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This Short Course in Artificial Intelligence will provide learners with the foundation and branches of artificial intelligence, such as search strategies, knowledge representation and reasoning techniques. This course will also introduce a range of well-known techniques and applications in artificial intelligence, such as fuzzy logic, machine learning, expert systems, natural language processing, and intelligent agents. At the end of the course, learners should be able to: 1. Understand the importance of AI and its applications. 2. Apply a range of well-established AI search strategies and knowledge representation techniques in problem solving. 3. Assess a range of well-established techniques for reasoning with uncertain knowledge. 4. Understand a range of machine learning techniques. 5. Understand the range of AI techniques that are being applied in industry or research. 6. Implement and evaluate a range of AI models and techniques for solving real-world problems.

Overview Our Computer Basics Short Course will provide students with an introduction to the key Computer Basics that with be required in their studies. Students will learn basic skills in using word processors, spreadsheets and presentation software. The course will focus on the Microsoft Office suite, with: reference being made to Microsoft Office 2010 software throughout. However, the course has been specifically designed to allow the relevant skills to be taught regardlass of the software version being used. All material can be adapted to other versions of Microsoft Office (such as the 2007 version) and also other word processing, spreadsheet, and presentation software packages; students should not be disadvantaged through the use of any particular version. Entry Requirements As a minimum, participants should have demonstrably previously studied in English at secondary school level.

It is a forward-looking approach with the focus on analysing the past or current data and predicting the future outcomes with the aim of making informed decisions. Regardless of industry or size, organizations that wish to remain competitive in the age of big data need to efficiently develop and implement data science capabilities. The course is made up of 4 Stages with each stage covering topics in Statistics, Coding, Modelling and Data Visualization verticals..-+ Individuals who are just embarking on the data science journey either as a "STEM" fresh graduate or those looking to upskill into data science Knowledge of either computer science, programming or strong mathematics background is essential.