No |
Subject code |
Subjects |
Credits |
Credit hours |
Pre-requisite (s) subject code |
||
Theory |
Practice |
Self-study |
|||||
I |
General knowledge module (Subject 8-9 are not included) |
21 |
|
|
|
|
|
1 |
PHI1006 |
Marxist-Leninist Philosophy |
3 |
30 |
15 |
0 |
|
2 |
PEC1008 |
Marx-Lenin Political Economy |
2 |
20 |
10 |
0 |
PHI1006 |
3 |
PHI1002 |
Scientific Socialism |
2 |
30 |
0 |
0 |
|
4 |
HIS1001 |
Revolutionary Guidelines of Vietnam Communist Party |
2 |
20 |
10 |
0 |
|
5 |
POL1001 |
Ho Chi Minh’s Ideology |
2 |
20 |
10 |
0 |
|
6 |
FLF1107 |
English B1 |
5 |
20 |
35 |
20 |
|
7 |
FLF1108 |
English B2 |
5 |
20 |
35 |
20 |
|
8 |
|
Physical Education |
4 |
|
|
|
|
9 |
|
National Defence Education |
8 |
|
|
|
|
II |
Field-Based Knowledge |
23 |
|
|
|
|
|
10 |
INS1014 |
English for Academic Purposes 1 |
4 |
30 |
30 |
0 |
|
11 |
INS1053 |
Introduction to BDA |
2 |
15 |
15 |
0 |
|
12 |
INT1004 |
Introduction to Informatics 2 |
3 |
17 |
28 |
0 |
|
13 |
MAT1092 |
Advanced Mathematics |
4 |
45 |
15 |
0 |
|
14 |
MAT1004 |
Theory of Probability and Mathematical Statistics |
3 |
27 |
18 |
0 |
|
15 |
INS2065 |
Computer Based Technologies |
2 |
18 |
12 |
0 |
INT1004 |
16 |
INS2020 |
Programming 1 |
3 |
30 |
15 |
0 |
|
17 |
PSY1050 |
Introduction to Psychology |
2 |
24 |
6 |
0 |
|
III |
Area-Based Knowledge |
14 |
|
|
|
|
|
18 |
INS3009 |
Entrepreneurship |
3 |
36 |
9 |
0 |
|
19 |
THL1057 |
Introduction to Law |
2 |
24 |
6 |
0 |
|
20 |
INE1050 |
Microeconomics |
3 |
36 |
9 |
0 |
|
21 |
INE1051 |
Macroeconomics |
3 |
36 |
9 |
0 |
|
22 |
INS2019 |
Business Organization and Management |
3 |
36 |
9 |
0 |
|
IV |
Discipline-Based Knowledge |
24 |
|
|
|
|
|
IV.1 |
Compulsory subjects |
18 |
|
|
|
|
|
23 |
INS3063 |
Enterprise Analytics for Decision Support |
3 |
27 |
18 |
0 |
|
24 |
INS3062 |
Principles of Information Security |
3 |
27 |
18 |
0 |
INS2025 |
25 |
INS2023 |
Operations Management |
3 |
36 |
9 |
0 |
INS2019 |
26 |
INS2037 |
Business Information Systems and Processes |
3 |
27 |
18 |
0 |
INT1004
|
27 |
INS2051 |
Quantitative Methods for Management |
3 |
27 |
18 |
0 |
MAT1004 |
28 |
INS2055 |
Database Systems |
3 |
27 |
18 |
0 |
INT1004 |
IV.2 |
Elective subjects |
06/18 |
|
|
|
|
|
29 |
INS2022 |
Legal, Ethical, Social Environment of Business |
3 |
27 |
18 |
0 |
THL1057 |
30 |
INS2058 |
Intellectual Property Rights |
3 |
27 |
18 |
0 |
THL1057 |
31 |
INS2053 |
Web Authoring and Web Management |
3 |
27 |
18 |
0 |
INT1004 |
32 |
INS3066 |
Enterprise Business Solutions |
3 |
27 |
18 |
0 |
INS2023 |
33 |
INS3059 |
IT Project Management |
3 |
27 |
18 |
0 |
INS2023 |
34 |
INS2060 |
IT and Business Innovation |
3 |
27 |
18 |
0 |
INS2019 |
V |
Specialized Knowledge |
63 |
|
|
|
|
|
V.1 |
Compulsory subjects |
28 |
|
|
|
|
|
35 |
INS2004 |
Economic Statistics |
3 |
27 |
18 |
0 |
MAT1004 |
36 |
INS2061 |
Data Mining and Business Analytics |
3 |
27 |
18 |
0 |
MAT1004 INS2055 |
37 |
INS3073 |
Data Warehousing and Business Analytics |
3 |
30 |
15 |
0 |
INS3063 |
38 |
INS3047 |
Python programming |
3 |
27 |
18 |
0 |
INS2020 |
39 |
INS3048 |
Optimization in Quantitative Management |
3 |
27 |
18 |
0 |
INS2051 |
40 |
INS3049 |
Econometrics |
4 |
40 |
20 |
0 |
MAT1004 |
41 |
INS3050 |
Data Structures and Algorithms |
3 |
27 |
18 |
0 |
INS2020 |
42 |
INS3075 |
Seminar |
3 |
27 |
18 |
0 |
|
43 |
INS3008 |
Project |
3 |
27 |
18 |
0 |
|
V.2 |
Elective subjects |
06/15 |
|
|
|
|
|
44 |
INS3060 |
E-Commerce |
3 |
27 |
18 |
0 |
|
45 |
INS3076 |
Big Data Analytics |
3 |
27 |
18 |
0 |
|
46 |
INS3046 |
Machine Learning |
3 |
27 |
18 |
0 |
MAT1004 |
47 |
INS3061 |
Enterprise Information Systems |
3 |
27 |
18 |
0 |
INS2019 INS2037 |
48 |
INS3021 |
Supply Chain Management |
3 |
27 |
18 |
0 |
INS2019 |
V.3 |
Elective courses/ Specialized and supplementary courses |
04/10 |
|
|
|
|
|
49 |
INS1005 |
IT Research Methodology |
2 |
18 |
12 |
0 |
INS1016 |
50 |
INS2059 |
Leadership and Team Building |
2 |
18 |
12 |
0 |
INS1016 |
51 |
INS3077 |
Big Data, Big Responsibilities: The Law and Ethics of Business Analytics |
2 |
20 |
10 |
0 |
