Artificial Intelligence
Computing, Engineering and Technology
Taught
MSc
Taught
MSc
Overview
Application Timeline
Tuition
- Year 1
| Student categories | Study | |
|---|---|---|
| Full-time | Part-time | |
| England | £13,300 | N/A |
| Northern Ireland | £13,300 | N/A |
| Scotland | £13,300 | N/A |
| Wales | £13,300 | N/A |
| Channel Islands | £13,300 | N/A |
| Republic of Ireland | £13,300 | N/A |
| EU | £31,900 | N/A |
| International | £31,900 | N/A |
Requirements
Language requirements information is currently unavailable.
Modules
Modules is currently unavailable
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About
Foundation in Computer Science
This course is designed to enhance your understanding of computer science principles and practices.
- Coding
- Mathematics
- Basic Engineering
AI Methodologies
You will explore both the theoretical and practical aspects of AI, focusing on:
- Symbolic AI
- Learning-based AI
Applications of AI Techniques
The course will cover the application of modern AI techniques in various fields, including:
- Computer Vision
- Robotics
- Graphics
- Data Analysis
- Games
Subject Area Information
Artificial Intelligence (AI) is a rapidly evolving field that encompasses a wide range of topics and applications. Courses in this discipline are designed to provide students with a comprehensive understanding of the theoretical foundations, practical implementations, and ethical considerations of AI technologies.
1. Introduction to Artificial Intelligence
2. Machine Learning
3. Natural Language Processing (NLP)
4. Robotics
5. Computer Vision
6. AI Ethics and Society
- Proficiency in programming languages such as Python, R, and Java
- Understanding of algorithms and data structures
- Ability to implement machine learning models and neural networks
- Capability to analyze and interpret complex data
- Develop predictive models and optimize algorithms
- Aptitude for designing innovative solutions to real-world problems using AI technologies
- Awareness of the ethical considerations and societal impacts of AI
Career
A curriculum in Artificial Intelligence equips students with a robust set of skills and knowledge, preparing them for a wide range of careers in academia, industry, and beyond. The interdisciplinary nature of AI ensures that graduates can contribute to various sectors, driving innovation and addressing complex challenges.
AI Research Scientist
Conducts cutting-edge research to advance the field of AI.
Machine Learning Engineer
Designs and implements machine learning models and systems.
Data Scientist
Analyzes large datasets to extract insights and inform decision-making.
Robotics Engineer
Develops and programs robots for various applications.
NLP Engineer
Works on projects involving language understanding and generation.
AI Ethicist
Focuses on the ethical implications and societal impacts of AI technologies.
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