Undergraduate Programme
Artificial
Intelligence
Curriculum Handbook
2026 Revision · Product-Oriented Track
8 Semesters |
144 Credits |
52 Courses |
6 Phases |
8 Semesters |
144 Credits |
52 Courses |
6 Phases |
A short introduction to this curriculum
Most AI programmes finish where this one turns the corner. Training a model that scores well on a held-out set is a solved teaching problem; what remains scarce is the graduate who can decide which model is worth building, design the system it lives inside, ship it to people who did not ask for a model, and explain what it costs. Every course here is written toward that end.
No. Deep learning, computer vision, natural language processing, generative models, and MLOps each get a full three-credit course, and the mathematics beneath them, linear algebra, discrete mathematics, logic, numerical methods, is front-loaded into the first two semesters. What changes is the framing: the final learning outcome of nearly every course asks the student to connect the technique to a user, a cost, or a decision.
The arc is cumulative. Semesters 1 and 2 lay mathematics, programming, and data foundations. Semester 3 introduces machine learning and language models beside product management and system design. Semester 4 goes deep into vision, language, and deployment. Semester 5 converges everything onto delivery. Semesters 6 and 7 turn outward under Kampus Berdampak, where approved placement hours convert into course credit. Semester 8 closes with a defended capstone.
How to read this book. Each semester page lists every course by code, name, and credit weight, grouped by category. The progression ladder gives the full six-phase shape at a glance before the semester-by-semester detail begins.
Artificial Intelligence · Curriculum Handbook 202602What this curriculum is organised by
Artificial Intelligence here is not a sequence of algorithms with an application chapter at the end. The organising unit is the product: what it is for, how it is designed, how it is trained, how it ships, and who it affects. Three principles run through every phase.
The learning outcomes are written so that each course ends where it meets a user. Computer Architecture closes on compute trade-offs for an AI product; Data Structures closes on speed and cost; even Discrete Mathematics closes on turning product requirements into formal structures.
Semester 3 runs Machine Learning, AI Product Management, and AI System Design in parallel rather than in sequence. A student meets the algorithm, the requirement it answers, and the architecture it must fit within the same term.
Semesters 6 and 7 turn outward. Time in an approved industry placement is not extra to the semester, it is the semester, converted directly into SKS through the four-credit courses carried out there.
Artificial Intelligence · Curriculum Handbook 202603The problem this programme is built to solve
Able to take an AI capability the whole way: identify where it creates measurable value, design the system around it, train and evaluate the model honestly, deploy it so it keeps running, and explain its limits to the people who have to trust it.
Organisations are not short of models. They are short of people who can tell which problem deserves one, what it will cost to run, and how to tell whether it is working after launch. The gap is rarely the algorithm, it is everything on either side of it.
These are the entry roles the early semesters are explicitly mapped to. Later semesters point toward ML engineering, AI solution architecture, and AI product management.
Artificial Intelligence · Curriculum Handbook 202604Structure in numbers
8 Semesters |
144 Total Credits |
52 Courses |
6 Curriculum Phases |
The eight semesters are organised around six phases rather than a flat sequence: Foundation, Core Systems, AI Core across two semesters, Product Practice, Kampus Berdampak across two semesters, and the Capstone. The order is deliberate: mathematics and programming are laid together, AI technique is introduced alongside the product discipline that gives it a purpose, that breadth converges on delivery in Semester 5, and the result is then tested in the field through a structured placement whose hours convert directly into semester SKS.
Semesters 3, 4, and 5 carry the heaviest classroom load, 21 SKS each. That weight is placed before the placement years by design, so that a student arrives at an industry desk with the technical range already in hand.
Each phase is defined by one verb. The full ladder is on the next page.
