MSc Internet of Things with Data Analytics

Program Overview

Bournemouth University's MSc Internet of Things with Data Analytics program prepares students to thrive in the growing field of IoT. Through hands-on experience and a strong theoretical foundation, graduates gain expertise in designing smart devices, analyzing IoT data, and engaging in research. The program's emphasis on collaboration with industry enhances employability and equips students to solve real-world IoT challenges.

Program Outline

Degree Overview:

This MSc Internet of Things with Data Analytics program at Bournemouth University is designed to equip students with the skills and knowledge needed to thrive in the rapidly growing field of the Internet of Things (IoT). The program focuses on the design and development of smart devices and networked systems, emphasizing the collection, movement, and management of IoT data.

Objectives:

• Develop expertise in designing and building next-generation smart devices and networked systems.

• Gain a strong theoretical foundation in IoT principles and technologies.

• Acquire hands-on experience in designing and developing IoT systems.

• Engage with the research activities of the department through the IoT Lab.

• Explore specialized areas of interest through optional units in Artificial Intelligence, Data Processing & Analytics, Computer Vision, Neuronal Analysis, and Search & Optimization.

• Conduct independent research and develop a Master's Project.

• Enhance employability through international placements and career support.

• Benefit from the university's strong connections with companies, research institutions, and government agencies seeking skilled IoT graduates.

Outline:

Program Structure:

• Full-time: 16 months (January start)
• Part-time: 32 months (January start)

Core Units:

• Mobile & Wireless Networks: This unit explores the principles, protocols, and standards of various mobile and wireless technologies, including WiFi, ad hoc networks, and cellular networks.
It examines their applications in different contexts and scenarios, addressing challenges and their integration into modern networking paradigms.
• Wireless, Sensor & Actuator Networks: This unit delves into the operating principles, standards, design, and configuration of Wireless Sensor and Actuator Networks (WSANs).
It also covers emerging paradigms like Mobile Crowdsensing Systems and technologies such as Wireless Power Transfer in ad-hoc networks.
• Security and Privacy in IoT: This unit focuses on the security vulnerabilities of smart objects, IoT applications, and their enabling platforms.
It explores how to address security attacks and changing operating conditions that can compromise system components. The unit also examines the ethical and legal implications of handling massive amounts of personal data generated by IoT systems.
• Research Methods & Professional Issues: This unit equips students with essential research skills, covering project proposals, planning, critical analysis of research findings, academic writing, and dissemination.
It emphasizes professional standards and ethical considerations in research.
• Individual Masters Project: This unit allows students to apply their knowledge and skills to solve a complex, real-world problem within the context of a substantial, independently conducted research project.
It examines the migration of local networks and IT resources to the cloud and strategies for effective cloud migration.
• Neuronal Analysis: This unit focuses on data analysis techniques in neuroscience, including algorithms adapted or designed for analyzing neuronal activity in various brain states.
It explores the mathematical modeling of neuronal functions and the development of parallel data processors inspired by biological neurons and networks.
• Search & Optimization: This unit examines search and optimization techniques used in various fields, including medicine, defense, transportation, aerospace, and finance.
It explores how stochastic optimization algorithms can be used to design optimal solutions for real-world problems.

Semester 2:

• Data Processing and Analytics: This unit develops students' knowledge and skills in data modeling, data analytics, and big data analytics.
• Artificial Intelligence: This unit provides an introduction to the principles and techniques of Artificial Intelligence (AI), covering sub-fields, challenges, nature-inspired algorithms, and their applications to real-world problems.
• Computer Vision: This unit explores various computer vision techniques, from traditional approaches to state-of-the-art developments.
It includes practical exercises where students build and evaluate computer vision models.

Assessment:

The assessment methods and contact hours for each unit are detailed in the program specification.

Teaching:

• Faculty: The program is taught by experienced faculty with expertise in relevant areas, including senior academic staff, qualified professional practitioners, and research students.
• Teaching Methods: The program utilizes a variety of teaching methods, including lectures, seminars, workshops, practical exercises, and project work.
• Unique Approaches: The program emphasizes hands-on learning through the IoT Lab, where students can engage in practical projects and research activities.

Careers:

Potential Career Paths:

• Product Manager, Consumer IoT
• IoT Global Partner Manager
• New Technologies & Innovation Manager
• Business Transformation Manager
• Head of Connected Cities
• IoT Proposition Manager

Opportunities:

• The program prepares students for a wide range of career opportunities in the rapidly growing field of IoT.
• Graduates can find employment in various industries, including manufacturing, transportation, logistics, defense, agriculture, infrastructure, retail, healthcare, and food services.

Outcomes:

• The program equips students with the skills and knowledge needed to succeed in the competitive IoT job market.
• Graduates are well-prepared to contribute to the development and implementation of innovative IoT solutions.

Other:

• The program is regularly reviewed to incorporate new approaches to teaching and learning and industry developments.
• The university offers a range of scholarships and bursaries to eligible students.
• Students have access to a variety of student services, including advisors, help desks, counsellors, placement support, and a careers service.
• The university provides access to Brightspace, a virtual learning environment, the library, IT labs, and other resources.
• The university offers disability and additional learning support.
• The BU Language Centre provides support for developing or improving foreign or English language skills.
• The university has a 24/7 security team.