Machine Learning Learning Roadmap

Week	Topics	Projects	Notes
Week 1	Python basics (variables, loops, functions)	Exploratory Data Analysis (Titanic dataset)	Add Note
Week 2	Pandas, NumPy, Matplotlib	EDA on Iris dataset	Add Note
Week 3	Git/GitHub basics	Version control for projects	Add Note
Week 4	Visualization with Seaborn	EDA on Boston Housing dataset	Add Note
Week 5	Linear Algebra Intuition	Matrix operations practice	Add Note
Week 6	Probability & Distributions	Spam classifier with Naive Bayes	Add Note
Week 7	Intro to ML: Supervised vs. Unsupervised	Train linear regression model	Add Note
Week 8	Model Evaluation Metrics	Evaluate spam classifier	Add Note
Week 9	Decision Trees & Random Forests	Train on Mall Customer dataset	Add Note
Week 10	Hyperparameter Tuning	Optimize Random Forest model	Add Note
Week 11	Neural Networks Basics	Perceptrons & activation functions	Add Note
Week 12	TensorFlow/PyTorch Basics	Build simple neural network	Add Note
Week 13	CNNs for Image Classification	Train on Plant Seedlings dataset	Add Note
Week 14	Transfer Learning (ResNet, MobileNet)	Improve crop disease detector	Add Note
Week 15	Flask API Basics	Deploy model locally	Add Note
Week 16	Docker & Containerization	Containerize Flask app	Add Note
Week 17	Cloud Deployment (AWS SageMaker)	Deploy model on SageMaker	Add Note
Week 18	MLOps & Model Monitoring	Track model performance	Add Note
Week 19	Generative AI (Diffusion Models)	Explore Stable Diffusion	Add Note
Week 20	LLMs & Prompt Engineering	Build chatbot with HuggingFace	Add Note
Week 21	Resume & Portfolio Building	Highlight 6 projects	Add Note
Week 22	Interview Prep (System Design)	Practice ML system design	Add Note
Week 23	Networking & LinkedIn Posts	Share projects on LinkedIn	Add Note
Week 24	Capstone Project: Waste Sorting App	Deploy with Flask/Docker	Add Note