study-groups

Study Groups

Welcome to the Study Groups folder! 📚

How to Use This Folder

• Navigate to the october-cohort subfolder to access the current available tracks.
• Each curriculum file contains structured materials, including week-by-week topics, video tutorials, and hands-on projects.
• Follow the recommended weekly order for a guided learning experience.
• Complete the mini-projects and assignments to reinforce your learning.
• Participate in the capstone project to demonstrate your skills.ns curated materials for the various study groups within the Machine Learning Lagos community. Each subfolder focuses on a specific topic, offering resources that provide comprehensive learning paths and references for learners at all levels. Whether you’re a beginner or looking to deepen your expertise, these materials are designed to guide your learning journey.

Available Tracks

We currently offer two comprehensive 10-week study group tracks:

1. ML Basics (Beginners)

Description: A comprehensive 10-week curriculum perfect for beginners looking to build a strong foundation in Machine Learning. This track covers everything from mathematical foundations to real-world deployment.

Duration: 10 weeks

What You'll Learn:

• Weeks 1-2: ML Math Foundations (Linear Algebra & Calculus)
• Week 3: Python Libraries for ML (Pandas, NumPy, Matplotlib, Seaborn)
• Week 4: Introduction to Machine Learning (Supervised, Unsupervised, Evaluation Metrics)
• Week 5: Classic Supervised ML Algorithms (Logistic Regression, Decision Trees, Random Forests, SVM)
• Week 6: Unsupervised Learning (K-means, PCA, t-SNE)
• Week 7: Advanced ML Concepts (Hyperparameter Tuning, Ensemble Methods)
• Week 8: Model Deployment (Flask, FastAPI, Streamlit, Gradio)
• Week 9: Review & Capstone Preparation
• Week 10: Capstone Project & Presentations

Prerequisites: Basic programming knowledge; willingness to learn Python

Capstone Project: Build and deploy a complete ML solution including data cleaning, model training, and deployment

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2. Generative AI

Description: A hands-on 10-week curriculum designed to take you from Generative AI fundamentals to building production-ready applications. Learn to work with LLMs, image generation models, and build AI-powered applications.

Duration: 10 weeks

What You'll Learn:

• Weeks 1-2: Generative AI Foundations & LLM Architecture (Transformers, Tokenization)
• Weeks 3-4: Prompt Engineering & Working with AI APIs (OpenAI, Gemini, Anthropic)
• Weeks 5-6: Building AI Applications (Text Generation Apps, Hugging Face Models)
• Week 7: Image Generation & Multimodality (Stable Diffusion, DALL·E)
• Week 8: Retrieval-Augmented Generation (RAG, Vector Databases)
• Week 9: Focused Project Development
• Week 10: Capstone Project Showcase

Prerequisites:

• Strong proficiency in Python
• Software engineering fundamentals (Git, CLI)
• Experience with API requests
• Basic knowledge of Flask or FastAPI
• High-level understanding of ML/neural networks

Capstone Project: Build a complex, multi-faceted generative AI application (e.g., code review assistant, trip planner, marketing copy generator)

How to Use This Folder

• Navigate to the file of the track you’re interested in.
• Each subfolder contains structured materials, including Markdown notes, tutorials, and references.
• Follow the recommended order for a guided learning experience, or dive into specific topics of interest.

Contributing

We welcome contributions from the community! If you have additional resources, corrections, or insights to share:

• Fork this repository.
• Add your contribution to the relevant subfolder.
• Submit a pull request with a clear description of your changes.

Contact

For any questions or suggestions, feel free to reach out to the Machine Learning Lagos team via email or open an issue in this repository.

Happy Learning! 🎉