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Computer Science and Technology(Master)

Master Program in Computer Science and Technology for International Students

Discipline Classification: Engineering     First Class Discipline Code0812  

First Class Discipline NameComputer Science and Technology 

According to the master student program of Nanjing University of Information Science & Technology (hereinafter referred to as NUIST), and with reference to the relevant regulations of NUIST on international students, the international student master program of NUIST is formulated as follows:

1. Introduction to the Major

The major was founded in 1987, and has formed a complete training system from undergraduate to graduate (master and doctoral) education. It is one of the national specialty construction point, and has been selected as a superior discipline in Jiangsu Province for two consecutive periods. It includes provincial and ministerial scientific research platforms, the Ministry of Education’s Internet Application Innovation Open Platform Demonstration Base, the Jiangsu Network Monitoring Engineering Center, and two central and local experimental platforms for digital forensics and meteorological data mining. Michigan State University jointly established the China-US Computer Science Research Center to strengthen international cooperation, exchanges and construction of disciplines. In the past five years, this subject has undertaken 3 key projects of the National Natural Science Foundation of China, more than 40 projects of the National Natural Science Foundation of China (general and youth), the national 863 project, the Ministry of Science and Technology Public Welfare Industry Research Special Project and other national-level scientific research. At present, this subject has entered the top 1% of the ESI computer subject global ranking, and the result of the fourth round of subject evaluation by the Ministry of Education is B grade.

 

2. Objectives 

Have amicable feelings towards China and a strong sense of professionalism and dedication.

Master solid basic theory and systematic expertise in this subject, and have the ability to engage in scientific research or independently undertake professional technical work. Master a foreign language, have the ability to proficiently read the foreign language materials of the major, and have strong listening, speaking, writing and translation skills.

Physical and mental health, capable of teaching, doing scientific research, business and management in colleges and universities, research institutes, business departments and other related departments after graduation.

 

3. Study Directions

(1)Cyberspace Security;

(2)Multimedia Processing;

(3)Internet of Things and Cloud Computing;

(4)Quantum Computing and Information Processing;

(5)Artificial Intelligence and Big Data Analysis.

 

4. Educational System, Length of Study and Credit Requirements

The length of education for master students is two (2) years.

If due to special circumstances a master student is unable to graduate on time, the student must apply in person, following the writing of the supervisor’s opinion and signature, the approval of the school affiliated. The application should be submitted to the Graduate School for approval and College of International Students for archiving. The maximum length of time that students can study at the University is five (5) years and during this extension period international students shall pay for the study and accommodation fees as required.

Credit Requirements: For master courses, a credit system has been implemented and consists of degree and non-degree courses. Degree courses must be no less than fifteen (15) credits, and the total credits must equal twenty-six (26) credits or above.

 

5. Course Introduction

Fundamental Courses

Software Architecture & Design: Software architecture provides opportunities for early evaluation of user needs, analysis of requirements and design, and prediction of system properties. Architectural styles, views, notations, and description languages provide systematic frameworks for engineering decisions and design practices.

Objected Oriented Programming: Object-oriented programming represents the integration of software components into a large-scale software architecture. The course focuses on the understanding and practical mastery of object-oriented concepts such as classes, objects, data abstraction, methods, method overloading, inheritance and polymorphism.

Design and Analysis of Algorithm: Algorithms are the soul of computing. This course introduces basic methods for the design and analysis of efficient algorithms emphasizing methods useful in practice. Different algorithms for a given computational task are presented and their relative merits evaluated based on performance measures.

Python Programming: Python is a language with a simple syntax, and a powerful set of libraries. This course is an introduction to the Python programming language for students without prior programming experience. It covers data types, control flow, object-oriented programming, and graphical user interface-driven applications.

Core Courses

Advanced Computer Architecture: An overview of computer architecture, which stresses the underlying design principles and the impact of these principles on computer performance. General topics include design methodology, processor design, control design, memory organization, system organization, and parallel processing.

Advanced Database: The course presupposes a basic knowledge of conceptual modelling for data base systems and implementation using relational DBMS and SQL. The course aims to have a more profound understanding of database theories, models, and methods and an ability to use these in different situations.

