This programme teaches you practical skills, underpinned by core theories so that you are able to gain expertise in the key skill areas of the internet of things. Through a combination of compulsory and elective models, you will explore a range of industry-relevant data analysis skills. These include Applied Statistics, where you will use the R-Language to find patterns in data; Big Data Processing using Google’s MapReduce & Apache Hadoop; Machine Learning using Keras and Data Analytics using Python. During the programme, you will also gain fundamental practical skills and learn how to engineer new smart devices. We teach you how to prototype innovative smart objects for IoT. You will focus on using a range of sensors, actuators and microcontroller and microcomputer boards, especially for location determination such as: air quality sensing, human activity recognition and robotics. We also teach you how to interconnect new and existing things to each other. We cover a range of networks including short-range, such as Near Field Communication and wireless personal area networks like Bluetooth and ZigBee. We also explore local area networks like Wi-Fi and cellular networks such as 5G and 6G, as well as cloud computing and edge computing. This programme has been accredited by the IET on behalf of the Engineering Council and a suffix "EngC Pathway" will be added to the degree title when a student satisfies the accreditation requirements. Progression and award requirements for an accredited MSc are stricter than these requirements for a standard QMUL degree. If a student does not satisfy the accreditation requirements, but does satisfy the requirements for a standard QMUL degree, the "EngC Pathway" suffix will not be added.