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Syllabus

Week 1: Python

Day 1

Monday, June 24th

Morning Session Topics (L1)

  • Introduction
  • Why take this course
  • Course Objectives
  • Review the Syllabus
  • Ice Breaker

Afternoon Session Topics (L1)

  • Introduction to Google Colab
  • Introduction to 'A Byte of Python'
  • A Byte of Python - Python Basics
  • Hello World Exercise
  • A Byte of Python - Operators and Expressions
  • Simple Calculator Exercise

Class Exercise (L1)

  • Set up your Google Colab environment
  • Hello World Exercise
  • Simple Calculator Exercise

Homework

Day 2

Tuesday, June 25th

Morning Session Topics (L1)

  • A Brief History of Programming
  • A Byte of Python - Control Flow
  • Exercise: The Guessing Game

Afternoon Session Topics (L1)

  • A Byte of Python - Functions
  • Exercise: The Fibonacci Sequence
  • A Brief History of Text Adventure Games
  • Build a Text Adventure Game

Class Exercise (L1)

  • Exercise: The Guessing Game
  • Exercise: The Fibonacci Sequence
  • Build a Text Adventure Game

Homework

Day 3

Wednesday, June 26th

Morning Session Topics (L1)

  • What is Data?
  • A Byte of Python - Data Structures
  • Exercise: Adding Data to Your Adventure Game

Afternoon Session Topics (L1)

  • A Byte of Python - Data Structures
  • Exercise: Loading Your First CSV File

Class Exercise (L1)

  • Exercise: Add data structures to your adventure game
  • Exercise: Loading Your First CSV File

Homework

Day 4

Thursday, June 27th

Morning Session Topics (L2)

  • A Byte of Python - Object Oriented Programming
  • Exercise: Working with Classes and Objects
  • A Byte of Python - Modules
  • Exercise: Calculating your 10,000th Day Alive

Afternoon Session Topics (L1, L2)

  • Some History about Tabular Data
  • Introduction to Pandas and DataFrames
  • Exercise: Upgrade your CSV program to use Pandas

Class Exercise (L2)

  • Exercise: Working with Classes and Objects
  • Exercise: Calculating your 10,000th Day Alive
  • Exercise: Upgrade your CSV program to use Pandas

Homework

Day 5

Friday, June 28th

Morning Session Topics (L2, L3)

  • The Prevalence of Tabular Data
  • Data Exploration with Pandas
  • Exercise: Exploring a Novel Dataset

Afternoon Session Topics (L2, L3)

  • Pandas - Reshaping Data
  • Pandas - Joining Data
  • Exercise: Working with Multiple Datasets

Class Exercise (L2, L3)

  • Exercise: Exploring a Novel Dataset
  • Exercise: Working with Multiple Datasets

Homework

  • Review the Pandas Tutorial
  • Finish: Exercises from Day 5
  • Enjoy your weekend!

Week 2: Data Science

Day 1

Monday, July 1st

Morning Session Topics (L2)

  • A Brief History of Data Science
  • What is a Model?
  • 'Weapons of Math Destruction'
  • Exercise: Finding Correlations in Housing Data

Afternoon Session Topics (L2)

`- Data Formats - A detour into the World Wide Web - Exercise: Scraping Data from the Web

Class Exercise (L2)

  • Exercise: Finding Correlations in Housing Data
  • Exercise: Scraping Data from the Web

Homework

  • Finish: Exercises from Day 1

Day 2

Tuesday, July 2nd

Morning Session Topics (L4)

  • Introduction to Data Visualization
  • A Tour of Data Visualizations

Afternoon Session Topics (L4)

  • What makes a good visualization?
  • Introduction to MatPlotLib and Seaborn
  • Exercise: Plotting Housing Data Correlations
Class Exercise (L4)
  • Exercise: Plotting Housing Data Correlations

Homework

Day 3

Wednesday, July 3rd

Morning Session Topics (L3, L4)

  • Introduction to Time Series Data
  • Introduction to SciKit Learn
  • Linear Regressions with SciKit Learn
  • Exercise: Predicting Airline Ridership

Afternoon Session Topics (L3, L4)

  • Feature scaling
  • Time Series in Industries (Manufacturing-focus, TBD guest speaker)
  • Exercise: Predicting The Stock Market

Class Exercise (L4)

  • Exercise: Predicting Airline Ridership
  • Exercise: Predicting The Stock Market

Homework

  • Finish: Exercises from Day 3
  • Review the SciKit Learn documentation
  • Enjoy your day off!

