Statistics and Data Science

Core Focus Areas
  1. Big Data Analytics – Extracting insights from large-scale data for strategic decision-making.
  2. Machine Learning & AI Applications – Developing predictive models for automation and intelligent systems.
  3. Statistical Modeling & Inference – Applying advanced statistical techniques for data-driven decisions.
  4. Business & Industrial Data Science – Optimizing operations using data-driven methodologies.

 

Career Prospects
Career Path Industries
Data Scientist Technology, Finance, Healthcare, Retail
Business Intelligence Analyst Banking, E-commerce, Consulting, Telecommunications
Statistical Consultant Government, Academia, Research Institutions
AI & Machine Learning Engineer Tech Companies, Autonomous Systems, Smart Cities

 

Real-World Applications
  • Fraud Detection – Identifying fraudulent activities in banking and e-commerce.
  • Healthcare Analytics – Predicting disease trends and optimizing hospital resource allocation.
  • Personalized Marketing – Customer segmentation and recommendation systems.
  • Risk Analysis for Financial Markets – Developing models for investment and risk management.

 

Curriculum

In the Curriculum 2021, some courses are accompanied by laboratory works. The international class is divided into 2 (two)
groups of courses:

  1. The core courses (134 credits)
  2. The elective focused courses (at least 15 credits).

 

List of Core Courses

SEMESTER I (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMM-1101 Calculus I 3 – Department of Mathematics
2 MFF-1011 Physics I 3 – Department of Physics
3 MKK-1101 Fundamental Chemistry I 3 – Department of Chemistry
4 MII21-1201 Programming 3 – Department of Computer Science and Electronics
5 MII21-1202 Lab Work in Programming 1 – Department of Computer Science and Electronics
6 MMS-1411 Statistical Methods 4 – Lab. of Statistics
7 MMS-1413 Lab Work in Statistical Methods 4 MMS-1411** Lab. of Statistics
8 UNU-222X Religion 2 – University
9 MMM-1401 Pancasila 2 – University
Total Credits 22    

SEMESTER II (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMM-1102 Calculus II 3 MMM-1101* Lab. of Analysis
2 MMS-1414 Exploratory Data Analysis 3(1) MMS-1411*, MMS-1413* Lab. of Statistics
3 MMS-1415 Matrix Algebra 2 – Lab. of Algebra
4 MMS-1418 Discrete Mathematics and Combinatorics 2 – Lab. of Statistics
5 MMS-1419 English 3 – University
6 MMS-1416 Basis Data 3(1) – Lab. of Statistics
7 MMS-1417 Applied Regression Analysis 3(1) MMS-1411*, MMS-1413* Lab. of Statistics
8 MMS-1418 Probability and Stochastic Processes 3 – Lab. of Applied Mathematics
9 UNU222013 Bahasa 2 – University
Total Credits 24    

SEMESTER III (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMS-2429 Survey Sampling Methods 3 MMS-1411*, MMS-1413* Lab. of Statistics
2 MMM-2428 Multivariable Calculus for Statistics 2 MMM-1202* Lab. of Statistics
3 MMM-2301 Elementary Differential Equations 3 MMM-1102* Lab. of Applied Mathematics
4 MMS-2420 Introduction to Mathematical Statistics I 3 MMM-1102* Lab. of Statistics
5 MMS-2430 Introduction to Experimental Design 2 MMS-1411*, MMS-1413* Lab. of Statistics
6 MMM-2111 Advanced Calculus 2 MMM-1102* Lab. of Analysis
7 MMS-2422 Statistical Computation I 3(1) – Lab. of Statistical computation
8 MMS-2423 Applied Multivariate Statistics 3(1) MMS-2420** Lab. of Statistics
Total Credits 21    

SEMESTER IV (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMS-2483 Introduction to Mathematical Statistics II 3 MMM-2420* Lab. of Statistics
2 MMS-2431 Official Statistics 2 – Lab. of Statistics
3 MMS-2433 Introduction to Data Science 2 MMM-2432* Lab. of Statistics
4 MMS-2434 Statistical Computation II 3(1) MMS-2422* Lab. of Statistical Computation
5 MMS-2435 Introduction to Data Mining 3(1) – Lab. of Statistical Computation
Total Credits 13    

SEMESTER V (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMS-3436 Practical Work 3 ≥ 80 SKS Lab. of Statistics
2 MMS-3446 Introduction to Measurement and Probability Theory 2 MMM-1102* Lab. of Statistics
3 UNU222012 Civic 2 – University
4 MMM-3429 Introduction to Time Series 3(1) MMM-2420* Lab. of Statistics
Total Credits 10    

SEMESTER VI (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1   Visiting the university partners* ≥ 5 credits ≥ 100 credits without grade E University partner
    OR      
2 UNU222001 Community Development Participation 4 ≥ 96 credits without grade E University
3 UNU222002 Community Communication 2 ≥ 96 credits without grade E University
4 UNU222004 Application to Knowledge Management 2 ≥ 96 credits without grade E University
Total Credits ≥ 13    
 

SEMESTER VII/VIII (the core courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMS-4091 Visiting the university partners*** ≥ 5 credits ≥ 100 credits without grade E University partner
2 MMS-4437 Final Assignment I 3 ≥ 120 credits Undergraduate Program
3 MMS-4438 Final Assignment II 6 Final Assignment I Undergraduate Program
Total Credits ≥ 14    

 

List of Elective Courses

FALL SEMESTER (the elective courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMS-4449 Capita Selecta in Statistics A 3 MMS-2483* Lab. of Statistics
2 MMA-2505 Generalized Linear Model 3 MMS-1417* Lab. of Statistics

SPRING SEMESTER (the elective courses)

No. Code Course Credits Prerequisite Organizer / Group in charge
1 MMS-2427 Forecasting Methods 3(1) MMS-1411*, MMS-1413* Lab. of Statistics
2 MMS-3431 Nonparametric Statistics 3 MMS-1411*, MMS-1413* Lab. of Statistics
3 MMS-3435 Structural Equation Modelling 3 MMS-2432*, MMS-1413* Lab. of Statistics
4 MMS-3445 Introduction to Econometrics 3(1) MMS-1411*, MMS-1413* Lab. of Statistics
5 MMS-3448 Statistical Machine Learning 3 MMS-2435* Lab. of Statistics
6 MMS-4423 Capita Selecta in Statistics B 3 – Lab. of Statistics
7 MMS-4416 Introduction to Analysis of Panel Data 3 MMS-2420* Lab. of Statistics

 

∗ : has been taken and completed the final exam
∗∗ : can be taken simultaneously
∗∗∗ : required to be taken for the international class

Note:
Capita Selecta A and B courses must align with the interests in data science and statistics.

 

The syllabi for Statistics and Data Science can be accessed through the following link external link.