AI Skills - Basic and Advanced Techniques in Machine Learning

Overview

This series of hands-on and interactive MOOCs will give learners a comprehensive overview of the basics machine learning topics. You will discover how machine learning classification and regression techniques allow you to make predictions for a category (classification) or for a number (regression) given data. This can be useful in predicting properties of objects (such as their weight or shape), or predicting qualities of people (customer satisfaction, etc.).You will learn about unsupervised learning techniques such as clustering and dimensionality reduction and how useful they are to make sense of large and/or high dimensional datasets.

We will also cover more advanced supervised learning techniques such as deep learning. This is useful to train neural networks to solve more complicated classification and regression tasks. Finally, you will deep dive into the reinforcement learning techniques and understand how to use them to train AI agents that interact with an environment.

This AI Skills - Basic and Advanced Techniques in Machine Learning Certificate in collaboration with Delft University of Technology (TU Delft) - DelftX is a Professional Certificate.

What you will learn

• Apply common operations (pre-processing, plotting, etc.) to datasets using Python.
• Explain the concept of supervised, semi-supervised, unsupervised machine learning and reinforcement learning.
• Explain how various supervised learning models work and recognize their limitations.
• Analyze which factors impact the performance of learning algorithms.
• Apply learning algorithms to datasets using Python and Scikit-learn and evaluate their performance.
• Optimize a machine learning pipeline using Python and Scikit-learn.
• Describe the main classes of clustering techniques.
• Implement k-means and hierarchical clustering.
• Motivate the need and choice of dimensionality reduction techniques.