Data Science and Analytics BSc Honours

Program Overview

The program also offers a short-term work-based learning experience and the opportunity to complete a year in industry to gain practical experience and enhance employability.

Program Outline

Data Science and Analytics BSc Honours - University of Westminster

Degree Overview:

This BSc Honours program in Data Science and Analytics aims to equip students with a blend of analytical, technical, and presentation skills to transform data into valuable insights. The program recognizes the growing importance of data processing in a rapidly evolving global environment, driven by social networks and the Internet of Things. It addresses the increasing demand for professionals who can effectively process, understand, and present data to support evidence-based decision-making in various sectors, including businesses, governments, and research institutions. The program focuses on the fundamental principles and technologies underpinning mathematics, statistics, and computing, with a strong emphasis on data science and analytics skills and theories.

Outline:

Year 1 (Credit Level 4):

• Applied Mathematics: This module introduces fundamental mathematical concepts and techniques relevant to data science and analytics.
• Database Design and Implementation: Students learn the principles of database design, implementation, and management, including relational databases and SQL.
• Software Development: Students gain practical experience in software development, including programming languages, software design principles, and testing methodologies.

Year 2 (Credit Level 5):

• Business Analytics: This module explores the application of data analytics techniques to business problems, including market research, customer segmentation, and forecasting.
• Data Visualization and Communication: Students develop skills in creating effective data visualizations and communicating data insights to different audiences.
• Machine Learning and Data Mining: This module introduces machine learning algorithms and techniques for data mining, including supervised and unsupervised learning, classification, and clustering.
• Algorithms: Theory, Design and Implementation: This module explores the theory, design, and implementation of algorithms, including data structures, sorting, searching, and graph algorithms.
• Database Systems: This module delves deeper into database systems, including database management systems, transaction processing, and database security.

Placement Year:

• Students have the opportunity to gain practical work experience in a relevant industry setting, typically in roles related to data science and analytics.
• The University provides support and guidance in finding and securing placement opportunities through workshops and events organized by the Careers and Employability Service.

Year 3 (Credit Level 6):

• Data Science and Analytics Final Project: Students undertake a substantial research project, applying their knowledge and skills to address a real-world data science problem.
• Operational Research and Optimization: Students learn about optimization techniques and their application to real-world problems, including linear programming, network optimization, and simulation modeling.
• Applied AI: This module introduces the principles and applications of artificial intelligence, including machine learning, deep learning, and natural language processing.
• Customer Relationship and Change Management (CRM & CM) with Business Intelligence: This module examines the use of business intelligence tools and techniques for managing customer relationships and driving organizational change.
• Digital Marketing, Social Media and Web Analytics: Students learn about the use of data analytics in digital marketing, social media, and web analytics.

Assessment:

The program utilizes a variety of assessment methods, including:

• Written exams: End-of-semester exams assess students' understanding of key concepts and theories.
• Coursework: This includes essays, reports, in-class tests, portfolios, and dissertations, allowing students to demonstrate their analytical and problem-solving skills.
• Practical assessments: These may involve presentations, videos, podcasts, lab work, and creating artifacts, showcasing students' practical application of knowledge and skills.

Teaching:

Teaching methods across the program emphasize active student learning through:

• Lectures: These provide a structured introduction to key concepts and theories.
• Seminars: These offer opportunities for interactive discussions and critical analysis of topics.
• Workshops: These provide hands-on experience with data analysis tools and techniques.
• Problem-based learning: Students work in groups to solve real-world problems, developing their critical thinking and collaborative skills.
• Blended learning: This combines online and face-to-face learning activities, providing flexibility and access to a wider range of resources.
The program is taught by a team of experienced faculty members with expertise in data science, analytics, and related fields.

Careers:

Graduates of the Data Science and Analytics BSc Honours program are well-prepared for a wide range of careers in data-driven industries, including:

• Data analyst/manager: Collect, clean, analyze, and interpret data to solve business problems and improve processes.
• The University's Careers and Employability Service provides support in finding and securing employment opportunities, with a network of over 3,000 employers worldwide.
• The program is intended to fulfill the educational requirements of the British Computer Society (BCS) for registration as a Chartered IT Professional (CITP) and partial Chartered Engineer (CEng).

• UK Fees: £9,250
• International Fees: £15,400
When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.