|
52 |
INS3078 |
Management Science |
2 |
18 |
12 |
0 |
INS2051 |
53 |
SOC1050 |
Introduction to Sociology |
2 |
24 |
6 |
0 |
|
V.4 |
Selected in-depth knowledge electives |
15 |
|
|
|
|
|
V.4.1 |
Analytical models development |
15 |
|
|
|
|
|
54 |
INS3079 |
Statistical Models for Data Analysis 1 |
3 |
27 |
18 |
0 |
|
55 |
INS3082 |
Statistical Models for Data Analysis 2 |
3 |
27 |
18 |
0 |
INS3079 |
56 |
INS3083 |
Data visualization and analytics |
3 |
27 |
18 |
0 |
MAT1004 INS3047 |
57 |
INS3069 |
Decision Support Systems |
3 |
30 |
15 |
0 |
INS2061 INS3063 |
58 |
INS3080 |
Artificial Intelligence |
3 |
30 |
15 |
0 |
INS3061 INS2023 |
V.4.2 |
Financial data analysis |
15 |
|
|
|
|
|
59 |
INS2015 |
Fundamentals of Finance |
3 |
30 |
15 |
0 |
INE1051 |
60 |
INS3007 |
Corporate Finance |
3 |
30 |
15 |
0 |
INS2015 |
61 |
INS3084 |
Financial Time Series |
3 |
30 |
15 |
0 |
INS2051 |
62 |
INS3085 |
Financial Computing for Actuaries |
3 |
30 |
15 |
0 |
INS2051 |
63 |
FIB3005 |
Investment and Portfolio Management |
3 |
30 |
15 |
0 |
INS3007 |
V.4.3 |
Marketing Data Analysis |
15 |
|
|
|
|
|
64 |
INS2003 |
Principles of Marketing |
3 |
36 |
9 |
0 |
|
65 |
INS3086 |
Data and Analysis for Marketing Decisions |
3 |
36 |
9 |
0 |
INS2003 INS2061 |
66 |
INS3087 |
Models for Marketing Strategy |
3 |
36 |
9 |
0 |
|
67 |
INS3088 |
Experiments for Business Decision Making |
3 |
36 |
9 |
0 |
|
68 |
INS3089 |
Quantitative Models in Marketing Research |
3 |
36 |
9 |
0 |
INS2051 |
V.5 |
Internship and Graduation/ Alternative subjects for Dissertation |
10 |
|
|
|
|
|
69 |
INS4001 |
Internship |
5 |
0 |
75 |
0 |
INS3059 INS3061 |
70 |
INS4011 |
Graduation Thesis |
5 |
0 |
75 |
0 |
|
|
Alternative subjects for Dissertation |
|
|
|
|
|
|
71 |
INS4016 |
Advanced Data Analytics |
2 |
20 |
10 |
0 |
INS3046 |
72 |
INS4017 |
Modern Data Mining |
3 |
27 |
18 |
0 |
INS2061 |
Total |
145 |
|
|
|
|
BUSINESS DATA ANALYTICS
INTRODUCTION
Training program: | Business Data Analytics (code: experimental program) |
Duration: | 4 years (8 semesters) |
Teaching language: | English |
Mode of study: | Full time in VNU International School |
Degree: | Bachelor’s Degree awarded by Vietnam National University Hanoi |
WHY DO YOU CHOOSE THE PROGRAM?
The Bachelor program of Business Data Analytics (BDA) was licensed by Vietnam National University according to Decision No. 941/QD-DHQGHN, issued in April 3rd, 2019 as a VNU’s unit-based highly-qualified training program; beginning in the academic year 2019-2020.
The program structure, teaching and assessment methods are designed based on the Pensylvania University (US)’ program, entirely conducted in foreign languages in accordance with international training standards, 20-25% major-based subjects are taught by foreign lecturers. VNU-IS always strives to ensure that 100% textbook and reference materials for major-based subjects are being used in foreign universities. The expected value of the graduates’ satisfactation is received also through field trips, study tours, learning from guest speakers, benefit from working on real case studies, graduation projects, which help students put their knowledge into practice.
BDA is a highly interdisciplinary major with the combination of mathematics, statistics, economics, finance, marketing, and computer science involving diverse methods and techniques to exploit and transform data into useful information for making decision, building strategies and plans, operating activities, optimizing the use of sources of big datain businesses, organizations, . Graduates from this program have basic knowledge in data science, economics, and managements, also in-depth knowledge in business data analysis; have ability to handle problems related to business data analysis; perform financial and marketing analysis and forecasting in operation of corporation in particular, and the economy in general; fluently use data analysis tools; have personal skills and job skills to work in interdisciplinary, multicultural and multinational environment with high international integration.