Machine Learning Specialization

Machine Learning Specialization

Course 1: Introduction to Machine Learning

 

Week 1: Basics of Machine Learning

Video Lectures: Overview of machine learning, types of learning (supervised vs. unsupervised).

Readings: Introduction to machine learning concepts and algorithms.

Quiz: Basic concepts and definitions.

  

Week 2: Supervised Learning Techniques

Video Lectures: Regression, classification algorithms, and their applications.

Assignment: Implement and evaluate a regression model.

Discussion Forum: Share and discuss different supervised learning techniques.

  

Week 3: Model Evaluation and Improvement

Video Lectures: Techniques for evaluating and improving models (cross-validation, hyperparameter tuning).

Quiz: Model evaluation metrics.

Assignment: Optimize and evaluate a model on a dataset.

 

Course 2: Advanced Machine Learning Techniques

 

Week 4: Unsupervised Learning

Video Lectures: Clustering, dimensionality reduction techniques.

Assignment: Apply clustering algorithms to a dataset.

Peer Review: Evaluate and provide feedback on peers' clustering results.

  

Week 5: Ensemble Methods

Video Lectures: Techniques like bagging, boosting, and stacking.

Project: Build an ensemble model and compare its performance to individual models.

Discussion Forum: Discuss the effectiveness of different ensemble methods.

 

Week 6: Neural Networks and Deep Learning

Video Lectures: Introduction to neural networks, deep learning frameworks.

Project: Build and train a neural network model using a deep learning library.

Quiz: Fundamentals of neural networks and deep learning.

 

Course 3: Real-World Applications of Machine Learning

 

Week 7: Machine Learning in Industry

Video Lectures: Applications of machine learning in various industries (e.g., finance, healthcare).

Case Study: Analyze and discuss a real-world machine learning case study.

  

Week 8: Data Handling and Processing

Video Lectures: Data preprocessing, feature engineering.

Assignment: Process and prepare a dataset for machine learning.

  

Week 9: Advanced Topics and Trends

Video Lectures: Emerging trends in machine learning and AI.

Discussion Forum: Explore and debate future trends and technologies in machine learning.