Introduction to machine learning

About this course

The course combines presentations with coding exercises, focusing on how machine learning methods are implemented rather than only explaining their theory. Topics include data pre-processing, Python data frames, elements of natural language processing, regression and classification, random forests, boosted decision trees, neural networks, convolutional neural networks and k-means clustering. Learners also examine loss functions, optimisation, model variables and hyperparameters. The course uses mainly word- and number-based data, with brief coverage of image processing. Each session addresses a different area, followed by homework for further exploration and a larger project later in the course.

What you'll learn

• Pre-process data using common techniques such as handling missing values and encoding variables
• Program simple machine learning algorithms in Python, including random forests, boosted decision trees, neural networks and k-means clustering
• Choose variables and adjust hyperparameters using informed judgement
• Compare common machine learning methods and identify when they may be appropriate
• Explore further machine learning topics in an informed way

Is this course right for you?

The course is intended for learners with programming experience but no previous machine learning experience. Participants should be comfortable with Python, R or a similar language, including for-loops and if-statements, and with using a computer. The curriculum is described as high-paced and includes homework after each session plus a larger project.

• Previous programming study or equivalent experience is required
• Mathematical understanding may be useful but is not necessary
• Learners unable to complete homework can still attend, though some learning outcomes may be missed

Before you go

• Learners may bring their own laptop if they prefer.
• Homework is set after each session, with a larger project assigned after the third session.
• The course may require use of a personal third-party account or creation of an account for course purposes.
• Those attending the full course receive an electronic City Lit certificate of attendance.