Data Science and Artificial Intelligence (Taught)

Please check the Sheffield Hallam University website for the latest information.

Course summary

• Develop Data Science and Artificial Intelligence (AI) skills critical to sectors and businesses across the world

• Gain hands-on experience with real world data, technologies and industry projects

• Enhance employability readiness in rapidly growing Data Science and AI landscape across sectors

You will learn principles of Data Science and AI methodologies and frameworks that are critical to hybrid professionals. You will gain practical experience through project- based learning in creation of learning models for data and application of AI methods including machine learning and neural networks to learn from data along with ethics and privacy issues related to data when deploying AI technologies.

How you learn

The course builds upon your foundational programming knowledge by introducing technical concepts across keys areas of data science and artificial intelligence. This includes programming for data analytics, data manipulation and visualisation, machine learning foundations, neural networks, and their application to make decisions based on data.

The ethics, security, privacy, and AI-bias in data, is considered in the course alongside the fundamental data analytics and AI technologies and approaches to foster a responsible approach to their use and applications.

To support this, there is a range of ways in which we help students with their learning and ongoing formative feedback:

• lectures

• tutorials and seminars

• regular feedback

• laboratory sessions

• real-world problem and practical activity-based sessions and assessment

• group and individual project work

• academic advisors

• supervisor support & guidance

• acting as mentors for new students

Applied learning
Work Experience

This course has a work experience route that offers a placement in industry of up to 12 months. For further information, please see MSc Data Science and Artificial Intelligence (Work Experience)

Live Projects

The course maintains strong links with the data analytics and AI industry, ensuring that the curriculum content remains relevant and aligned with industry requirements. Industry partners and collaborations across local and national research centres include Sheffield Hallam’s Advance Wellbeing Research Centre, Sheffield Robotics, Advanced Manufacturing Research Centre, AstraZeneca, and the British Machine Vision Association. Collaborations with domain experts provides students with exposure to cutting-edge technologies and real-world applications.

This collaboration facilitates live projects, where students work on real-world challenges in data science and application of AI to data analysis. These projects encourage technical and professional skills including creativity, critical thinking, collaboration, communication and leadership that are essential for industry employment. The aim is to mirror the complexity of scenarios encountered in the professional realm.

Networking opportunities

Networking events will also be used to connect students with industrial professionals. Building these connections enhances students' understanding of the AI landscape, opening doors to mentorship, internships, and potential employment opportunities. Students will have opportunities to interact with our MSc Big Data Analytics students and MSc Artificial Intelligence students, as well as benefit from attending our AI Festival, which brings together different cohorts for an enriching day filled with presentations, networking opportunities, and celebrations of completed projects. The events also include themed competitions, allowing them to showcase their skills and knowledge in AI, thereby promoting innovation and development in this rapidly evolving field.

Important notice: The structure of this course is periodically reviewed and enhanced to provide the best possible learning experience for our students and ensure ongoing compliance with any professional, statutory and regulatory body standards. Module structure, content, delivery and assessment may change, but we expect the focus of the course and the learning outcomes to remain as described. Following any changes, updated module information will be published on our website.

Module and assessment information for future years is displayed as currently validated and may be liable to change. When selecting electives, your choices will be subject to the core requirements of the course. As a result, selections may be limited to a choice between one of two or more specified electives in some instances.

Modules studied may differ depending on when you start your course.

Compulsory modules

Modules

Advanced Artificial Intelligence Projects In Data Science
Artificial Intelligence Seminar Series
Computing Research Project
Foundations Of Data Science For Machine Learning
Introduction To Programming For Big Data
Research Skills For Computing

Coursework