Data Science Bootcamp
Last updated: June 2026
Source org: ga-curriculum
How to Use This Repo
Each module below is a separate repo in the ga-curriculum org. You have two ways to work with it:
- GitHub Repo — clone this to work locally, submit homework, or browse the raw files (slides, datasets, starter code).
- GitHub Pages — a formatted, readable version of the lesson in your browser. Best for a quick read-through before or after class.
Content types:
| Type |
What it is |
| Lesson |
Instructor-led teaching content |
| Lab |
Guided, hands-on practice (usually same-day) |
| Project |
A larger, graded deliverable |
| Resource |
Supplementary material (solutions, references, instructor-only notes) |
A few lessons are delivered as a Slide Deck instead of a repo — those are marked accordingly and have no Pages/Repo link.
Quick Links
Unit 1
Python Foundations
SQL
| Module |
Type |
GitHub Repo |
GitHub Pages |
| SQL I - Introduction to Queries and BigQuery |
Lesson |
Repo |
Pages |
| SQL II - Grouping, Filtering, NULLs, and Joins |
Lesson |
Repo |
Pages |
| SQL III - Conditional Logic, Subqueries, CTEs and Window Functions |
Lesson |
Repo |
Pages |
| SQL IV - SQLite |
Lesson |
Slide Deck |
— |
Labs
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Lab - Python Trial I |
Lab |
Repo |
Pages |
| Lab - Python Trial II |
Lab |
Repo |
Pages |
| Lab - SQL |
Lab |
Repo |
Pages |
| Project 1 - Python Budget Tracker Application |
Project |
Repo |
Pages |
| Project 1 - Instructor View |
Resource |
Repo |
Pages |
Resources
| Module |
GitHub Repo |
GitHub Pages |
| Labs - Sample Solutions |
Repo |
Pages |
Exploratory Data Analysis
EDA Labs
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Lab - Titanic EDA |
Lab |
Repo |
Pages |
| Lab - Excel EDA |
Lab |
Repo |
Pages |
EDA Projects
Projects
| Module |
GitHub Repo |
GitHub Pages |
| Project 2 - EDA |
Repo |
Pages |
Resources
| Module |
GitHub Repo |
GitHub Pages |
| Project 2 - EDA Sample Solution |
Repo |
Pages |
Unit 2
Machine Learning
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Probability |
Lesson |
Repo |
Pages |
| Linear Regression I |
Lesson |
Repo |
Pages |
| Linear Regression II |
Lesson |
Repo |
Pages |
| Regression Metrics |
Lesson |
Repo |
Pages |
| Model Generalizability: Bias/Variance Tradeoff and Holdout Techniques |
Lesson |
Repo |
Pages |
| Model Workflow |
Lesson |
Repo |
Pages |
| k-Nearest Neighbors |
Lesson |
Repo |
Pages |
| Logistic Regression |
Lesson |
Repo |
Pages |
| Classification Metrics |
Lesson |
Repo |
Pages |
| Imbalanced Data |
Lesson |
Repo |
Pages |
| Regularization |
Lesson |
Repo |
Pages |
| Grid Search and Pipelines |
Lesson |
Repo |
Pages |
| Model Interpretation / Explainability |
Lesson |
Repo |
Pages |
| Framing a Data Science Problem |
Lesson |
Repo |
Pages |
| Leveraging Gen AI as a Data Scientist |
Lesson |
Slide Deck |
— |
| Time Series I: EDA |
Lesson |
Repo |
Pages |
| Time Series II: Modeling |
Lesson |
Repo |
Pages |
| Time Series III: Extras (GLS, GARCH, and VAR Models) |
Lesson |
Repo |
Pages |
| Introduction to Simulation |
Lesson |
Slide Deck |
— |
| Decision Trees with CART |
Lesson |
Repo |
Pages |