Artificial Intelligence · Curriculum Handbook 202605From first program to a defended product
| S1 | GroundLinear algebra, discrete mathematics, and logic arrive alongside the first Python program, so the notation and the code are learned as one thing. |
| S2 | BuildObjects, data structures, databases, and statistical inference, plus a first survey of what AI can and cannot do. |
| S3 | ModelMachine learning and large language models taught in the same term as product management, system design, and AI ethics. |
| S4 | ApplyDeep learning, vision, and language, and the MLOps discipline that carries a trained model into something that keeps running. |
| S5 | DeliverGenerative AI, cloud, architecture, and business. The technical breadth converges on shipping a product and defending it. |
| S6 | ImmerseKampus Berdampak begins: architecture, strategy, and product engineering carried out inside an approved placement, credited into the semester's SKS. |
| S7 | ImmersePlacement continues, a second full semester of supervised field experience converted into course credit. |
| S8 | MasterCapstone: a complete AI product, built and defended, often while a placement continues in parallel. |
Artificial Intelligence · Curriculum Handbook 202606Courses and credits, semester by semester
| Semester | Focus | Courses | SKS | Note |
|---|---|---|---|---|
| Semester 1 | Foundation | 8 | 19 | Mathematics and code together |
| Semester 2 | Core Systems | 8 | 20 | Engineering and data |
| Semester 3 | AI Core | 8 | 21 | Model, problem, and system |
| Semester 4 | Applied AI | 7 | 21 | Vision, language, deployment |
| Semester 5 | Product Practice | 7 | 21 | Converging on delivery |
| Semester 6 | Kampus Berdampak I | 6 | 18 | Field placement plus concentration work |
| Semester 7 | Kampus Berdampak II | 6 | 16 | Placement continues |
| Semester 8 | Ending. Capstone | 2 | 8 | Capstone plus research |
| Total | 52 | 144 | Two credits below the 146 minimum |
Reading the notes. Semesters 3, 4, and 5 are the heaviest classroom terms at 21 SKS each, deliberately placed before the placement years. Semesters 6 and 7 look lighter on paper but are delivered in the field: their four-credit courses are carried out inside an approved industry placement under Kampus Berdampak. Semester 8 pairs the capstone with the tail end of that placement where a student chooses to continue it.
The programme currently totals 144 SKS against a 146 SKS minimum. Note also that Indonesian Way of Life / Pancasila is listed twice, in Semester 3 and again in Semester 6, at 2 SKS each; if that is a duplication rather than a two-part sequence, removing one instance widens the gap to four credits.
Artificial Intelligence · Curriculum Handbook 202607What Semester 5 is for
Semester 5 is not a choice between tracks. Every student takes all seven courses. The three strands below describe the roles those courses prepare a student to hold on a real team, not alternatives to pick between.
ABuild GENERATIVE AI, CLOUD, SOFTWARE ENGINEERING Making the thing work: generative models, the infrastructure to run them, and the engineering discipline to keep the codebase alive. Role focus ML Engineer
| BArchitect AI SOLUTION ARCHITECTURE Deciding how the pieces fit: data, model, and serving components designed as one system with explicit trade-offs. Role focus AI Solution Architect
| CDeliver PRODUCT, COMMUNICATION, BUSINESS Getting it adopted: taking a prototype to a real user, explaining it to non-technical stakeholders, and arguing its business case. Role focus AI Product Manager
|
By the end of this term a student should be able to sit in any of the three seats on a small AI team and understand what the other two are worried about. That is the specific competence the placement years are about to test.
The claim is testable at the end of Semester 5, before any placement begins: a student who has taken Generative AI, Cloud Computing, Software Engineering, AI Solution Architecture, AI Product Development, Data & AI Communication, and AI for Business in a single term has been asked, seven times over, to finish the same sentence, this is who it is for and this is what it costs.
Artificial Intelligence · Curriculum Handbook 202608| Kode | Mata Kuliah | SKS |
|---|---|---|
| Wajib | ||
| SAI1101 | Discrete Mathematics | 3 |
| SAI1205 | Fundamentals of Linear Algebra | 3 |
| SAI1102 | Intro to Computer Programming | 3 |
| SAI1103 | Project-Based Programming (Python) | 3 |
| SAI1202 | Computational Logic | 2 |
| SAI1104 | Digital Transformations | 2 |
| SAI1201 | Computer Architecture | 2 |
| Umum | ||
| WUC1118 | Career Development I | 1 |
Linear algebra, discrete mathematics, and logic arrive in the same term as the first Python program. The intent is that a matrix and a tensor are introduced as the same object seen twice, once on paper and once in code.
