Artificial Intelligence - MSc

London Metropolitan University

This module introduces the essential principles, methods and techniques in AI. It covers a broad range of topics such as search, planning, logic, knowledge representation and machine learning. It discusses examples of intelligent systems and studies how to develop intelligent applications such as expert systems, learning systems, and autonomous mobile and robotic systems. Students will be offered lectures, which introduces the important concepts, explain the principles and techniques, and demonstrate how to apply them to solve problems in the related topics. The workshops will provide practical sessions to help students understand the content of the lectures and build the necessary skills to develop intelligent systems.

This module provides students with an in-depth appreciation of the Internet of Things (IoT) and Cloud Computing concepts, models, infrastructures and capabilities. The module will place emphasis on modern system architecture and design, Autonomous Intelligent Systems (AIS), key wireless/mobile/sensor technologies, and issues of privacy and trust, in the development of Cloud-based IoT systems. Practical work within the module will provide students with real, hands-on, experience of building a basic Internet of Things infrastructure that can access Cloud Computing services and the opportunity to develop their Python programming skills and abilities. Some basic knowledge of Python will be used throughout. Understanding of various Intelligent, wired and wireless technologies could be an advantage.

The module aims to strengthen students? skills in data technologies ranging from database and data warehousing to Big Data. First, it will provide students with good understanding of database concepts and database management systems in reference to modern enterprise-level database development. Once gaining good skills in database development, students will be able to study and gain an in-depth understanding of data warehousing which include concepts and analytical foundations as well as data warehousing development. Through intensive hands-on sessions, the students will be able to get familiar with related technological trends and development in the field. the module will leverage a portfolio of SQL server tools that include SQL Server DBMS, SQL Server Integration Services (SSIS), SQL Server Reporting Services (SSRS) and SQL Server Analysis Service (SSAS) to provide hands-on experience in implementing a reporting solution through a combination of assignments and lab exercises.

The module provides students with the experience of planning and bringing to fruition a major piece of individual work. Also, the module aims to encourage and reward individual inventiveness and application of effort through working on research or company/local government projects. The project is an exercise that may take a variety of forms depending on the nature of the project and the subject area. Particular students will be encouraged to carry out their projects for local companies or government departments.

This module provides a comprehensive overview of the methods for machine learning and data analytics suitable for use in the data analysis and Big Data Analytics. It also provides practical skills for working with various tools for data analysis and Big Data Analytics inside and outside the platform such as Python, R, Spark, etc. The knowledge and skills obtained can be used in many tasks where the data analysis is of crucial importance for the competitiveness and the effectiveness of the businesses ? customer profiling, product recommendations, market trends analysis, cybersecurity, etc. Some basic programming skills using languages for numerical processing such as Python or R or other relevant languages can be an advantage.

This module provides the theoretical foundations, the technologies and the corresponding tools for constructing intelligent model-driven software systems with explicit representation of knowledge. It will enable the students to model, design and implement software systems, which demonstrate ?artificial intelligence? similar to the intelligence of the human behaviour. At the same time, it will help the students understand better the rationality behind the human intelligence.