Introduction to Scientific Computing for AI - Module

This module will provide an introduction to the core mathematics and core programming skills required in machine learning. On the successful completion of this module participants will be able to:

Use Python to implement standard programming constructs.

Understand the use of Calculus, Linear Algebra and Probability Theory in machine learning applications

Apply Python to simple machine learning models and data visualisations.

Award: University Certificate of Study

Subjects taught

Introduction to Scientific Computing for AI CE4021

Using a number of E-tivities you will hone your Python coding skills as well as your knowledge and skills in Calculus, Linear Algebra and Probability Theory as the three core areas of mathematics that underpin machine learning.

Entry requirements

This module is suitable for applicants with previous exposure to mathematics and computer programming languages.

Successful completion of this module does not automatically qualify you for entry into a further award. All programme applicants must meet the entry requirements listed if applying for a further award.

Application dates

Please ensure you enter the Module Code below when applying for this MicroCred. Applications without this cannot be processed. You may apply for more than one MicroCred under the same application.


7 weeks part-time.

Enrolment dates

Next Intake: Autumn 2024

Post Course Info

This micro-credential represents a single module within a larger further award (eg. Certificate, Diploma, Masters). By taking this micro-credential you may be eligible to apply for a credit exemption should you progress to study for a further award. The programmes associated with this MicroCred are:

Professional Diploma in Artificial Intelligence for Computer Vision
Professional Diploma in Computer Vision Systems
Machine Learning for Finance - MSc (Online)
Artificial Intelligence - MSc (Online)

More details
  • Qualifications


  • Attendance type

    Part time

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