Internet of things with data science

This module will help you to explore the full data mining lifecycle, from data pre-processing and exploratory data analysis to the application and evaluation of supervised and unsupervised machine learning algorithms.

Through practical, hands-on workshops using Python and Microsoft Azure Machine Learning, you will gain experience at using machine learning and data mining tools and techniques to extract insights from data. 

This module will provide you with the history, advanced understanding, and context of IoT, the skills, challenges, System Design and methodologies the term implies. You will learn about the architectures to develop an IoT application using wearable sensors. You will experience all the stages in the design and implementation of a complex system, from its specification to the demonstration of a working prototype.

During this module, you will cover aspects of embedded systems programming, sensor data analytics using machine learning methods, user interface design, system integration and testing. 

IoT devices and applications present new security vulnerabilities and challenges, and the data they generate has given rise to concerns over personal data and privacy. This industry-aligned module provides specialist cyber security knowledge, and a hands-on ethos, so you will gain the skills and knowledge ready to fight security and privacy issues and challenges in IoT systems.

In this module, you will learn about both attack and defence mechanisms and consider established attack surfaces (networking, social engineering) and modern issues (IoT, Cloud).  You will also examine trade-offs between security and availability, and between privacy and audit; study threats to information security, technologies used to detect and combat them, and techniques and tools used to manage and investigate incidents.  

The project module aims to provide you with an opportunity to integrate learning from the course modules, working under the direction of an academic supervisor to carry out high-level coordinated academic and practical work on researching a suitable problem and developing, evaluating and critically assessing a robust, scalable and usable solution.

This module will provide you with a broad overview of relational databases and Structured Query Language (SQL). You will learn the theory and practice of effective database design and will gain fluency in using SQL to query, extract and analyse data, and to create and manage databases.  You will also learn key issues within the field of databases, including performance, security, recovery and transaction management.

This module will introduce you to Big Data, the characteristics that define it, and the challenges and opportunities it presents. You will learn how cloud computing, distributed data processing frameworks, and NoSQL databases can be used to ingest, process, analyse and store massive, complex datasets. Alongside this, practical workshops will give you hand-on experience working with a wide range of real-world datasets, including unstructured text data, image data and data from Internet of Things sensor networks. You will learn how to use Apache Spark to process large-scale data and apply data analysis, data visualisation and machine learning techniques.