Big Data Analytics MSc

Program Overview

This online Big Data Analytics program provides comprehensive knowledge of both the technology and practical applications of big data. Delivered entirely online, it offers a global perspective and is accredited by the BCS for Chartered IT Professional registration. The program covers key topics such as machine learning, cloud computing, and security engineering, preparing graduates for careers in data science, big data consulting, and machine learning engineering.

Program Outline

Degree Overview:

This online Big Data Analytics MSc | PGDip | PGCert program is designed for individuals seeking to develop their knowledge and open career opportunities in the expanding field of big data analytics. The program is delivered 100% online, making it perfectly suited to its subject matter, within an international virtual classroom that offers a unique global perspective. The content has been developed by experts from the University of Liverpool’s Department of Computer Science – an institution that is globally renowned for the strength of its research into computer science, artificial intelligence and emerging technologies. The MSc program is accredited by the BCS, The Chartered Institute for IT, for the purposes of meeting the further learning academic requirement for registration as a Chartered IT Professional.

Outline:

The program consists of the following modules. You are required to complete 180 credits to achieve a full Master of Science (MSc), 120 credits to achieve the postgraduate diploma (PGDip), and 60 credits to achieve the postgraduate certificate (PGCert).

Modules:

• Global Trends in Computer Science (15 credits): This module explores the latest trends and developments in computer science, including artificial intelligence, machine learning, and cloud computing.
• Machine Learning in Practice (15 credits): This module provides a practical introduction to machine learning, covering topics such as supervised and unsupervised learning, classification, and regression.
• Cloud Computing (15 credits): This module explores the concepts and technologies of cloud computing, including cloud infrastructure, services, and security.
• Deep Learning (15 credits): This module provides an in-depth exploration of deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks.
• Elective module (15 credits): Students can choose from a range of elective modules, including:
• Applied Cryptography
• Cyber Forensics
• Cybercrime Prevention and Protection
• Multi-Agent Systems
• Natural Language Processing and Understanding
• Reasoning and Intelligent Systems
• Robotics
• Security Risk Management
• Strategic Technology Management
• Technology, Innovation and Change Management
• Research Methods in Computer Science (15 credits): This module introduces students to research methodologies and techniques used in computer science.
• Computer Science Capstone Project (60 credits): This module provides students with the opportunity to apply their knowledge and skills to a real-world project.

Assessment:

The assessment methods for this program may vary depending on the specific module. However, common assessment methods include:

• Assignments: These may include essays, reports, presentations, and case studies.
• Exams: These may be taken online or in person, depending on the module.
• Projects: These may involve individual or group work, and may require students to apply their knowledge and skills to a real-world problem.

Teaching:

The program is delivered 100% online, using a variety of teaching methods, including:

• Live lectures: These are delivered by experienced faculty members and provide students with the opportunity to interact with their peers and ask questions.
• Pre-recorded lectures: These are available on demand and allow students to learn at their own pace.
• Discussion forums: These provide a platform for students to engage in discussions with their peers and faculty members.
• Online quizzes and assessments: These help students to track their progress and identify areas where they need to improve.

Careers:

With an expected skills gap shortage in the industry, gaining a specialist qualification in big data analytics will help you to succeed in this constantly evolving field of computer science. Potential job titles include:

• Data Scientist
• Big Data Consultant
• Machine Learning Engineer
• Research Scientist
Alongside the subject-specific knowledge you will gain during the program, you will also develop professional skills such as communication, teamwork, critical thinking, and research. These will enhance your CV, allowing you to improve your career prospects and access more senior roles.

Other:

The University of Liverpool has been offering online programs since 2000. We are recognized as one of Europe’s leading providers of wholly online postgraduate degrees.

MSc: £16,065 PGDip: £10,710 PGCert: £5,355 Fees for the academic year 2024/25 MSc: £16,868PGDip: £11,246PGCert: £5,623 These fees are fully inclusive of all costs, including all teaching materials, core textbooks, assessments and resits.