Artificial Intelligence · Curriculum Handbook 202609| Kode | Mata Kuliah | SKS |
|---|---|---|
| Wajib | ||
| CIK2108 | Object-Oriented Programming | 3 |
| CIK2109 | Data Structures | 3 |
| Statistical Thinking | 3 | |
| CIK3102 | Numerical Methods | 2 |
| CIK4105 | Database System | 3 |
| Introduction to AI | 2 | |
| CIK1109 | Human-Computer Interaction | 3 |
| Umum | ||
| WUC1120 | Career Development II | 1 |
Artificial Intelligence · Curriculum Handbook 202610| Kode | Mata Kuliah | SKS |
|---|---|---|
| Wajib | ||
| WUC1113 | Design Thinking | 2 |
| CIK4101 | Data Mining and Warehousing | 3 |
| Machine Learning | 3 | |
| Large Language Models | 3 | |
| AI Product Management | 3 | |
| AI System Design | 3 | |
| Data Security and AI Ethics | 2 | |
| Umum | ||
| WUC1111 | Indonesian Way of Life / Pancasila | 2 |
Machine Learning, AI Product Management, and AI System Design run in the same term on purpose. A model, the problem it serves, and the system it lives inside are taught as one subject rather than three.
Artificial Intelligence · Curriculum Handbook 202611| Kode | Mata Kuliah | SKS |
|---|---|---|
| Wajib | ||
| CIK3101 | Web Application Development | 3 |
| Deep Learning | 3 | |
| Natural Language Processing | 3 | |
| Computer Vision | 3 | |
| Digital Image Processing | 3 | |
| Model Deployment / MLOps | 3 | |
| CIK2110 | Web Client Development | 3 |
Artificial Intelligence · Curriculum Handbook 202612| Kode | Mata Kuliah | SKS |
|---|---|---|
| Wajib | ||
| Generative AI | 3 | |
| Cloud Computing | 3 | |
| Software Engineering | 3 | |
| AI Solution Architecture | 3 | |
| AI Product Development | 3 | |
| Data & AI Communication | 3 | |
| AI for Business | 3 | |
Seven courses, one direction. Every subject this term is about getting a working AI system in front of a real user and being able to justify it, technically and commercially.
Artificial Intelligence · Curriculum Handbook 202613| Kode | Mata Kuliah | SKS |
|---|---|---|
| Konsentrasi | ||
| AI Solutions Architecture | 4 | |
| AI Strategy and Innovation | 4 | |
| AI Product Engineering | 4 | |
| Pendukung | ||
| WUC1115 | Technical / Professional Writing | 2 |
| Umum | ||
| WUC1111 | Indonesian Way of Life / Pancasila | 2 |
| WUC2109 | Civic / Kewarganegaraan | 2 |
Kampus Berdampak. Semester 6 opens the placement track: the three four-credit courses are carried out on real organisational problems, and approved placement hours convert directly into SKS.
Artificial Intelligence · Curriculum Handbook 202614| Kode | Mata Kuliah | SKS |
|---|---|---|
| Konsentrasi | ||
| AI-Driven Decision Making | 4 | |
| AI Requirements Discovery | 4 | |
| Pendukung | ||
| WUC1122 | Professional Ethics | 2 |
| Umum | ||
| WUC1101 | Religions | 2 |
| WUC1108 | English | 2 |
| WUC2107 | Applied Indonesian Language | 2 |
Credit conversion continues through Semester 7, so the two semesters function as one continuous placement rather than two separate terms.
Artificial Intelligence · Curriculum Handbook 202615| Kode | Mata Kuliah | SKS |
|---|---|---|
| Capstone | ||
| WUC1114 | Capstone Project | 6 |
| Pendukung | ||
| CIK1103 | Research Methodology | 2 |
Students may continue their Kampus Berdampak placement through Semester 8 while completing and defending the capstone, so placement and closing project run side by side rather than one blocking the other.
Artificial Intelligence · Curriculum Handbook 202616Artificial Intelligence moves from first program to defended capstone in eight semesters: mathematics and code laid together, machine learning taught beside the product discipline that gives it a purpose, a semester spent converging on delivery, two semesters inside industry, and a capstone that has to work in front of an audience.