Welcome to the Advanced Machine Learning course! This comprehensive course covers the latest advancements in machine learning, providing you with the knowledge and skills to tackle complex data challenges.

Course Overview

  • Duration: 12 weeks
  • Format: Online, self-paced
  • Prerequisites: Basic knowledge of Python and statistics

Course Content

  • Week 1: Introduction to Machine Learning

    • Understanding machine learning concepts
    • Types of machine learning algorithms

  • Week 2: Supervised Learning

    • Linear regression
    • Logistic regression
    • Decision trees

  • Week 3: Unsupervised Learning

    • Clustering
    • Dimensionality reduction

  • Week 4: Deep Learning

    • Neural networks
    • Convolutional neural networks (CNNs)
    • Recurrent neural networks (RNNs)

  • Week 5: Reinforcement Learning

    • Q-learning
    • Policy gradients

  • Week 6: Natural Language Processing

    • Text classification
    • Sentiment analysis

  • Week 7: Time Series Analysis

    • Autoregression models
    • Forecasting techniques

  • Week 8: Feature Engineering

    • Feature selection
    • Feature extraction

  • Week 9: Model Evaluation

    • Cross-validation
    • Performance metrics

  • Week 10: Hyperparameter Tuning

    • Grid search
    • Random search

  • Week 11: Model Deployment

    • REST APIs
    • Containerization

  • Week 12: Capstone Project

    • Apply your knowledge to a real-world problem

Learning Outcomes

  • Understand the principles of machine learning
  • Implement various machine learning algorithms
  • Evaluate and deploy machine learning models
  • Work with real-world datasets

Resources

Machine Learning