version control		Reading 1 quiz Due Fri 4/28 at 11:59pm
wk4	7	4/25	Lecture 7 L7_Podcast	Data structures, wrangling, data cleaning (part 1)	previous week lecture review, Assignment 2 overview, LISC, group formation and signup
wk4	8	4/27	Lecture 8 L8_Podcast	More on data cleaning, Visualization review - choosing plot types, plot options, modules in python		Assigned: R2 due Fri 5/5 at 11:59pm Assigned: Lecture Quiz wk1-2 due Fri 5/5 at 11:59pm
wk5	9	5/2	Lecture 9 L9_Podcast	Outlier detection, data cleaning part 2, more on visualization of neural data, statistical data analysis	Lecture review, A2
wk5	10	5/4	Lecture 10 L10_Podcast example final project	Statistical neural data analysis part 2 Groups, main group project introduction Distributions.ipynb TestingDistributions.ipynb StatisticalComparisons.ipynb
wk6	11	5/9	Lecture 11 L11_Podcast	Relating statistics to neural data science, AC/DC, filtering theory (LP, HP, Notch, Bandpass), central tendency, variability, covariance, correlation	Previous week review, groups, reading 2 review	Due: R2 extended to Tuesday 5/9 at midnight Due: Lecture quiz extended to Tuesday 5/9 at midnight Due: A2 extended to 5/9 at midnight Assigned: In class survey/quiz (before) here due Friday at midnight Assigned: After class survey/quiz (after) here due Friday at midnight
wk6	12	5/11	Lecture 12 L12_Podcast	Time series, sampling, aliasing, filtering, signal processing continued, scientific visualization		Assigned: A3 due SUNDAY 5/21 at midnight (EXTENDED)
wk7	13	5/16	Lecture 13 L13_Podcast	Connectionist paradigms and modeling, single cell recording, high density recording, spike sorting, intro to neuropixels and other technologies
wk7	14	5/18	Lecture 14 L14_Podcast	Helping you maximize your learning in the class		Assigned: Project proposal Assigned: Previous project review Assigned: Mid-quarter and grade check-ins
wk8	15	5/23	Lecture 15 L15_Podcast	Class workshop, organization - remaining assignments, project plan and heterogeneous datasets
wk8	16	5/25	Lecture 16 L16_Podcast
wk9	17	5/30	Lecture 17 L17_Podcast	Single trial analysis, class workshop		Assigned: Project data checkpoint Due ~~Friday~~ Extended to Saturday 11:59pm Assigned: Lecture quiz week 5-6 Assigned: Reading R4 Due Sat 11:59pm
wk9	18	6/1	Lecture 18 L18_Podcast	Hypothesis development, neural data science question development, project discussion and workshop
wk10	19	6/6	Lecture 19 L19_Podcast
wk10	20	6/8	Lecture 20 L20_Podcast	Final lecture, course review, thesis, final project and checkpoint info, careers, where to go from here