Course Schedule

Tue: Reproducibility 1 (Jan 21)

• Course Overview
• Hardware, OS, Interpreters

Watch: Lecture
Watch: Recording
Slides: PDF
Assigned:

• Survey 1 (5:00 pm)

Thu: Reproducibility 2 (Jan 23)

• versioning
• git commands
• branching and merging
• conflict resolution

Watch : Lecture
Watch: Recording
Slides: PDF
Due:

Survey 1 (11:59:00 pm)

Tue: Performance 1 (Jan 28)

• check_output
• time
• identifying steps
• counting executed steps
• complexity analysis

Watch: Lecture
Watch: Recording
VM Setup: Video
Git Workflow: Video
Lecture notes: Code
Read: HTML1 (NB1), HTML2 (NB2)
Slides: PDF
Assigned:

• Lab 1 (8:00 am)
• Project 1 (5:00 pm)

Thu: Performance 2 (Jan 30)

• big O notation
• worksheet practice
• large data
• generators

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB)
Worksheet: Question, Answer
Assigned:

• Quiz 1 (5:00 pm)

Tue: OOP 1 (Feb 04)

Classes

• attributes
• methods
• constructors

Watch: Lecture
Watch: Recording
GitLab: Video
Lecture notes: Code
Read: HTML (NB)
Slides: PDF
Optional Reading: Think Python 15, 16, and 17.1 - 17.5
Assigned:

• Lab 2 (8:00 am)
• Project 2 (5:00 pm)

Due:

• Quiz 1 (11:59:00 pm)
• Project 1 (11:59:00 pm)

Thu: OOP 2 (Feb 06)

Special Methods

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

Inheritance

• method resolution order
• overriding methods
• calling overridden methods

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML1 (NB1), HTML2 (NB2)
Slides: PDF
Optional Reading: Python Data Model
Optional Reading: Think Python 18
Assigned:

• Quiz 2 (5:00 pm)

Tue: Recursion and Graphs (Feb 11)

Recursion

• functions that return something
• functions that do something

Graphs

• graphviz
• types of graph

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML1 (NB1), HTML2 (NB2)
Worksheet: Question, Answer
Interactive Exercises
Assigned:

• Lab 3 (8:00 am)
• Project 3 (5:00 pm)

Due:

• Quiz 2 (11:59:00 pm)
• Project 2 (11:59:00 pm)

Thu: Trees (Feb 13)

• trees
• binary trees
• binary search trees (BSTs)
• BSTs: height, for sets+dicts

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB)
Slides: PDF
Assigned:

• Quiz 3 (5:00 pm)

Grade Released: Project 1 (10:00 pm)

Tue: Graph Search 1 (Feb 18)

• depth-first search

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB)
Slides: PDF
Honorlock: Practice with Honorlock
Assigned:

• Lab 4 (8:00 am)

Due:

• Quiz 3 (11:59:00 pm)

Thu: Graph Search 2 (Feb 20)

• breadth-first search
• stacks, queues, priority queues
• deque (for queues)
• heapq (for priority queues)

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML1 (NB1), HTML2 (NB2)
Slides: PDF
Assigned:

• Quiz 4 (5:00 pm)

Grade Released: Project 2 (10:00 pm)

Tue: Web 1 (Feb 25)

Selenium

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

Recursive Crawl

• more tricky pages
• BFS for webpages

Watch: Lecture
Watch: Recording
Tricky Pages, Crawl Practice
Lecture notes: Code
Read: HTML1 (NB1), HTML2 (NB2)
Slides: PDF
Assigned:

• Lab 5 (8:00 am)

Due:

• Quiz 4 (11:59:00 pm)

Thu: Exam 1 (Honorlock) (Feb 27)

• Regular exam: during class time
• McBurney exam (with 1.5 x time): during class time
• McBurney exam (with > 1.5 x time): 5:45 pm to 7:15 pm

Assigned:

• Exam 1

Answers Released: Exam 1 (10:00 pm)

Tue: Web 2 (Mar 04)

Flask

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

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB)
Slides: PDF
Assigned:

• Lab 6 (8:00 am)
• Project 4 (5:00 pm)

Due:

• Project 3 (11:59:00 pm)

Thu: Web 3 (Mar 06)

Flask

• robots.txt
• query strings
• decorators

A/B testing

• data collection
• significance

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB), TechCrunch article
Slides: PDF
Assigned:

• Quiz 5 (5:00 pm)

Tue: Web 4 (Mar 11)

Dashboards

• dashboards
• POST
• CDFs

Watch: Lecture
Lecture notes: Code
Read: HTML (NB)
Assigned:

• Lab 7 (8:00 am)
• Project 5 (5:00 pm)

Due:

• Quiz 5 (11:59:00 pm)
• Project 4 (11:59:00 pm)

