Artificial Intelligence

The MSc in AI contains modules covering fundamental and specialised AI topics as well as topics related to operationalisation and application of AI to solve real-world problems. All students will gain a deeper understanding of the complete development lifecycle of AI software applications from requirements elicitation and analysis, implementation, decision making, evaluation, and documentation.

The course will be delivered using academic research, industry defined practical problems, and case studies. This approach will naturally provide a deeper knowledge of AI and create skills required in industry such as critical thinking, problem-solving, creative thinking, communication, teamwork, and research skills.

Upon completion of this course, graduates will be able to:
• Demonstrate expert knowledge of Engineering Artificial Intelligence systems, Machine Learning, Optimisation Techniques, and the tools, techniques and technologies of Artificial Intelligence utilised in real world contexts.

• Formulate, design, implement, and evaluate novel real-world solutions at the forefront of Artificial Intelligence using the latest industry practices and standards.

• Select, assess, and apply advanced and emerging Artificial Intelligence techniques and tools to enhance decision making.

• Synthesise and communicate technical Artificial Intelligence solutions.

• Critically assess and evaluate ethical, sustainable, and responsible issues associated with the development and deployment of Artificial Intelligence systems.

• Conduct independent research in the field of Artificial Intelligence.

Who is this course for?
This course is ideal for graduates that are looking to progress into the emerging AI market to increase their employment potential. The course is suitable for graduates who have programming and mathematical problem-solving skills. Graduates from disciplines that have not developed these skills will need to be able to demonstrate an aptitude for programming or mathematical problem solving.

Subjects taught

Core Modules
Foundations of Artificial Intelligence
Programming for Artificial Intelligence
Data Analytics for Artificial Intelligence
Data Governance and Ethics
Engineering and Evaluating Artificial Intelligence Systems
Intelligent Agents and Process Automation
Artificial Intelligence Driven Decision Making
Machine Learning
Emergent Artificial Intelligence Technologies and Sustainability
Practicum/Internship

Entry requirements

A minimum of a level 8 primary degree in Computing or a cognate area with a 2.2 award or higher or equivalent on the National Qualifications Framewor. Cognate area means a STEM (Science, Technology, Engineering, and Mathematics) degree that also taught programming/ application development related modules. An assessment and/ or interview may be conducted to ascertain suitability if necessary.

The college operates a Recognition of Prior Experiential Learning (RPEL) scheme meaning applicants who do not meet the normal academic requirements may be considered based on relevant work and other experience. This may be assessed using a portfolio of learning, demonstration of work produced, and an interview. The programming ability of the applicant will also be assessed. Non-English speaking applicants must demonstrate fluency in the English language as demonstrated by IELTS academic score of at least 6.0 or equivalent.

Laptop Requirement
This programme has a BYOD (Bring Your Own Device) policy. Specifically, students are expected to successfully participate in lectures, laboratories and projects using a portable computer (laptop/notebook) with a substantial hardware configuration. The minimal suitable configuration is 8GB of RAM (16GB are recommended); a modern 64-bit x86 multicore processor (Intel i5 or superior); 250+ GB of available space in hard disk; WiFi card; and a recent version of Ubuntu, macOS, or Windows. It is the responsibility of each student to ensure their computer is functioning correctly and that they have full administrator rights. NCI IT cannot provide support for these personal devices. Some students may be able to avail of theStudent Laptop Loan Scheme, subject to eligibility.

Application dates

Apply online.

Duration

Part-time Schedule

Duration
2 years, 4 semesters with an Internship/Practicum

Delivery
Blended - Livestream with some on-campus stream classes, scheduled in advance.

Indicative Timetable
Two evenings per week, 18.00 - 22.00 and every second Saturday. Please note that exams can be scheduled during the morning, afternoon, or evening Monday to Saturday.

Full-time Schedule

Duration
1 year; 3 semesters with an Internship/Practicum

Delivery
Classes will take place face-to-face on campus.

Indicative Timetable
Students need to be available 09.00 - 18.00 Monday to Friday. (Class days and times vary)

Enrolment dates

Start Date: September 2023.

More details
  • Qualification letters

    MSc

  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Blended,Daytime,Evening,Full time,Part time,Weekend

  • Apply to

    Course provider