Computer Science – Applied Statistics
Introduction
Vision & Mission
Program Objective
Expected Learning Outcomes
Prospective Career of The Graduate
Course Structure
Prerequisites
Quality Controlled Examination (UPM)
Introduction
Nowadays, all kinds of data are being generated when business processes are conducted or when enterprises interoperate. This vast amount of data is called as Big Data and it can be analysed using process-mining and data-mining techniques to understand how a business is performing and to identify new opportunities. The combination of Statistics and Computer Science into one program is designed to maximize the learning opportunities for the student in of handling Big Data, techniques for analyzing it, and simulation techniques for exploring the new business scenarios. This interdisciplinary study addresses the complexity of manipulating, analysing and using Big Data in business. The program can be completed within 4 - 4.5 years. Furthermore, to provide work experience for students, there are industrial internships, interesting research or entrepreneurship programs for 1 semester. Catalog 2017 (PDF), Catalog 2018 (PDF), Catalog 2019 (PDF), Catalog 2020 (PDF), Catalog 2021 (PDF), Catalog 2022 (PDF), Catalog 2023 (PDF)Vision
A World Class study program by providing excellent educational experiences in Statistical Computing, Fostering and Empowering the Society in Serving and Building the Nation.Source : BINUS UNIVERSITY OFFICIAL CURRICULUM SITE
Mission
The mission of Computer Science and Statistics Program is to contribute to the global community through the provision of world-class education by:- Educating students to effectively apply their educational experiences in Statistical Computing to solve real-world problems.
- Preparing our graduates to develop exemplary soft skills & technical skills required as ICT professionals, leaders and entrepreneurs in global market.
- Promoting high impact research that contributes to the nation.
- Fostering BINUSIAN as lifelong learners through self-enrichment.
- Empowering BINUSIAN to continuously improve society’s quality of life.
Program Objective
The objectives of the program are:- Graduates will become successful professionals in ICT fields;
- Graduates will obtain employment in global companies or become entrepreneurs;
- Graduates will obtain professional certification or continue their study to the postgraduate level;
- Graduate will have ability to pursue higher degree of education.
Student Outcomes
After completing the study, graduates are:- Able to analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions
- Able to design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of computer science
- Able to communicate effectively in a variety of professional contexts
- Able to recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles
- Able to function effectively as a member or leader of a team engaged in activities appropriate to computer science
- Able to apply computer science theory and software development fundamentals to produce computing-based solutions
- Able to conduct data management, including data design and collection in the form of surveys and experiments, data organization, exploration, and analysis based on statistical methods, using statistical software.
- Able to solve estimation problems and hypothesis testing through data utilization and several methods of estimation and hypothesis testing.
- Able to conduct data science project flow to solve real business and industry problems
- Able to develop software by implementing statistical models.
- Able to apply interdisciplinary knowledge and skills in developing alternative solutions for problem-solving
Prospective Career of the Graduates
The graduates of the double study program Statistics and Computer Science can follow careers in:- Business analyst, DSS Manager, or business strategist
- Actuary analyst, risk analyst, or quantitative credit analyst
- Strategy consultant or evaluator of company performance
- Data scientist, market researcher, or researcher of analysis techniques
- Database designer, database administrator, or system analyst
Course Structure for Binusian 2027
Appendix Foreign Language Courses
Code | Course Name | SCU |
ENGL6253049 | English for Frontrunners | 0 |
ENGL6254049 | English for Independent Users | 0 |
ENGL6255049 | English for Professionals | 0 |
JAPN6190049 | Basic Japanese Language | 0 |
CHIN6163049 | Basic Chinese Language | 0 |
- Students with Binus University English Proficiency Test score less than 437 are required to take English for Frontrunners and English for Independent Users.
- Students with Binus University English Proficiency Test score less than 520 are required to take English for Independent Users and English for Professionals.
- Students with Binus University English Proficiency Test score equal to or greater than 520 are required to take English for Professionals and choose Basic Japanese Language or Basic Chinese Language.
- Students can see the requirements to pass the foreign language courses at BINUSMAYA – Beelingua.
- Students are required to pass the foreign language courses before they take enrichment.
Track | Semester 8 | ||||||
IN | RS | EN | CD | SA | IS | etc | |
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Prerequisites for Binusian 2027
There is no prerequisite for this programQuality Controlled Courses for Binusian 2027
Student should pass all of these quality controlled courses as listed below:No | Course Code | Course Name | Minimal Grade |
1. | CHAR6013049 | Character Building: Pancasila | B |
2. | COMP6047049 | Algorithm and Programming* | C |
3. | COMP6798049 | Program Design Methods* | C |
4. | COMP6048049 | Data Structures* | C |
5. | STAT6185049 | Theory of Statistics I* | C |
6. | STAT6157049 | Data Mining and Visualization | C |
7. | MATH6187049 | Machine Learning | C |
8. | COMP6799049 | Database Technology | C |
9. | STAT6044049 | Categorical Data Analysis | C |
10. | STAT6048049 | Regression Analysis* | C |
11. | COMP6100049 | Software Engineering* | C |
12. | COMP6697049 | Operating System | C |
13. | STAT6053049 | Multivariate Statistics* | C |
14. | ENTR6511001 | Entrepreneurship: Market Validation | C |
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