Course Schedule

[Mon] No Class (Jan 23)

[Wed] Reproducibility 1 (Jan 25)

• Course Overview
• Hardware, OS, Interpreters

Watch: Lecture
Read: Syllabus
Slides: PDF

[Fri] Reproducibility 2 (Jan 27)

• versioning

Watch: Lecture
Slides: PDF
Read: Course Notes

[Mon] Reproducibility 3 (Jan 30)

• git commands
• branching and merging
• conflict resolution

Watch: Lecture (LEC001)
Watch: Lecture (LEC002)
Lecture notes: Lecture notes repository
Slides: PDF
Read: Course Notes (NB)
Lab: Week 2 Activities

[Wed] Performance 1 (Feb 1)

• check_output
• time
• identifying steps
• counting executed steps

Released: P1 (perf measurements)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)

[Fri] Performance 2 (Feb 3)

• complexity analysis
• big O notation
• worksheet practice

Lecture: attendance (requires wisc login)
Watch: Lecture
Worksheet: PDF
Read: Course Notes (NB)
Quiz (now due Sat, Feb 4th): week 1

[Mon] Performance 3 (Feb 6)

• large data
• generators

Lecture: attendance (requires wisc login)
Watch: Lecture
Read: Course Notes
Lab: Week 3 Activities

[Wed] OOP 1: Classes (Feb 8)

• attributes
• methods
• constructors

Optional Reading: Think Python 15, 16, and 17.1 - 17.5
Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)

[Fri] OOP 2: Special Methods (Feb 10)

• __str__, __repr__, _repr_html_
• __eq__, __lt__
• __len__, __getitem__
• __enter__, __exit__

Released: P2 (trees)
Optional Reading: Python Data Model
Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)
Quiz: week 2 and before (cumulative)

[Mon] OOP 3: Inheritance (Feb 13)

• method resolution order
• overriding methods
• calling overridden methods

Optional Reading: Think Python 18
Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)
Lab: Week 4 Activities

[Wed] Recursion (Feb 15)

• functions that return something
• functions that do something

Due: P1
Lecture: attendance (requires wisc login)
Watch: Lecture
Worksheet: PDF
Read: Course Notes (NB)

[Fri] Graphs and Tree Intro (Feb 17)

• types of graph
• graphviz

Lecture: attendance (requires wisc login)
Watch: Lecture
Read: Course Notes (NB)
Quiz: week 3 and before (cumulative)

[Mon] Trees 1 (Feb 20)

• trees
• binary trees
• binary search trees (BSTs)

Lecture: attendance (requires wisc login)
Watch: Lecture
Read: Course Notes (NB)
Lab: Week 5 Activities

[Wed] Trees 2 (Feb 22)

• BSTs: height, for sets+dicts
• depth-first search

Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)

[Fri] Graph Search 1 (Feb 24)

• breadth-first search
• stacks, queues, priority queues

Released: P3 (crawler)
Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)
Quiz: week 4 and before (cumulative)

[Mon] Graph Search 2 (Feb 27)

• deque (for queues)
• heapq (for priority queues)
• web intro

Lecture: attendance (requires wisc login)
Watch: Lecture
Read: Course Notes (NB)
Lab: Week 6 Activities

[Wed] Web 1: Selenium (Mar 1)

• finding elements, text
• polling
• screenshots
• clicking, typing

Due: P2
TRICKY PAGES
Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF

[Fri] Exam 1 (Mar 3)

• Regular exam: in class
• McBurney exam: 5:45 to 7:05 PM

[Mon] Web 2: Recursive Crawl (Mar 6)

• more tricky pages
• BFS for webpages

CRAWL PRACTICE
Lecture: attendance (requires wisc login)
Watch: Lecture
Read: Course Notes (NB)
Lab: Week 7 Activities

[Wed] Web 3: Flask (Mar 8)

• Internet overview
• flask
• headers, rate limiting (HTTP 429)

Lecture: attendance (requires wisc login)
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)

[Fri] Web 4: More Flask (Mar 10)

