Graduates of the Bachelor degree program in Data Science must meet the following
requirements (LO - Learning Outcome):
● LO 1: Have fundamental knowledge of science and social science.
● LO 2: Have fundamental and advanced knowledge of Data Science (be able to
use statistical programming languages, data analysis tools, etc)
● LO 3: Be capable of reasoning, analyzing, forecasting, senior statistics and
solving problems related to Data Science.
● LO 4: Have skills in scientific research and knowledge discovery (document
survey, analysis, evaluation).
● LO 5: Have a systematic mindset and be able to design components or entire
systems that collect and analyze data.
● LO 6: Have personal and professional skills, understand the ethical values, and
lifelong learning abilities.
● LO 7: Have teamwork skills with professional manners.
● LO 8: Have communication skills.
● LO 9: Be able to use foreign languages in specialized field.
● LO 10: Understand social needs, the impact of big data mining technologies in
the context of industrial revolution 4.0. Be able to form ideas, analyze, design,
and apply statistical tools and apply Data Science applications into practice to
meet social needs, solve economic problems, and improve competitiveness,
development, entrepreneurship and creativity.
1. Overview
1.1 Education outcomes
Providing high quality human resources with strong professional skills and excellent knowledge in Data science. Undegraduates receive in-depth training with IT and Data science, good health and morality to work and research in data science and artificial intelligent.
1.2 Career opportunities
Student after graduated from Data science program are capable for these positions:
- Data analyst or data statistic. Be able to analyze, synthesize, and building forecast model based on data.
- Data engineering. Be able to build software for analyzing data, building distributed data system, making query and extracting information from data.
- Researcher in data science. Be able to work and operate with big data, select optimization data model, and conduct quantitative analysis in business and stock.
- Be able to work as lecturer or researcher at academic organizations.
1.3 Viewpoints of educational program.
Educating high quality student with strong IT-skills and research skills in data science: collecting data, cleaning data , classifying data, analyzing data, making statistical inference, and synthesizing data.
Data science students are able to work and research with data in many fields: science data, economical data, social data, and stock data.
1.4 Education time
- Type of training: Full-time
- Time: 4 years (8 semesters).
- Qualification: Bachelor of Data science.
2. University entrances
- Option 1: Passed the National University Entrance Exam.
- Option 2: Directly admission: candidates with Gold medal, Silver medal, and Bronze medal from National Teams for the Gifted or Olympic Teams about Information Technology.
3. Education Policies
2019
Nguyễn Đình Long, Ngô Hồng Phúc, Nguyễn Gia Tuấn Anh: Phát Triển Hợp Đồng Mua Bán Thông Minh Trên Thiết Bị Di Động Bằng Công Nghệ Blockchain, Hội nghị Khoa học trẻ và Nghiên cứu sinh tháng 5, 2019, Hồ Chí Minh, Việt Nam. (Sinh viên Nguyễn Đình Long và Ngô Hồng Phúc thuộc lớp CNTT2015).
Tin Van Huynh, Duc-Vu Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen, Anh Gia-Tuan Nguyen. Hate Speech Detection on Vietnamese Social Media Text using the Bi-GRU-LSTM-GRU Model. The Sixth International Workshop on Vietnamese Language and Speech Processing VLSP 2018 - in conjunction with the international conference PACLING 2019, 10/2019, Hanoi. (Sinh viên Huỳnh Văn Tín thuộc lớp CNTT2016).
Hang Thi-Thuy Do, Huy Duc Huynh, Duc-Vu Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen, Anh Gia-Tuan Nguyen. Hate Speech Detection on Vietnamese Social Media Text using the Bidirectional-LSTM Model. The Sixth International Workshop on Vietnamese Language and Speech Processing VLSP 2019 - in conjunction with the international conference PACLING 2019, 10/2019, Hanoi. (Sinh viên Đỗ Thị Thúy Hằng và Huỳnh Đức Huy thuộc lớp CNTT2016).
2018
Kiet Van Nguyen, Vu Duc Nguyen, Phu Xuan-Vinh Nguyen, Tham Thi-Hong Truong, Ngan Luu-Thuy Nguyen, UIT-VSFC: Vietnamese Students' Feedback Corpus for Sentiment Analysis, 2018 10th International Conference on Knowledge and Systems Engineering (KSE 2018), November 1-3, 2018, Ho Chi Minh City, Vietnam. (Sinh viên Nguyễn Xuân Vĩnh Phú và Trương Thị Hồng Thắm thuộc lớp CNTT2014).
Phu Xuan-Vinh Nguyen, Tham Thi-Hong Truong, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen, Deep Learning versus Traditional Classifiers on Vietnamese Students' Feedback Corpus, The 5th NAFOSTED Conference on Information and Computer Science (NICS 2018), November 23-24, 2018, Ho Chi Minh, Vietnam. (Sinh viên Nguyễn Xuân Vĩnh Phú và Trương Thị Hồng Thắm thuộc lớp CNTT2014).
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1. Principal subjects
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No.
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Code
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Course name
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1 |
IT001 |
Introduction to Programming
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2 |
IT003 |
Data Structure and Algorithm
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2. Fundamental subjects
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No.
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Code |
Course name |
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1 |
IE101
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Information Technology Infrastructure
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2 |
IE103
|
Information Management
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3 |
IE104
|
Internet and Web Technology
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4 |
IE105
|
Introduction to Information Assurance and Security
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5 |
IE106
|
User Interface Design
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6 |
SE104
|
Introduction to Software Engineering
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|
7 |
IS402
|
Cloud Computing
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3. Advance subjects
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No.
|
Code |
Course name |
|
1 |
IE201
|
Analysis of Statistical Data
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2 |
IE212
|
Big Data
|
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3 |
IE221
|
Introduction to Python Programming
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4 |
IE222
|
Introduction to data analysis
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5 |
IE309
|
Internship
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6 |
IE202
|
Business Management
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|
7 |
IE203
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Bussiness Process Management Systems
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8 |
IE301
|
Customer Relationship Management
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9 |
IE302
|
System Integration and Architecture
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|
10 |
IE102
|
Platform Technologies
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|
11 |
IE204
|
Search Engine Optimization (SEO)
|
|
12 |
IE213
|
Web Application Development
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|
13 |
IE303
|
Java Technology
|
|
14 |
IE307
|
Multi-platform mobile application Development
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15 |
IE205
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Satellite Image Processing
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16 |
IE304
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Global Positioning System (GPS)
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17 |
IE305
|
Tin học môi trường
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4. Graduation subjects
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No.
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Code |
Course name |
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1 |
IE401
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Environmental Informatics
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2 |
IE402
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Three- Dimentional Geographic Information System
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3 |
IE403
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Social Media Mining
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4 |
IE405
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Big data analysis
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5 |
IE406
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Introduction to Data hiding and Applications.
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