EISE Programme
Engineering is entering a new era driven by intelligent physical systems that can sense, learn, communicate, and act autonomously in complex environments. This transformation extends far beyond robotics, reshaping industries ranging from telecommunications and biomedical engineering to autonomous systems, smart energy, and advanced manufacturing. Meeting these challenges requires more than expertise in artificial intelligence alone—it demands engineers who can seamlessly integrate AI with electronics, communications, power, and control to create reliable, real-world solutions. The EISE program has been designed to meet this emerging global need by providing a rigorous engineering education that combines strong theoretical foundations with hands-on design experience, preparing graduates to lead the development of next-generation intelligent systems. The programme equips students with the knowledge, skills, and innovation mindset to thrive at the forefront of global industry, research, and technological advancement.
Graduate Profile
Graduates of the EISE program are more than software-bound AI practitioners. They are uniquely trained engineers capable of navigating the entire stack—from high-level intelligence to the physical hardware that powers it. They will develop a comprehensive understanding of the four pillars that are central to modern engineering:
- The Mathematics of Intelligence: A rigorous grounding in the calculus, linear algebra, and random signal analysis that form the theoretical core of AI.
- The Hardware Foundation: Practical expertise in the electronic device physics, circuit design, and computer architecture that provides the necessary infrastructure for modern AI.
- Sector-Specific Transformation: The specialized knowledge to integrate AI into Telecommunications, Automation, Robotics and Power Systems—sectors where intelligent systems are currently driving radical change.
- Engineering Leadership: A comprehensive understanding of the managerial, ethical, and economic aspects required to lead complex engineering projects in a global market.
Programme Structure
The degree program is designed for completion within four academic years. Each academic year has 2 semesters of 15 week duration. During a single semester, a student can enroll up to 20 credits of courses being offered. The courses are organized at five different levels indicated by the course numbers in 1000, 2000, 3000, 4000 (based on academic year) and 5000 series (elective courses).
Credit Requirement of the EISE Program
| Sub-Classification | Credits | |
|---|---|---|
| Core Courses | Technical | 88 |
| Research Projects | 6 | |
| Industrial Training | 6 | |
| Elective Courses | Technical | 15 |
| General | 15 | |
| Total | 130 | |
Course Structure for the Electronic and Intelligent Systems Engineering
The EISE program has been developed in line with the academic quality assurance and outcome-based education principles associated with IESL accreditation and the Washington Accord framework. Accordingly, the program is structured to satisfy the academic pathway expected for professional engineering recognition through the IESL–ECSL framework, enabling graduates to pursue lawful engineering practice in Sri Lanka, subject to the professional requirements applicable at the time to engineering graduates of universities across the country.
| (YEAR) | SEMESTER | CODE | TITLE | CREDITS | Core /Optional |
|---|---|---|---|---|---|
|
(1) 1000 Level |
1 (19 Credits) |
EF1010 | English for Communication I | 3 | Core |
| EM1010 | Calculus I | 4 | Core | ||
| EE1010 | Electricity | 3 | Core | ||
| EE1050 | Analog Electronics | 3 | Core | ||
| EE1052 | Signals and Systems | 3 | Core | ||
| CO1010 | Programming for Engineers I | 3 | Core | ||
|
2 (18 Credits) |
EM1040 | Advanced Differential Equations | 3 | Core | |
| EM1020 | Linear Algebra | 3 | Core | ||
| EE1053 | Random Signal Analysis | 3 | Core | ||
| EE1051 | Fundamentals of Artificial Intelligence | 3 | Core | ||
| EE1020 | Electronic Device Physics | 3 | Core | ||
| CO1810 | Programming for Engineers II | 3 | Core | ||
|
(2) 2000 Level |
3 (18 Credits) |
EE2010 | Circuit Analysis | 3 | Core |
| EE2030 | Digital Logic Design and Synthesis | 3 | Core | ||
| EE2056 | Data Engineering for AI Systems | 3 | Core | ||
| EE2052 | Digital Signal Processing | 3 | Core | ||
| EE2053 | Automatic Control Systems | 3 | Core | ||
| Technical Elective | 3 | Elective | |||
|
4 (16 Credits) |
EE2054 | Embedded Systems Design | 3 | Core | |
| EE2060 | Electromagnetic Theory | 3 | Core | ||
| EM5050 | Complex Analysis | 3 | Core | ||
| CO2070 | Computer Architecture | 3 | Core | ||
| EE2051 | Advanced Artificial Intelligence | 3 | Core | ||
|
Short Semester 1 (9 Credits) |
General Electives x 3 | 9 | Elective | ||
|
(3) 3000 Level |
5 (15 Credits) |
EE3030 | Communication Systems | 3 | Core |
| EE3050 | Smart Systems Design Project | 3 | Core | ||
| EE3054 | Electric Power | 3 | Core | ||
| EE3051 | Intelligent Systems and Automation | 3 | Core | ||
| EE3055 | AI Systems Development management | 3 | Core | ||
| EF4010 | Industrial Training | 6 | Core | ||
|
Short Semester 2 (6 Credits) |
General Electives x 2 | 6 | Elective | ||
|
(4) 3000/4000 Level |
7 (12 Credits) |
Technical Electives x 2 | 6 | Elective | |
| EE3052 | Intelligent Systems Research Project I | 3 | Core | ||
| EE3053 | Intelligent Power Systems | 3 | Core | ||
|
8 (11 Credits) |
EE4052 | Intelligent Systems Research Project II | 3 | Core | |
| EE4053 | Ethics and Responsible AI | 2 | Core | ||
| Technical Electives x 2 | 6 | Elective |
Note: Semester 6 = Short Semester 1 + Short Semester 2
Note: The students will go on 24 weeks of industrial training (EF4010) after completion of semester 5.