Course description
Machine Learning faces with increasing availability of large datasets are significant drivers for technological development of robots and autonomous systems, and they are being increasing utilised in new products and services.
The aim of this module is to provide delegates with the necessary knowledge and understanding for the application of machine learning & artificial intelligence techniques to real world industrial problems within the domain of robotics and beyond.
Companies using machine learning to optimize business processes and decision-making have distinct advantages over those that aren’t. By wielding machine learning technology to make business objectives more predictive and prescriptive, data-driven enterprises are redefining how to create and measure value. With the development of free, open-source machine learning and artificial intelligence tools, it’s never been easier for companies of all sizes to harness the power of data.
Effectively integrating machine learning applications into your business requires a practical understanding of its models. The Machine Learning short course from aims to equip your workforce with the skills to understand the impact of machine learning and apply its models. Your employees will learn to analyze the models and techniques.
Upcoming start dates
Suitability - Who should attend?
This course is suitable for:
- Engineers
Outcome / Qualification etc.
What you will learn
On successful completion delegates should be able to:
- Construct a wide range of machine learning techniques to solve industry problems particularly within the domain of robotics.
- Appraise the application of machine learning approaches to a wider set of data mining and classification type problems.
- Using a provided implementation, plan machine learning analysis on suitable forms of computer and robotics data.
- Examine the concepts and operation of a range of machine learning algorithms in order to facilitate re-implementation in a software programming environment with which they are already familiar.
- Develop programme in solving machine learning problems through interactive learning workshops.
Training Course Content
Core content
- Introduction to Machine Learning Theory Applications.
- Decision tree modelling, logical reasoning.
- Probability theory and Bayesian methods.
- Classification methods and clustering techniques.
- Bio-inspired artificial intelligence algorithms.
- Reinforcement learning.
- Case study for robotics applications.
Course delivery details
Course structure
Working group activities including presentation on the last day. Lectures and computer labs
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Cranfield University
Cranfield is a specialist postgraduate university that is a global leader for education and transformational research in technology and management. We have many world-class, large-scale facilities, including our own global research airport, which offers a unique environment for transformational education...