Python for Machine Learning

Explore machine learning fundamentals and get started with popular algorithms. Get hands-on with a step-by-step tutorial on Python programming and how it's used to solve machine learning problems.

About this course

Machine learning enables rapid, automatic analysis of complex data in large volumes to deliver accurate results quickly. It can help organisations identify opportunities and avoid unknown risks.

This course provides participants with a fundamental background knowledge of the theory, approaches and history of machine learning and helps develop programming skills in Python for practical application to machine learning tasks and problems.

Course structure

The following content will be covered during this course:

• Overview of modern-day data analytics and machine learning

• Machine learning fundamentals

• Introduction to Python and basic operations

• Cluster analysis

• Performing clustering algorithms

• Classification and regression

• Programming regression models and logistic regression

• Time series modelling

• Inventory modelling with autoregressive integrated moving average and Hidden Markov Model

• Recommendation systems

• Collaborative filtering and non-negative matrix factorisation

• Conclusion, action planning and next steps.

Learning outcomes

By the end of the course you will be able to:

• Explain to a peer how machine learning algorithms can be applied and the background behind these algorithms

• Program in Python to solve common machine learning problems

• Apply machine learning related Python tools, including numpy and scikit-learn libraries.