Tools in Data Science

Week 0: Bridge Course

Overview
Accounts and Access
System Requirements
Linux / WSL / Terminal Setup
Shell Basics
VS Code Installation
VS Code Extensions
Python + UV Setup
Git + GitHub Setup
Browser and HTTP Basics
AI Learning Rules

Week 1: Development & Tooling

Overview
Coding environment setup
VS Code Workflow
UV
Bash Scripting
Git & GitHub
AI-Assisted Debugging
SQLite
HTTP Clients
Requestly
Data Formats
GitHub Pages
LaTeX / Pandoc

Lab 1: Publish a library to PyPI Lab 2: Publish a UV CLI tool Lab 3: Bash Automation

Week 2: APIs & Data Retrieval

Overview
API Fundamentals
FastAPI Basics
Streamlit / Gradio Basics
CORS & Input Validation
Authentication Basics
Config Management
Data Retrieval Strategy
Google Search Operators / Dorking
Public Dataset Portals
Deployment Platforms
Logging & Testing
Simple Monitoring
Cloudflare Tunnels
Simple Caching

Lab 1: Deploy a FastAPI App Lab 2: Retrieve Hidden Data

Week 3: AI & LLM Engineering

Overview
AI Literacy
LLM Basics
Good Prompt Engineering
Prompt Patterns
Prompt Iteration
Token & Cost Control
Human-First then AI-Assisted Work
Context Engineering
Open-Source LLMs
LLM CLI Tools
AI Coding Assistants
Spec-Driven Development
Pydantic & Structured Output
Multimodal Inputs
Embeddings Basics
Evaluation Basics
LLM Failure Modes

Project 1

Week 4: Embedding & Practical RAG

Overview
Why RAG
Keyword Search
Embeddings for Search
Chunking Strategies
Vector Stores
Retrieval Pipeline
Hybrid Search Basics
Reranking Basics
Grounding & Citations
RAG Evaluation
RAG Failure Modes
Contextual Retrieval

Week 5: AI Coding Agents & Automation

Overview
Agent Fundamentals
Supervised Agent Use
Context Files for Agents
Function / Tool Calling
Coding Agent Workflow
Agent Skills
Agent Hooks
Antigravity / Agent-First IDEs
Browser Automation
Chrome CDP Basics
Data Tools for Agents
MCP Basics
LangGraph Basics
Agent Memory Basics
Agent Evaluation
Agent Safety

Week 6: Web Scraping & Data Processing

Overview
Responsible Scraping
BeautifulSoup
Playwright & Selenium
Crawl4AI / Firecrawl Overview
GitHub Actions Cron Basics
Document Parsing
DuckDB + Parquet
Vision Models for Extraction
Image Generation & Editing
Image Processing Basics
Audio AI
Video AI
Multimodal Prompting
Data Provenance
Data Quality Checks

ROE
Project 2

Week 7: AI Security & Cloud Deployment

Overview
CI/CD with GitHub Actions
Pipeline Security
Secrets Management
Cloud Infrastructure Basics
Simple Deployment Review
OWASP Web Security Basics
LLM Security - Offensive
LLM Safety - Defensive
OWASP LLM Top 10 Basics
Agent Security
Evaluation Sets
Logging & Observability for AI Apps
Cost Control
Digital Provenance
Incident Response Basics
AI Risk Review & Responsible Notes

Week 8: Portfolio, MLOps Lite & Future Readiness

Overview
Choosing the Right AI Strategy
When Not to Fine-Tune / Train Models
Model Selection
Fine-Tuning Basics
MLOps Lite
Model Evaluation
Dataset and Prompt Versioning
Model Publishing Basics
Hugging Face Basics
Project Polish
Demo Skills
Career Readiness
Future Readiness
Final Demo Day

Project 3
Live Sessions
End Term
Resources

Fine Tuning Basics

Fine-Tuning Basics#

Status: Draft scaffold.

Placeholder page for the May 2026 term. Replace with the final lesson content.

Part of Week 8: Portfolio, MLOps Lite & Future Readiness .

Model Selection Mlops Lite