Robotics and Artificial Intelligence (MSc)

Program Overview

The MSc Robotics and Artificial Intelligence program at the University of Aberdeen equips students with the skills to design, build, and test robotic and AI systems. The program focuses on fundamental concepts, bioinspired approaches, machine learning, and hands-on experience. Graduates are prepared for careers in robotics and AI, including roles as engineers, data scientists, and researchers.

Program Outline

Degree Overview:

• The MSc Robotics and Artificial Intelligence program is designed for individuals with a background in engineering or computer science who want to pursue a career in robotics and AI.
• The program focuses on:
• fundamental concepts of robotics and AI (e.g., robot manipulator arms, mobile robots)
• bioinspired approaches
• machine learning
• simultaneous localization and mapping (SLAM)
• swarm robotics
• computer vision
• AI
• hands-on experience through practical projects and lab work
• The program prepares graduates to design, build, and test systems to improve operational efficiency and productivity.
• Industry 4.0 is a major focus.

Outline:

• The MSc Robotics and Artificial Intelligence program has a course structure focusing on fundamentals and applications:
• Semester 1:
• Introduction to Mobile Robotics and Bioinspiration (15 credits) - Examines nature-based solutions for real-world robotic applications such as locomotion.
• Applied Artificial Intelligence (15 credits) - Enables exploration and creation of AI systems, using deep learning libraries and simulations.
• Machine Learning (15 credits) - Delves deep into Machine Learning methodologies and algorithms for applications like images, videos, health data, time series, language, etc.
• Semester 2:
• Kinematics and Dynamics of Industrial Robot Arms (15 credits) - Introduces analysis and use of robotic arms, focusing on theoretical and practical aspects like kinematics, dynamics, and control.
• Industrial Robot Programming and Learning (15 credits) - Covers various approaches for specifying motion of robots, including learning from experience, and fundamentals relevant for robotics research and practice.
• Data Mining with Deep Learning (15 credits) - Equips students with basic data mining and visualization techniques, using software tools for analyzing complex datasets and discovering novel patterns across diverse domains, preparing them for careers as data analysts or data scientists.
• Software Agents and Multi-Agent Systems (15 credits) - Provides a solid foundation in the theory and tools for developing and utilizing autonomous systems, relevant to both software and robots, such as self-driving cars and Amazon Echo.
• Semester 3 (Both Programs):
• MSc Individual Project (60 credits) - Students conduct independent research on a topic related to the program, focusing on a real-world industry problem and demonstrating the application of skills and knowledge acquired in the course.

Assessment:

• Assessment methods and weightings may vary depending on the specific courses.
Some examples of assessment methods were found:
• Individual and Group Projects
• Tutorials and Practical Lab work
• Examinations covering theoretical concepts
• Coursework requiring application and analysis
• MSc individual project requiring independent research, written report, and potentially oral presentation.

Teaching:

• Teaching is conducted by experienced staff from Electrical & Mechanical Engineering and Computer Science, offering an interdisciplinary approach.
• Teaching methods include:
• Lectures for foundational knowledge and theoretical understanding
• Seminars for focused discussion and exploration
• Practical Lab Work for hands-on experience with robotics equipment and technologies
• Research project supervision for personalized guidance and mentorship.
• The University of Aberdeen Robotics Laboratory provides students with access to cutting-edge technology for hands-on learning.

Careers:

• This program is designed to equip graduates for a range of careers in the rapidly expanding fields of robotics and artificial intelligence.
Potential career paths could include:
• Artificial Intelligence Engineer/ Specialist
• Design Engineer
• Machine Learning Engineer
• Robotics Engineer
• Software Engineer
• With the increasing adoption and advancement of robotic and intelligence technology across industries, strong career prospects and advancement are anticipated.
• Students are equipped for continuing their learning and adapting to new developments in Data Science and AI.
• Students have access to dedicated robotics laboratories for practical learning and research projects, with diverse equipment for a wide range of applications.
• The University is a member of the Turing University Network, contributing to cutting-edge research and development in AI and data science.

UK

Tuition Fees for 2024/25 Academic Year: £11,100

EU / International students

Tuition Fees for 2024/25 Academic Year: £27,000