🧠 Explore cutting-edge techniques in machine learning with this specialized curriculum.

Course Overview

This course dives into advanced topics such as:

  • Deep Learning Architectures 🤖
  • Optimization Algorithms 📊
  • Reinforcement Learning 🔄
  • Natural Language Processing (NLP) 📖

For foundational concepts, check out our Machine Learning Basics module.

Key Modules

  1. Neural Network Design

    Neural_Network_Design
    - Multi-layer perceptrons - Convolutional and recurrent networks

  2. Advanced Optimization

    Optimization_Techniques
    - Stochastic gradient descent variants - Second-order methods (e.g., Adam, RMSProp)

  3. Ethical AI & Bias Mitigation
    📌 Critical discussions on fairness, transparency, and responsible AI deployment.

Practical Projects

  • Build a deep learning model for image classification
  • Implement reinforcement learning in a simulated environment
  • Analyze NLP pipelines for sentiment detection

For hands-on practice, explore our AI Lab resources.

Recommended Tools

  • TensorFlow 📦
  • PyTorch 📦
  • Scikit-learn 📦
  • Jupyter Notebooks 📄
Click to expand additional resources - [Advanced ML Research Papers](/research/advanced_ml_papers) - [Case Studies Gallery](/case_studies)

Stay curious and keep coding! 🚀