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Data Science and Artificial Intelligence (work experience) (Taught)

Course details
  • 1 Study option
  • Postgraduate
Course location
City Campus

Course summary

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.

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.

How to apply

Open days

Fees and funding

Choose a specific option to see funding information.

Course options

Sponsorship information

Scholarships, discounts and bursaries may be available to students who study this course.

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