Day 4

Thursday, July 4th * Fourth of July, no class.

Day 5

Friday, July 5th

Morning Session Topics (L3, L4)

  • Introduction to Natural Language Processing (NLP)
  • Text Preprocessing Techniques
  • Exercise: Sentiment Analysis of Music Lyrics

Afternoon Session Topics (L3, L4)

  • Text Preprocessing Techniques (continued)
  • Markov chains and N-grams
  • Term-Frequency Inverse Document Frequency (TFIDF)
  • Exercise: Use TFIDF to Separating Music by Artist

Class Exercise (L3, L4)

  • Exercise: Sentiment Analysis of Music Lyrics
  • Exercise: Use TFIDF to Separating Music by Artist

Homework

  • Finish: Exercises from Day 5
  • Enjoy your weekend!

Week 3: Machine Learning

Day 1

Monday, July 8th

Morning Session Topics (L5)

  • What is Machine Learning?
  • Supervised Learning: Overview and Applications
  • Training and Scoring
  • Exercise: Linear Regressions Revisited

Afternoon Session Topics (L5)

  • Train Test Split
  • Decision Trees
  • Logistical Regressions
  • Model Evaluation Techniques
  • Exercise: Decision Trees

Class Exercise (L5)

  • Exercise: Linear Regressions Revisited
  • Exercise: Decision Trees

Homework

  • Finish: Exercises from Day 1

Day 2

Tuesday, July 9th

Morning Session Topics (L5)

  • Unsupervised Machine Learning
  • Clustering
  • Anomaly detection
  • Principal Component Analysis (PCA)

Afternoon Session Topics (L5)

  • Ensemble Learning
  • Random Forests
  • Exercise: Random Forests

Class Exercise (L5)

  • Exercise: Random Forests

Homework

  • Finish: Exercises from Day 2

Day 3

Wednesday, July 10th

Morning Session Topics (L6)

  • Introduction to and history of Neural Networks
  • Watch the first 3Blue1Brown video on Neural Networks
  • Basics of Deep Learning
  • Using Pytorch
  • Exercise: Using Pytorch to Classify Handwritten Digits

Afternoon Session Topics (L6)

  • Shapes of networks
  • Convolutional Neural Networks (CNNs)
  • Categorizing images with Neural Networks
  • Exercise: Using Pytorch to Classify Images

Class Exercise (L6)

  • Exercise: Using Pytorch to Classify Handwritten Digits
  • Exercise: Using Pytorch to Classify Images

Homework

Day 4

Thursday, July 11th

Morning Session Topics (L6)

  • Recurrent Neural Networks (RNNs)
  • Word2Vec
  • Exercise: Generating Word2Vec Artwork

Afternoon Session Topics (L6)

  • Transformers
  • "Attention is All You Need"
  • Exercise: Revisiting Your Text Adventure Game with dolly-v2-3b LLM

Class Exercise (L6)

  • Exercise: Generating Word2Vec Artwork
  • Exercise: Revisiting Your Text Adventure Game with dolly-v2-3b LLM

Homework

  • Finish: Exercises from Day 4

Day 5

Friday, July 12th

Morning Session Topics (L6)

  • Transfer Learning
  • Latent Diffusion Models
  • Exercise: Discuss Strategies for Safely Using LLMs in your College Experience

Afternoon Session Topics (L6)

  • Ethics and Responsibility
  • Careers in Data Science and Machine Learning
  • Revisiting why we're here
  • Q&A Session / Open Class Discussion