BSc (Hons) in Computing in Artificial Intelligence Engineering
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Course Overview
This course combines a strong foundation in software engineering with specialist knowledge in Artificial Intelligence, Machine Learning, Deep Learning, Large Language Models, Agentic AI and MLOps. The course progresses from foundational concepts such as programming and mathematics into advanced areas including Machine Learning, Cloud Services, Vector Databases, Natural Language Processing, Explainable AI and responsible AI development.
Students will learn not only how AI models work, but how to design, build, deploy and maintain scalable AI-powered applications. Through labs, practical projects and a dedicated Work Placement or Erasmus semester, students develop real-world technical and professional experience.
Graduates will be prepared for careers such as AI Engineer, Machine Learning Engineer, Software Engineer and Data Scientist, as well as progression to postgraduate study and research.
What makes this course different
Engineer AI, Don’t Just Use It
This course goes beyond teaching students how to use AI tools. Students learn how to design, build, deploy and maintain complete AI systems, combining AI expertise with strong software engineering, cloud and DevOps skills.
Learn the Technologies Shaping the Future of AI
The curriculum includes emerging areas such as Agentic AI, Large Language Models (LLMs), Deep Learning, Vector Databases, Explainable AI and MLOps, giving students experience with technologies at the forefront of modern AI engineering.
Real-World Experience Built into the Degree
Students have the opportunity to complete a dedicated Work Placement or Erasmus semester in Year 3, while practical, integrated projects run throughout the programme. This allows students to apply what they learn to substantial real-world problems and build experience before graduating.
Understanding the Industry
Artificial Intelligence is rapidly transforming how organisations develop software, analyse data, automate processes and solve complex real-world problems. This course is designed with industry and employability at its core, giving students an understanding of how modern AI technologies are designed, deployed and managed within professional environments.
Career Opportunities
- AI Engineer
- Machine Learning (ML) Engineer
- Software Engineer
- AI Software Developer
- Data Scientist
- Graduate AI Developer
- Graduate Software Engineer – AI
- AI Security / Data Science roles
- MLOps / AI Deployment roles
- AI Researcher / Postgraduate Researcher
Sectors
- Technology
- Finance
- Healthcare
- Research
Course Delivery and Modules
Through labs, practical projects and a dedicated Work Placement or Erasmus semester, students develop real-world technical and professional experience.
- Professional Skills for Computing
- Programming (year-long)
- Static Website Development
- Mathematics
- Linux Fundamentals
- Introduction to Design
- Networking
- Database Systems
- Dynamic Website Development
- DevOps
- Project 1 – Prime
- Wellbeing and Career Resilience
- Object-Oriented Programming
- Software Testing
- Microservices
- Mathematics for AI
- Dataset Engineering
- Object-Oriented Design
- Project Management
- Data Mining and Visualisation
- Probability and Statistics
- Project 2 – Bridge
- Design Patterns
- Algorithms and Data Structures
- Security
- Distributed Big Data Systems
- Machine Learning
- Project 3 – Collaborate
- Work Placement or Semester Abroad or International Intensive Project
- Agentic AI
- Cloud Services
- Research Methods
- Reinforcement Learning or Ethical AI and Trustworthy Software Development
- Project 4 – Summit (year-long)
- The Ethical Future Professional
- Deep Learning
- Vector Databases and Information Retrieval
- Machine Learning Operations (MLOps)
- Natural Language Processing and Large Language Models with Explainable AI
Work placement
Students have the opportunity to put their learning into practice through a dedicated Work Placement in Year 3. Allowing them to experience a professional working environment, develop valuable industry connections and apply the technical skills you have developed throughout the course to real-world challenges.
Work placement is an important part of preparing for a career in the rapidly evolving technology sector. Alongside technical experience, students will develop essential professional skills such as communication, teamwork, problem-solving and adaptability, helping you build confidence and experience before graduating.
Students may also have the opportunity to choose an Erasmus or international experience as an alternative, providing the chance to broaden their skills and gain valuable experience in an international setting
Fees and Funding
Please find information on fees and funding here: www.dkit.ie/fees
Entry requirements
Standard entry requirements apply.
- Standard Requirements for Leaving Certificate Applicants
- Standard Requirements for UK/NI Applicants
- Standard Requirements for QQI-Further Education Applicants
- Mature Applicants: Minimum of 23 years of age on January 1st of year of application
How to apply
Apply on CAO
All standard entry first-year applicants must apply for entry through the CAO. See Important application dates for CAO and information for specific applicant types below:
International Application (non-EU)
International Applicants (not from or living in the EU) can apply through an agent or directly to DkIT to study this course.
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Department Office
Disclaimer: All module titles are subject to change and for indicative purposes only. All courses are delivered subject to demand and timetables are subject to change. Elective Module options will only run subject to student numbers. The relevant Department will determine the viability of each elective module option proceeding depending on the number of students who choose that option. Students will be offered alternative elective modules on their programme should their preferred elective option not be proceeding. Award Options for Common Entry Programmes: The relevant Department will determine the viability of each award option proceeding depending on the number of students who choose either option. If the numbers for one of the Award options exceed available places, students for this option will be selected based on Academic Merit (highest grades).