Intelligent Systems and Robotics
Computing, Engineering and Technology
Taught
MSc
Intelligent Systems and Robotics
Taught
MSc
Overview
Application Timeline
Tuition
- Year 1
| Student categories | Study | |
|---|---|---|
| Full-time | Part-time | |
| England | £12,125 | £12,125 |
| Northern Ireland | £12,125 | £12,125 |
| Scotland | £12,125 | £12,125 |
| Wales | £12,125 | £12,125 |
| Channel Islands | £12,125 | £12,125 |
| Republic of Ireland | £12,125 | £12,125 |
| EU | £23,500 | £23,500 |
| International | £23,500 | £23,500 |
Requirements
Language requirements information is currently unavailable.
Modules
Modules is currently unavailable
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About
Overview of Robotics
Robotics integrates knowledge from various fields such as computer science, artificial intelligence, engineering, and neuroscience to create hardware capable of sensing and interacting with the real world. This multidisciplinary approach has led to the development of diverse technologies, including satellites, submarines, racecars, and robots.
Research Achievements
Our research team has made significant contributions to the field, including:
- Participation in the Robot Soccer World Cup final
- Creation of an autonomous robot fish for the London Aquarium
- Development of a self-programming computer vision system
Course...
Subject Area Information
Intelligent Systems is a multidisciplinary field that integrates principles from computer science, artificial intelligence (AI), machine learning, robotics, and cognitive science to create systems capable of performing tasks that typically require human intelligence.
1. Introduction to Intelligent Systems
2. Machine Learning
3. Robotics and Autonomous Systems
4. Cognitive Systems
5. Data Mining and Big Data
6. Natural Language Processing (NLP)
- Understanding of fundamental principles
- Ability to identify and describe various intelligent systems
- Basic programming skills
- Ability to design and implement machine learning algorithms
- Proficiency in using machine learning libraries and frameworks
- Data analysis and preprocessing
- Designing and programming robotic systems
- Integrating sensors and actuators
- Developing control algorithms
- Implementing autonomous navigation
- Understanding of cognitive processes
- Ability to design systems that mimic human cognition
- Proficiency in developing interactive systems
- Extracting meaningful patterns from large datasets
- Using big data tools and technologies
- Data visualization techniques
- Developing NLP applications
- Understanding linguistic structures
- Implementing speech and text processing algorithms
Career
Upon completing courses in Intelligent Systems, students can pursue a variety of careers, including but not limited to roles that involve designing, implementing, and managing intelligent systems across various applications.
AI Engineer
Designing and implementing AI models and algorithms.
Machine Learning Engineer
Developing machine learning models and deploying them in production environments.
Robotics Engineer
Creating and programming robotic systems for various applications.
Data Scientist
Analyzing and interpreting complex data to help organizations make informed decisions.
NLP Specialist
Developing applications that process and analyze human language data.
Cognitive Systems Engineer
Designing systems that simulate human cognitive processes.
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