MSc Big Data Technologies

The MSc in Big Data Technologies at GCU London provides advanced knowledge in big-data engineering, cloud computing, machine learning, IoT and analytics. It suits graduates from computing, engineering, mathematics or related fields who want careers as data engineers, data scientists, BI analysts, cloud specialists or big-data architects.

Curriculum Structure (Full-time, 1 Year)

Year of Study

Students begin with Big Data Landscape, Software Development for Data Science, Artificial Intelligence and Machine Learning, and Data Ethics and Research Methods. These modules introduce large-scale data ecosystems, build strong programming and data-science skills, teach core AI and ML models, and establish ethical and research principles for working with data.

In the next stage, they study Cloud Computing and Web Services, Internet of Things, Big Data Platforms, and Data Visualisation. Here they learn to design cloud-based data solutions, integrate IoT-generated data, use scalable big-data storage and processing platforms, and communicate insights through meaningful visualisation techniques.

The programme concludes with an MSc Dissertation, where students complete an applied or research project that integrates big-data engineering, AI/ML, cloud systems and analytics to solve a real-world challenge.

Focus areas: “Big-data engineering, cloud computing, AI and machine learning, IoT systems, scalable data platforms, data visualisation, applied data-science project”

Learning outcomes: “Program for data science; design scalable big-data pipelines; apply ML algorithms; deploy cloud and IoT data solutions; visualise and interpret large datasets; complete an independent big-data project.”

Professional alignment (accreditation): Accredited by BCS, The Chartered Institute for IT, aligning with professional expectations in data engineering, analytics and cloud technologies.

Reputation (employability rankings): The programme is industry-focused and prepares graduates for high-demand roles in data engineering, big-data architecture, analytics, and cloud-based systems across sectors such as finance, technology, healthcare and retail.