60-day challenge
Artificial Intelligence
Build with models, agents and data, one task a day for 60 days.
- Python
- LLMs
- RAG
- Agents
- Evaluation
How it works
Start any day. Go at your own pace.
- 01
A task a day
Each day opens once the one before is submitted: a scoped task that takes under an hour.
- 02
Build in public
Push the work to your GitHub repository and post about it on LinkedIn. Both links are your submission.
- 03
A quiz each week
A short multiple-choice quiz at the end of the week, marked straight away with the reasons.
- 04
Badges to share
First day, seven days, halfway and the finish, each a badge you can post.
By the end, you will
- Build and ship LLM-powered features end to end
- Design retrieval and agent workflows
- Evaluate and improve model quality
The 60 days
Every day, planned.
Week 1 · Days 1–7AI Foundations - From Pipelines to Your First Classifier
- Day 1What Does an AI System Actually Do?
- Day 2Your First Python AI Script
- Day 3Text is Data - Turning Words into Numbers
- Day 4Vectors - Teaching Meaning to Machines
- Day 5Build a Mini Search Engine
- Day 6What is Machine Learning? Build an Intuition
- Day 7Your First Classifier
Week 2 · Days 8–14Week 2
- Day 8How Machines Read Human Language
- Day 9Teaching AI Semantic Meaning Through Vectors
- Day 10Build Your First End-to-End NLP Pipeline
- Day 11Build Your First Document Retrieval System
- Day 12Chunking Strategies for Long Document Processing
- Day 13Understanding Embeddings as Semantic Coordinates
- Day 14Build a Semantic Search Engine
Week 3 · Days 15–21Week 3
- Day 15Build Your First RAG Pipeline
- Day 16Diagnosing RAG Failure Modes
- Day 17Improve RAG Precision with Metadata Filtering
- Day 18Why LLMs Hallucinate and How to Measure It
- Day 19Prompt Engineering for Reliable LLM Outputs
- Day 20Build a Working AI Knowledge Assistant
- Day 21What Makes AI Products Actually Good
Week 4 · Days 22–28Week 4
- Day 22Designing Production-Ready AI APIs
- Day 23Connect a Frontend to Your AI Backend
- Day 24Building Conversation Memory Systems
- Day 25AI System Architecture Review and Refactoring
- Day 26Introduction to AI Agents and the ReAct Pattern
- Day 27Structured Tool Calling with the OpenAI Functions API
- Day 28Multi-Step AI Workflows with State Management
Week 5 · Days 29–35Week 5
- Day 29Building AI Evaluation Systems
- Day 30Ship a Working AI Research Assistant
- Day 31How Production AI Systems Handle Scale
- Day 32Latency Optimisation for AI Pipelines
- Day 33Debugging AI Systems Systematically
- Day 34Prompt Injection and AI Safety Engineering
- Day 35Production Hardening and Reliability Engineering
Week 6 · Days 36–42Week 6
- Day 36Deploy Your AI Backend to the Cloud
- Day 37Deploy Your AI Frontend
- Day 38Collecting and Structuring Real User Feedback
- Day 39Iterate on Your AI Product Based on Evidence
- Day 40Mid-Program Demo Day and Portfolio Documentation
- Day 41Define Your AI Product Problem and Target User
- Day 42Design Your AI Product System Architecture
Week 7 · Days 43–49Week 7
- Day 43Build Your Knowledge Base and Data Ingestion Pipeline
- Day 44Define MVP Scope and Build the Core AI Loop
- Day 45Build the Backend Infrastructure for Your AI Product
- Day 46Integrate Advanced Retrieval into Your Product
- Day 47Prompt Engineering for Production Reliability
- Day 48Build Product-Specific Memory and Personalisation
- Day 49Frontend UX Sprint for Your AI Product
Week 8 · Days 50–56Week 8
- Day 50Evaluate Your AI Product with a Domain-Specific Eval Suite
- Day 51Handle Edge Cases and Build Failure Resilience
- Day 52Optimise Your Product for Speed and Cost
- Day 53Deploy Your AI Product to Production
- Day 54Collect and Analyse Real User Feedback
- Day 55Build Your AI Engineering Portfolio
- Day 56Technical Review and Final System Hardening
Week 9 · Days 57–60Week 9
- Day 57AI Engineering Interview Preparation
- Day 58Public Product Launch Day
- Day 59Community Showcase and Peer Review
- Day 60AI Engineer Graduation - Transformation Showcase