• robots.txt
• query strings
• decorators

Due: P3
Released: P4 (website)
Watch: Lecture
Quiz: week 6 and before (cumulative)

[Mon] Spring Break (Mar 13)

[Wed] Spring Break (Mar 15)

[Fri] Spring Break (Mar 17)

[Mon] Web 5: A/B testing (Mar 20)

• data collection
• significance

Read: The Morality of A/B Testing (TechCrunch article)
Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF
Lab: Week 9 Activities

[Wed] Web 6: Dashboards (Mar 22)

• dashboards
• POST
• CDFs

Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)

[Fri] Regex 1 (Mar 24)

• character classes
• repetition
• anchoring

Read: DS100 Ch 13
Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF
Quiz: week 8 and before (cumulative)

[Mon] Regex 2 (Mar 27)

• practice

Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)
Lab: Week 10 Activities

[Wed] Visualization 1 (Mar 29)

• matplotlib coordinate systems
• drawing custom lines/polygons

Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)

[Fri] Visualization 2 (Mar 31)

• geographic maps
• shapely
• coordinate reference systems

Due: P4
Released: P5 (trace analysis)
Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)
Quiz: week 9 and before (cumulative)

[Mon] Visualization 3 (Apr 3)

• shapefiles, GeoJSON
• DPI (dots per inch)
• geocoding

Lecture attendance: link provided in-person
Watch: Lecture
Lab: Week 11 Activities

[Wed] ML overview (Apr 5)

• regression, classification
• clustering, decomposition

Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF

[Fri] Exam 2 (Apr 7)

• Regular exam: in class
• McBurney exam: 5:45 to 7:05 PM

[Mon] Regression 1 (Apr 10)

• sklearn LinearRegression
• explained variance
• train/test split

Lecture attendance: link provided in-person
Watch: Lecture
Lab: Week 12 Activities

[Wed] Regression 2 (Apr 12)

• PolynomialFeatures
• OneHot Encoding
• Pipelines

Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF

[Fri] Linear Algebra 1 (Apr 14)

• numpy arrays
• numpy images
• multiplication

Due: P5
Released: P6 (land matrices and regression)
Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)
Quiz: week 11 and before (cumulative)

[Mon] Linear Algebra 2 (Apr 17)

• more multiplication
• fit with np.linalg.solve
• predict with np.dot
• column perspective

Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)
Lab: Week 13 Activities

[Wed] Linear Algebra 3 (Apr 19)

• column spaces
• projection matrices

Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)

[Fri] Classification 1 (Apr 21)

• LogisticRegression
• multiclass, proba
• decision boundaries
• standardization

Released: P7 (classification)
Lecture attendance: link provided in-person
Watch: Lecture
Quiz: week 12 and before (cumulative)

[Mon] Classification 2 (Apr 24)

• confusion matrices
• accuracy, precision, recall

Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF
Lab: Week 14 Activities

[Wed] Clustering 1 (Apr 26)

• KMeans
• AgglomerativeClustering
• fit, transform, "predict"

Due: P6
Lecture attendance: link provided in-person
Watch: Lecture

[Fri] Clustering 2 (Apr 28)

• AgglomerativeClustering
• linkage

Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF
Quiz: week 13 and before (cumulative)

[Mon] Decomposition (May 1)

• Principal Component Analysis (PCA)
• Feature Dimensionality Reduction
• Compressing Data

Lecture attendance: link provided in-person
Watch: Lecture
Read: Course Notes (NB)
Lab: Week 15 Activities

[Wed] Parallelism (May 3)

• threads vs. processes
• multiprocessing pools
• parallel map
• pytorch

Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF
Read: Course Notes (NB)

[Fri] Final review / Unsupervised Machine Learning Recap (May 5)

• wrapup Dendrograms
• when to use KMeans, AgglomerativeClustering, PCA

Due (HARD DEADLINE - No submissions accepted after today): P7
Final exam: Regular exam: Friday, May 12th 10:05AM - 12:05PM
Final exam: McBurney exam: Friday, May 12th 9:00AM - 1:00PM
Lecture attendance: link provided in-person
Watch: Lecture
Slides: PDF