Introducing online MSc Artificial Intelligence — University of Essex

Sharon Sibanda, head of computing at the University of Essex Online, explains how the MSc Artificial Intelligence equips students from all backgrounds with the skills to thrive in the fast-moving world of AI

What does a course on artificial intelligence involve?

The programme covers a range of topics designed to provide a comprehensive understanding of the field, including:

• Machine learning - Techniques and algorithms that enable computers to learn from data.
• Neural networks - Understanding the structure and function of artificial neurons and how they form networks.
• Programming - Involving languages like Python and R.
• Model evaluation - Methods for assessing the performance of AI models.
• Ethics in AI - Understanding the ethical implications and responsibilities of AI development.
• Problem solving - Developing strategies to tackle complex AI challenges.
• Collaboration - Working in teams to build and refine AI models.
• Major project - Practical projects to apply learned concepts to real-world problems.

Can you tell us about studying online and how that works?

Studying online has become increasingly popular and offers a flexible way to learn. The MSc in AI course is hosted on our award-winning virtual learning environment called Moodle.

Courses are divided into modules, which contain several units. Each unit is studied weekly and includes content such as lecturecasts, quizzes, readings and practical labs or exercises. This is in addition to regular seminars throughout the module.

Seminars are live sessions where students interact with their tutors and get the opportunity to raise any questions. Interaction is also encouraged via discussion forums where students can ask questions, share insights, and discuss topics. Peer collaboration is fostered through group projects and peer reviews, allowing students to work together and learn from each other.

Regular assessments focus on testing your understanding. Practical assignments often involve real-world applications. You can often complete the course at your own speed, making it easier to fit into your schedule. Online courses allow you to study from anywhere with an internet connection, using a computer, tablet, or smartphone.

Support is available with direct feedback from tutors on assignments and projects. The academic team offer help with any technical issues you might encounter.

What makes the course unique?

This course includes a practical lab-based approach to skills development in addition to theoretical concepts. Lecturecasts are used to convey complex information in an engaging manner. The subject matter is relevant and regularly updated to align with industry trends. Some key areas covered in the content include:

• Robotics - applying AI to control and optimise robotic systems.
• Healthcare - using AI for diagnostics, treatment planning, and personalised medicine.
• Finance - implementing AI for fraud detection, trading algorithms, and risk management.

Where can the course lead?

Some potential paths include:

• Machine learning engineer - Designing and implementing machine learning models and algorithms.
• AI research scientist - Conducting cutting-edge research to advance the field of AI.
• AI product manager - Overseeing the development and deployment of AI products and solutions.
• Robotics engineer - Developing intelligent robotic systems for various applications.
• Natural Language Processing (NLP) specialist - Working on technologies that enable machines to understand and process human language.
• Computer vision engineer - Developing systems that can interpret and understand visual information.
• University lecturer  - Teaching and mentoring the next generation of AI professionals while conducting research.

You could also work in healthcare, finance, the automotive industry or as a startup founder launching your own AI-based startup to bring innovative solutions to market.

What types of students would suit this course?

An AI postgraduate programme can be a great fit for a variety of students, including:

• Computer science graduates - Those with a strong foundation in programming, algorithms, and data structures.
• Engineering students - Particularly those from electrical, electronics, or mechanical engineering backgrounds.
• Mathematics enthusiasts - Students who enjoy working with complex mathematical models and theories.
• Statisticians - Those with a background in statistics and data analysis.
• AI hobbyists - Individuals who have been exploring AI through online courses, projects, or personal research.
• Tech innovators - Students who are excited about the potential of AI to solve real-world problems.
• Business professionals - Those interested in applying AI to their field, e.g. healthcare for medical diagnostics and treatment.
• Business analysts - Individuals looking to leverage AI for business intelligence and decision-making.
• Research-oriented students - Those interested in contributing to academic research and pushing the boundaries of AI knowledge.

What advice do you have for anyone considering studying the course?

Considering a postgraduate AI programme is an exciting step. Ensure you have a solid understanding of programming, mathematics, and statistics. Familiarise yourself with basic AI concepts through introductory courses or reading materials.

You should also:

• Work on practical projects to apply what you've learned. This can help you build a portfolio that showcases your skills.
• Follow industry news, research papers, and attend conferences to stay informed about the latest developments in this rapidly evolving field.
• Participate in online forums, local meetups, and professional organisations related to AI.
• Think about what you want to achieve with your AI degree. Whether it's research, industry work, or entrepreneurship, having clear goals can guide your efforts.
• Look for internships, part-time jobs, or volunteer opportunities in AI-related roles. Practical experience is invaluable.

Find out more

• Take a look at the MSc Artificial Intelligence.
• Read all about the information technology sector.