Artificial Intelligence and Applications

This module covers the main analytical skills and tools in the field of Artificial Intelligence (AI). It will also build on the foundations on how to properly communicate this information to the relevant audience. The students will be progressively guided through the world of AI starting from an introduction to AI and its core concepts of designing and enabling AI by means of different methods including machine learning and genetic programming. Students will embark on the real-world problems and learn how to apply AI algorithms using a variety of existing architectures and languages including Python. Additional key advanced concepts and research trends in the field of AI will also be presented as well as the basic needed principles to communicate clearly and effectively. A special attention will thus be paid to AI applications so that the students will able to apply the AI techniques on the variety of problems.

With a diversity of lectures and lab work, the students will be able to make informed decisions on the most suitable methods to analyse how to apply AI on specific problems and get hands-on experience on their application. They will also learn how to interpret the results and communicate their findings using the appropriate visualisation tools and techniques. An indicative outline of the topics that will be covered follows:

• Introduction to AI
• Methods for machine learning
• Data preparation
• Basic Analytics/Pre-processing/Classifications
• Neural networks and Deep neural networks
• Natural language processing
• Applications of AI

At the end of this module the student will be able to:

• Gain deep knowledge and comprehensive understanding of the main methods and tools available for AI, including the underlying theoretical concepts.
• Apply and evaluate different machine learning methods to real problems and make an informed decision on their suitability for specific situations.
• Design AI methodologies for specific problems including effective communication of main findings to relevant audiences, and critically appraise the results.

This is an SCQF Level 11 module and upon successful completion, participants will be awarded 20 credits.

 

Delivery 

This module will be delivered on Paisley campus. Timetable to be confirmed.

 

Course presenter

This module will be delivered by Professor Naeem Ramzan.

 

Funding

This course may be available on a fully funded basis to some delegates. Further details, including regarding eligibility, are available under Funding Support.

If you have any questions, please contact us at cpd@uws.ac.uk 

 

NOTE: This is a university module and upon approval of your application, you will be invited to register and then supported to complete enrolment. To enrol on the university system, the first step involves security set-up using the Microsoft Authenticator app; you will need to ensure that you have a compatible smartphone.

Further enrolment information is available at the Student Information Portal.

To access this module via the CPD route, individuals should be ordinarily resident in Scotland.