AI Sprint Learning Journey - Complete Progress Tracker
AI Sprint Learning Journey - Progress Tracker
Welcome to my comprehensive AI learning journey. This page serves as the central hub for tracking all progress through the 4-week intensive AI sprint.
Learning Timeline Overview
Week 1: Machine Learning Fundamentals & Data Processing
- Day 1: Environment Setup & Data Processing - August 11, 2025
- Day 2: Data Analysis & Preprocessing - August 12, 2025
- Day 3: Logistic Regression Implementation - August 13, 2025
- Day 4: sklearn Pipeline & Cross-validation - August 14, 2025
- Day 5: End-to-End Project - August 15, 2025
Week 1 Progress: 5/5 days completed (100%)
Week 2: PyTorch Introduction (CV/NLP)
- Day 1: Tensor & Autograd Basics - August 16, 2025
- Day 2: DataLoader & Transforms - August 17, 2025
- Day 3: MLP/CNN Training Loop - August 18, 2025
- Day 4: Regularization Techniques - August 19, 2025
- Day 5: Hyperparameter Tuning - August 20, 2025
Week 2 Progress: 0/5 days completed (0%)
Week 3: NLP Fine-tuning (Small Models)
- Day 1: Text Processing & Tokenization - August 21, 2025
- Day 2: Transformers Training - August 22, 2025
- Day 3: Training Optimization - August 23, 2025
- Day 4: Error Analysis - August 24, 2025
- Day 5: Inference Script - August 25, 2025
Week 3 Progress: 0/5 days completed (0%)
Week 4: Mini LLM Practice (LoRA + Demo)
- Day 1: Model Selection & Data Prep - August 26, 2025
- Day 2: LoRA Training & Quantization - August 27, 2025
- Day 3: Gradio Demo Development - August 28, 2025
- Day 4: Performance Analysis - August 29, 2025
- Day 5: Documentation & Blog - August 30, 2025
Week 4 Progress: 0/5 days completed (0%)
Overall Progress Summary
Days Completed: 5 / 20 (25%)
Weeks Completed: 1 / 4 (25%)
Projects Finished: 1 / 4 (25%)
Skills Acquired: 10 / 20+ (50%)
Key Learning Objectives
Week 1 Goals
- [x] Environment setup and data processing
- [x] Linear/Logistic regression from scratch
- [x] sklearn pipeline implementation
- [x] End-to-end project completion
Week 2 Goals
- [ ] PyTorch fundamentals mastery
- [ ] MNIST/CIFAR10 model training
- [ ] Training loop optimization
- [ ] Model evaluation and tuning
Week 3 Goals
- [ ] NLP fine-tuning techniques
- [ ] Transformer model training
- [ ] LoRA implementation
- [ ] Inference script development
Week 4 Goals
- [ ] LLM instruction fine-tuning
- [ ] Gradio web interface
- [ ] Performance optimization
- [ ] Project documentation
Quick Navigation
Latest Updates
Learning Resources
Progress Visualization
Week 1: ████████████████████ 100% (5/5 days)
Week 2: ░░░░░░░░░░ 0% (0/5 days)
Week 3: ░░░░░░░░░░ 0% (0/5 days)
Week 4: ░░░░░░░░░░ 0% (0/5 days)
Overall: ████████████████████ 25% (5/20 days)
Milestone Celebrations
- Day 1 Complete: Environment setup and data processing mastered
- Day 2 Complete: Data analysis and preprocessing mastered
- Day 3 Complete: Logistic regression from scratch implemented
- Day 4 Complete: Hyperparameter optimization and cross-validation mastered
- Day 5 Complete: Deep result analysis and model insights completed
- Week 1 Complete: All 5 days finished successfully!
- Sprint Target: Complete by August 30, 2025
Learning Insights
Each day builds upon the previous, creating a comprehensive learning journey. The structured approach ensures steady progress while maintaining quality and depth of understanding.
This progress tracker is updated daily as I complete each learning session. Follow along on this exciting AI learning journey.