Data Science and Analytics
2
Years
22
Subjects
76
Credits
$1,250 /year
Tuition Fee
This program is designed to provide practical knowledge on how to develop an interdisciplinary field that combines scientific methods, processes, algorithms, and systems to extract knowledge and understanding from structured and unstructured data. It involves techniques such as data mining, machine learning, statistical analysis, and visualization to reveal patterns, trends, and correlations in large data sets.
Total Duration
1599 Hours (Physical Class)
Admission Fee
500 USD
| Semester | Subjects | Hours | Code |
|---|---|---|---|
| S1 | Computer Literacy | 45 | FD001 |
| Japanese Culture and Communication | 45 | FD002 | |
| Professional Life and Humanities in Leadership | 45 | SK001 | |
| Linar Algebra and Calculus | 45 | DS001 | |
| C++ Programming | 60 | DS002 | |
| S2 | Microsoft Excel Advanced | 45 | DS003 |
| Statisctics | 45 | DS004 | |
| Data Visualisation | 45 | DS005 | |
| Data Cleaning | 30 | DS006 | |
| Python Programming | 60 | DS007 | |
| SQL | 45 | DS008 | |
| S3 | Microsoft PowerBI | 45 | DS009 |
| Tableau | 30 | DS010 | |
| Programming in R | 45 | DS011 | |
| Machine Learning | 45 | DS012 | |
| NoSQL | 45 | DS013 | |
| SSIS | 45 | DS014 | |
| S4 | Communication and Ethics in Working Professionals | 45 | SK002 |
| Project and Research Methodology | 45 | RS001 | |
| Intership Program | 504 | PR001 | |
| Tech Startup Project and Research (TSPR) | 240 | RS002 | |
| Total: | 1599 | ||
Learning Outcome
- Understand the fundamental concepts and principles of data science
- How to organize, analyze, and visualize data
- Be able to statistic software and libraries for data analysis
- Be able to use big data technologies and tools to efficiently process large data sets
- Be able to ethical considerations and best practices regarding the management of confidential data.
Career Path Expectation
- Data Scientist or Data Analyst or Information Scientist
- Computer Scientist
- Data Engineer
- Data Researcher
- Consultant/Advisor
- Machine Learning Engineer
- Business Intelligence Analyst
