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 2016 (PDF), Catalog 2017 (PDF), Catalog 2018 (PDF), Catalog 2019 (PDF),
Catalog 2020 (PDF), Catalog 2021 (PDF)
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.
*) This course is delivered in English**) Global Learning System Course Free Electives:
-) For Free Electives, students are required to choose from the list of Free Electives in Appendix.English University Courses:
-) For English University Courses, students with Binus University English Proficiency Test scores less than 500 will take English Savvy, and students with test scores greater than or equal to 500 will take English for Written Business Communication.
-) Students must pass English Savvy with a minimum Grade of C.Appendix: Free Electives (7th Semester)
Because free electives will be implemented on the 7th semester, data will be collected from Curriculum 2022Enrichment Program (8th Semester):
-) Student will take one of enrichment program tracks (off campus). See enrichment appendix for the tracks detail.Enrichment Track Scheme
IN : Certified Internship
RS : Certified Research
EN : Certified Entrepreneurship
CD : Certified Community Development
SA : Certified Study Abroad
IS : Certified Specific Independent Study
etc : Study Program Special Purposes
Student will take one of enrichment program tracks
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