Computer Science-Statistics 54 months Undergraduate Programme By Bina Nusantara University (BINUS) |TopUniversities

Programme overview

Main Subject

Computer Science and Information Systems

Degree

Other

Study Level

Undergraduate

Study Mode

On Campus

The Dual Computer Science – Statistics program at BINUS University is designed to equip students with a comprehensive combination of computing and data analysis skills, answering the industry's need for talent capable of processing and interpreting data at scale. This program integrates the principles of computer science, statistics, and database management, so that students not only understand theory, but are also able to build data-based solutions end-to-end, from data collection, processing, modeling, to data interpretation and visualization. Students will receive intensive material briefing in programming languages such as Python and R, as well as the use of modern statistical and analytical tools. The curriculum covers a wide range of topics ranging from sampling techniques, data wrangling, modeling with statistical learning and machine learning, data visualization, spatio-temporal analysis, actuarial fundamentals, to data-based decision-making. In addition, the project-based learning approach and real-life case studies will help students understand practical applications in various sectors, such as finance, technology, digital marketing, manufacturing, public services, and healthcare.

Programme overview

Main Subject

Computer Science and Information Systems

Degree

Other

Study Level

Undergraduate

Study Mode

On Campus

The Dual Computer Science – Statistics program at BINUS University is designed to equip students with a comprehensive combination of computing and data analysis skills, answering the industry's need for talent capable of processing and interpreting data at scale. This program integrates the principles of computer science, statistics, and database management, so that students not only understand theory, but are also able to build data-based solutions end-to-end, from data collection, processing, modeling, to data interpretation and visualization. Students will receive intensive material briefing in programming languages such as Python and R, as well as the use of modern statistical and analytical tools. The curriculum covers a wide range of topics ranging from sampling techniques, data wrangling, modeling with statistical learning and machine learning, data visualization, spatio-temporal analysis, actuarial fundamentals, to data-based decision-making. In addition, the project-based learning approach and real-life case studies will help students understand practical applications in various sectors, such as finance, technology, digital marketing, manufacturing, public services, and healthcare.

Admission Requirements

54 Months

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