Master of Science in Artificial Intelligence and Data Science

University of Hull

UK,England

 0 Shortlist

12 Months

Duration

CAD 15,000/year

Tuition Fee

CAD 0 FREE

Application Fee

Jan 2025

Apply Date

UK, England

Type: University

Location Type: Urban

Founded: 1954

Total Students: 16,000 +

Int. Students: 2,500 +

Campus Detail

Main Campus Address

Cottingham Rd, Hull HU6 7RX, United Kingdom

Master of Science in Artificial Intelligence and Data Science

Program Overview

Understanding how to analyse, validate and interpret it to inform decision making are key skills in just about every walk of life. Nationally, there is a widely recognised shortage of qualified Artificial Intelligence (AI) and data scientists to meet the needs of industry.

This course is will equip you with the skills and professional insight you need to launch a career in this fast-growing sector. The programme is aimed at STEM (science, technology, engineering and mathematics) and non-STEM graduates, who want to develop their digital skills. It’s also suitable for people who are looking to upskill and improve their career prospects.You will learn Python coding, so experience in programming is not required.

You’ll cover topics such as programming, statistics, machine learning, big data, data visualisation, computer vision and the ethical and legal responsibilities of using data. Learning is delivered online and on-campus through a series of bespoke taught modules. In the third semester, you will do an academic dissertation or an industrial placement, where you will apply your knowledge to real-world problems, using data science and AI solutions. The University has teamed up with a range of employers to offer internship opportunities to students.

At the end of the course, graduates will have developed key competencies in AI and data science, including programming, data visualisation, problem-solving and data interpretation.

You will be able to apply AI and data science techniques to real-world problems; critically evaluate AI and data science methodologies; plan, design and carry out empirical research, and interpret, present and communicate the outcomes of data science and AI solutions.