Informatics Institute of Technology 35 years
Informatics Institute of Technology 35 years
infomatics institute of technology

The programme combines fundamental theory with practical, industry-focused learning to develop both
technical expertise and essential professional skills. You will build strong capabilities in programming,
data processing, statistics, algorithms and problem-solving, alongside communication, creativity,
teamwork and critical thinking. With these skills, you will be well prepared for exciting careers in AI,
machine learning, data science and other rapidly evolving technology fields.

infomatics institute of technology

Awarding University & Course Recognition

infomatics institute of technology

Awarded by the University of Westminster, UK

infomatics institute of technology

Recognized by the University Grants Commission of Sri Lanka

Next Intake

January
Intakes

January / September

infomatics institute of technology

Duration

3 Years

(Full-Time / Part-Time)

infomatics institute of technology

Entry Requirements

  • Students must possess at least six passes in GCE O/L including a minimum “C” for English language and a “C” Pass grade for Mathematics in the local syllabus and six passes including “C” grade for English language and “C” Pass for Mathematics in London O/L
  • Pass certificate in IIT Foundation Programme
  • Other recognised equivalent qualification formally accepted by IIT and University of Westminster.

For most courses a decision will be made on the basis of your application form alone. However, for some courses the selection process may include an interview to demonstrate your strengths in addition to any formal entry requirements.

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Associated Careers

Graduates of the BSc (Hons) Artificial Intelligence programme are well-positioned for a wide range of
AI, data, software, and technology-focused roles across diverse industries. Potential career pathways
include:

  • AI Consultant
  • AI Engineer
  • AI Ethics Officer
  • AI Policy Analyst
  • AI Solutions Architect
  • Autonomous Systems Engineer
  • Business Intelligence Analyst
  • Data Scientist
  • MLops Engineer
  • Software Engineer
Core Modules
  • Applications of AI and Prompt Engineering
  • Database Technologies
  • Foundations of AI
  • Human-Centred AI and Ethics
  • Mathematics for AI
  • Software Development I
Core Modules
  • Applied Deep Learning
  • Data Science Project Lifecycle
  • Game Theory and Reinforcement Learning
  • Robotic Principles
  • Practical Machine Learning
  • Data Engineering
Optional Modules
  • Data Visualisation and Communication
  • Game Engine Architecture
Core Modules
  • Advanced topics in deep learning
  • Applications of Large Language Models
  • AI final year project
  • Secure, Scalable AI and Cloud Computing
Optional Modules
  • Applied Robotics
  • Big Data Analytics
  • Business Innovation with Artificial Intelligence
  • Game AI

Professional Body Accreditation & External References
The course has been designed with reference to:

  • QAA Subject Benchmark for Computing
  • Engineering Council – Accreditation of Higher Education Programmes (AHEP), 4th Edition
  • QAA Guidelines for Preparing Programme Specifications
  • SEEC Credit Level Descriptors for Further and Higher Education

Professional Recognition

  • Designed to meet the educational requirements for BCS (The Chartered Institute for IT) accreditation towards CITP (Chartered IT Professional).
  • Partially meets the academic requirements for CEng (Chartered Engineer).
  • The programme will be submitted for initial BCS accreditation before the first cohort graduates.

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