| Bootstrapping, Bagging, and Random Forests |
Lesson |
Repo |
Pages |
| Boosting |
Lesson |
Repo |
Pages |
| Support Vector Machines (SVMs) |
Lesson |
Repo |
Pages |
| Gradient Descent |
Lesson |
Repo |
Pages |
| Intro to Clustering with K-Means |
Lesson |
Repo |
Pages |
| DBSCAN and Other Clustering Techniques |
Lesson |
Repo |
Pages |
| Principal Component Analysis (PCA) |
Lesson |
Repo |
Pages |
| Recommender Systems |
Lesson |
Repo |
Pages |
ML Labs
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Lab - Regression (Sacramento) |
Lab |
Repo |
Pages |
| Lab - Classification (Left Handedness) |
Lab |
Repo |
Pages |
| Lab: Supervised Learning Model Comparison |
Lab |
Repo |
Pages |
ML Projects
Projects
| Module |
GitHub Repo |
GitHub Pages |
| Project 3 |
Repo |
Pages |
Unit 3
Data Engineering
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Introduction to Data Engineering |
Lesson |
Repo |
Pages |
| Designing Databases: Data Modeling and Normalization |
Lesson |
Slide Deck |
— |
| Creating and Managing Data Pipelines (ETL and ELT) |
Lesson |
Slide Deck |
— |
| Data Orchestration and Processing Data (batch vs real time) |
Lesson |
Slide Deck |
— |
| Data Governance and Data Catalog |
Lesson |
Slide Deck |
— |
| Data Lakes and Warehouses |
Lesson |
Slide Deck |
— |
| Storing and Processing Data: Cloud-Based vs. Compute Engines (On-Prem) |
Lesson |
Slide Deck |
— |
| AI Model Deployment |
Lesson |
Repo |
Pages |
| MLOps Fundamentals |
Lesson |
Repo |
Pages |
Unit 4
Deep Learning
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Deep Learning: Introduction to Frameworks and Tools |
Lesson |
Repo |
Pages |
| Deep Learning: Building and Optimizing NNs with Pytorch |
Lesson |
Repo |
Pages |
| Deep Learning: Intro to Neural Nets Architectures |
Lesson |
Repo |
Pages |
Deep Learning Labs
| Module |
Type |
GitHub Repo |
GitHub Pages |
| Lab - Building and Optimizing a Feedforward Neural Network |
Lab |
Repo |
Pages |
| Lab - Image Classification with Transfer Learning |
Lab |
Repo |
Pages |
Deep Learning Projects
Projects
| Module |
GitHub Repo |
GitHub Pages |
| Project 4 - Deep Learning End to End Solution |
Repo |
Pages |
| Project 4 - Building an Image Classifier for Detecting Plant Diseases |
Repo |
Pages |
NLP & LLMs
| Module |
Type |
GitHub Repo |
GitHub Pages |
| NLP and LLMs: Foundations of Modern NLP Part 1 |
Lesson |
Repo |
Pages |
| NLP and LLMs: Foundations of Modern NLP Part 2 (Embeddings) |
Lesson |
Repo |
Pages |
| NLP and LLMs: NLP Pipelines |
Lesson |
Repo |
Pages |
| NLP and LLMs: Introduction to Transformers |
Lesson |
Repo |
Pages |
| NLP and LLMs: Evaluating NLP Models |
Lesson |
Repo |
Pages |
| NLP and LLMs: Fine-Tuning |
Lesson |
Repo |
Pages |
NLP Labs
| Module |
Type |
GitHub Repo |
GitHub Pages |
| NLP Lab: Build a Sentiment Analysis Classifier |
Lab |
Repo |
Pages |
| NLP Lab: Build a QA Pipeline for Financial Documents |
Lab |
Repo |
Pages |
Capstone
| Module |
GitHub Repo |
GitHub Pages |
| Capstone |
Repo |
Pages |
Getting Help
Stuck on a lesson or lab? Check the References section inside that module’s repo first, then reach out in your cohort’s Slack channel.