COURSE CURRICULUM

The Data Analytics module provides an advanced study of modern data analytics techniques, equipping students with the knowledge and practical skills required to solve complex, real-world data challenges across a range of industries. Building on core concepts in statistics and machine learning, the module explores advanced analytical methods including supervised and unsupervised learning, predictive analytics, clustering, time series forecasting, natural language processing (NLP), and deep learning. Students gain practical experience working with large and complex datasets while learning to design, develop, and implement complete end-to-end data analytics workflows using industry-standard technologies such as Python, R, TensorFlow, PyTorch, Spark, cloud computing platforms, and modern data pipeline orchestration frameworks. Throughout the module, emphasis is placed on selecting appropriate analytical techniques, evaluating model performance, ensuring model interpretability, and applying responsible artificial intelligence principles to support ethical and transparent decision-making. Students develop the ability to critically assess different analytical approaches and determine the most suitable methodologies for addressing diverse business, scientific, and organisational problems. Practical laboratory sessions and a comprehensive capstone project enable students to apply theoretical knowledge in realistic scenarios, strengthening their technical expertise, analytical thinking, and problem-solving capabilities while producing actionable insights that support evidence-based decision-making. The curriculum also explores the ethical implications of advanced analytics, including fairness, accountability, bias, transparency, and responsible AI practices, preparing students to develop trustworthy and sustainable data-driven solutions. By the end of the module, students will be able to critically evaluate advanced analytics and machine learning methods, design and implement robust data analytics pipelines, and communicate analytical findings effectively to technical and non-technical audiences. Worth 20 credits, this core module provides a comprehensive foundation in advanced data analytics, combining theoretical understanding with extensive hands-on experience to prepare graduates for professional roles in data science, artificial intelligence, business analytics, and research, where the ability to analyse complex data and deliver meaningful insights is essential for innovation, strategic planning, and organisational success.