 

6. Training Style and Methods

The program of master students is combined course work with thesis work. Usually, course work will be done within one (1) year and thesis work takes more than one year.

The training of master students is implemented by the supervisor tutorial system. In this way, supervision is carried out under the supervisor and with a group of experts.

 

7. Midterm Evaluation 

Master students in the third semester will have midterm evaluation which is to evaluate students’ moral behavior, course score, research progress and other related issues. Failed students can apply for re-evaluation after six (6) months whereas the postponed period is no longer than one (1) year.

 

8. Degree Thesis

(1) Topic Selection and Thesis Proposal

The master proposal should be completed in the early third semester. Those who need to postpone the submission of the proposal due to special circumstances, a written application should be submitted to the Graduate School in advance and the time limit for delay shall not exceed two (2) months. After the proposal is accepted, changes in principle are not permitted. If there are, however, major changes in topic selection, the proposal should be rewritten.

(2) Thesis Writing and Requirements

This is conducted according to university thesis writing requirements.

(3) Thesis Pre-defense and Defense

  Masters students must complete all the required courses, pass all the courses and midterm evaluation, complete academic and practice activities and acquire required credits before they are allowed to apply for thesis pre-defense which is held before the end of March each year. Then they will go for blind review of the thesis. Only those students who have passed the pre-defense and blind review can apply for the final defense.

(4) Degree Applications

Degree applications is carried out according to the specific implementation methods outlined in the Nanjing University of Information Science & Technology Masters and Doctorate Degree Conferment Regulations and Nanjing University of Information Science & Technology Regulations on the Program and Qualifications of International Master Students (Trial).

Students shall pass sufficient courses in the program to get no less than twenty-six (26) credits, achieve required academic results, pass HSK Level 3 (or above) and pass the thesis defense.

 

9. Practice

Practice is combined with Academic Reports and other practice activities. It is worth two (2) credits.

During the period of master thesis work and excluding the Thesis Proposal, a public academic report should be held at least once. The student’s supervisor and the school affiliated are responsible for assessing the quality of the academic report. Master students should also participate in no less than six (6) academic activities including but not limited to academic reports, conferences, teaching and technology competitions both on and off the University campus. Students are required to take records on Academic Activities Brochure and only qualified students can attend final defense.


Attachment: Curriculum for International Master’s Students in Computer Science and Technology

Type

Course

Class Hours

Credits

Opening Semester

Teaching Method

Form of Evaluation

Note

A

入学教育

Orientation

16

1

1

In-Person Instruction

Exam

5 credits

中国概况(1

China Overview (1)

32

1

1

In-Person Instruction

Exam

中国概况(2

China Overview (2)

32

1

2

In-Person Instruction

Exam

综合汉语(1

Comprehensive Chinese (1)

96

1

1

In-Person Instruction

Exam

综合汉语(2

Comprehensive Chinese (2)

96

1

2

In-Person Instruction

Exam

B

面向对象程序设计

Objected Oriented Programming

32

2

1

In-Person Instruction

Exam

10 credits

软件系统分析与设计

Software System Analysis & Design

48

3

1

In-Person Instruction

Exam

算法设计与分析

Design and Analysis of Algorithm

32

2

2

In-Person Instruction

Exam

Python程序设计

Python Programming

48

3

1

In-Person Instruction

Exam

C

现代计算机体系结构

Advanced Computer Architecture

32

2

2

In-Person Instruction

Exam

4 credits

现代数据库技术

Advanced Database

32

2

1

In-Person Instruction

Exam

D

密码学与网络安全

Cryptography and Network Security

32

2

2

In-Person Instruction

Exam

No less than 5 credits

计算机网络

Computer Network

32

2

2

In-Person Instruction

Exam

云计算

Cloud Computing

32

2

2

In-Person Instruction

Exam

人工智能

Artificial Intelligence

32

2

2

In-Person Instruction

Exam

大数据

Big Data

32

2

2

In-Person Instruction

Exam

机器学习

Machine Learning

48

3

2

In-Person Instruction

Exam

E

学术报告

Academic Seminars

32

2

2

Others

Others

2 credits

NoteA) Public Courses; B) Major Compulsory Courses; C) Limited-Elective Courses; D) Major Elective Courses; E) Practice