Thu: Regex (Mar 13)

• character classes
• repetition
• anchoring
• practice

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB), DS100 Ch 13
Slides: PDF
Assigned:

• Quiz 6 (5:00 pm)

Grade Released: Project 3 (10:00 pm)

Tue: Visualization 1 (Mar 18)

• matplotlib coordinate systems
• drawing custom lines/polygons
• coordinate reference systems

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB)
Assigned:

• Lab 8 (8:00 am)

Due:

• Quiz 6 (11:59:00 pm)

Thu: Visualization 2 (Mar 20)

• geographic maps
• shapely
• shapefiles, GeoJSON
• DPI (dots per inch)
• geocoding

Watch: Lecture
Watch: Recording
Lecture notes: Code
Read: HTML (NB)
Assigned:

• Quiz 7 (5:00 pm)

Grade Released: Project 4 (10:00 pm)

Tue: Spring Break (Mar 25)

Thu: Spring Break (Mar 27)

Tue: Regression 1 (Apr 01)

• Machine Learning (ML) overview
  • regression, classification
  • clustering, decomposition

• sklearn LinearRegression

Watch: Lecture
Watch: Recording
Lecture notes: Code
Assigned:

• Lab 9 (8:00 am)
• Project 6 (5:00 pm)

Due:

• Quiz 7 (11:59:00 pm)
• Project 5 (11:59:00 pm)

Thu: Regression 2 (Apr 03)

• explained variance
• train/test split
• PolynomialFeatures
• OneHot Encoding
• Pipelines

Watch: Lecture
Lecture notes: Code
Slides: PDF
Assigned:

• Quiz 8 (5:00 pm)

Tue: Linear Algebra (Apr 08)

• numpy arrays
• numpy images
• multiplication
• fit with np.linalg.solve
• predict with np.dot
• column perspective
• column spaces
• projection matrices

Watch: Lecture
Lecture notes: Code
Read: HTML1 (NB1), HTML2 (NB2), HTML3 (NB3)
Assigned:

• Lab 10 (8:00 am)

Due:

• Quiz 8 (11:59:00 pm)

Thu: Exam 2 (Honorlock) (Apr 10)

• Regular exam: during class time
• McBurney exam (with 1.5 x time): during class time
• McBurney exam (with > 1.5 x time): 5:45 pm to 7:15 pm

Assigned:

• Exam 2

Grade Released: Project 5 (10:00 pm)
Answers Released: Exam 2 (10:00 pm)

Tue: Classification 1 (Apr 15)

• LogisticRegression
• multiclass, proba
• decision boundaries

Watch: Lecture
Lecture notes: Code
Slides: PDF
Assigned:

• Lab 11 (8:00 am)
• Project 7 (11:59:00 pm)
• Survey 2 (5:00 pm)

Due:

• Project 6 (11:59:00 pm)

Thu: Classification 2 (Apr 17)

• standardization
• confusion matrices
• accuracy, precision, recall

Watch: Lecture
Lecture notes: Code
Slides: PDF
Assigned:

• Quiz 9 (5:00 pm)

Tue: Clustering (Apr 22)

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

Watch: Lecture
Lecture notes: Code
Slides: PDF
Assigned:

• Lab 12 (8:00 am)
• Project 8 (11:59:00 pm)

Due:

• Quiz 9 (11:59:00 pm)
• Project 7 (11:59:00 pm)

Thu: Decomposition (Apr 24)

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

Watch: Lecture
Lecture notes: Code
Read: HTML (NB)
Grade Released: Project 6 (10:00 pm)
Assigned:

• Quiz 10 (5:00 pm)

Tue: Unsupervised ML Recap (Apr 29)

• linkage
• wrapup Dendrograms
• when to use the following:
  • KMeans
  • AgglomerativeClustering
  • PCA

Watch: Lecture
Lecture notes: Code
Slides: PDF
Assigned:

• Lab 13 (8:00 am)

Due:

• Quiz 10 (11:59:00 pm)

Thu: Parallelism (May 01)

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

Watch : Lecture
Lecture notes: Code
Read: HTML (NB)
Slides: PDF
Due:

• Survey 2 (11:59:00 pm)
• Project 8 (due (hard deadline) on Saturday, May 03 at 11:59:00 pm)

Grade Released: Project 7 (10:00 pm) on May 03
Grade Released: Project 8 (10:00 pm) on May 04

Tue: No Class (May 06)

Tursday: Final Exam (Online Exam with Honorlock) (May 8)

• Regular exam: 5:05 pm - 7:05 pm
• McBurney exam: 4:05 pm - 8:05 pm
• Alternate exam: 4:05 pm - 6:05 pm

Assigned:

• Final Exam (5:05 pm - 7:05 pm)

Answers Released: Final exam (10:00 pm)