Masters in Computer Science and Engineering (CSE)

Program Description: M.Sc. / M.Engg. in Computer Science and Engineering (CSE)

Faculty: Faculty of Computer Science and Engineering
Duration: 2 Years (4 Semesters)
Total Credit Hours: 36
CGPA Range: Highest 4.00 – Lowest 2.50
Program Type: Outcome-Based Postgraduate Program

Overview

The Master of Science (M.Sc.) and Master of Engineering (M.Engg.) in Computer Science and Engineering (CSE) at Mawlana Bhashani Science and Technology University (MBSTU) are advanced postgraduate programs designed to develop research excellence, technical expertise, and innovation in computer science and related engineering disciplines.

The program extends over two academic years (divided into four semesters) and consists of 36 credit hours. The M.Sc. program emphasizes research and innovation with 50% of total credits dedicated to thesis work, while the M.Engg. program focuses on professional and applied learning, including a 6-credit project component.

Both programs follow an Outcome-Based Education (OBE) framework, ensuring that graduates acquire not only theoretical and practical mastery but also the competencies required to address evolving technological challenges. The courses are taught by highly qualified faculty members with Ph.D. and Postdoctoral experience from reputed national and international universities.

Program Majors and Research Areas

Students can specialize or conduct research in any of the following advanced CSE fields:

• Artificial Intelligence and Machine Learning
• Data Science and Big Data Analytics
• Cybersecurity and Privacy Engineering
• Software Engineering and Quality Assurance
• Computer Networks and Cloud Computing
• Internet of Things (IoT) and Embedded Systems
• Blockchain and Distributed Systems
• Computer Vision and Natural Language Processing

Program Outcomes (POs)

Upon successful completion of the M.Sc./M.Engg. in CSE, graduates will be able to:

PO1: Advanced Knowledge
Demonstrate comprehensive knowledge of advanced computer science principles, computational models, and engineering methodologies.

PO2: Research and Innovation
Formulate, conduct, and present high-quality research or project work that contributes to technological advancement and knowledge creation.

PO3: Technical Proficiency
Apply advanced algorithms, software tools, and programming techniques to design and implement secure, efficient, and scalable computing solutions.

PO4: Problem Solving and Critical Thinking
Analyze complex computing problems using scientific reasoning, modeling, and simulation to propose optimized, innovative solutions.

PO5: Communication and Leadership
Demonstrate effective communication, teamwork, and leadership skills in collaborative research or professional environments.

PO6: Professional Ethics and Responsibility
Apply ethical principles, data integrity standards, and professional responsibility in computing practice, research, and software development.

PO7: Continuous Learning
Engage in lifelong learning, staying current with emerging technologies and global developments in computing and software engineering.

PO8: Research and Project Execution
For M.Sc. students – complete a rigorous research thesis demonstrating originality and scholarly contribution.
For M.Engg. students – complete an applied research or industrial project addressing real-world computing challenges.

Program Structure (Credit Distribution)

Component

M.Sc. in CSE

M.Engg. in CSE

Core Courses

15 Credits

21 Credits

Elective Courses

3 Credits

9 Credits

Thesis / Research Project

18 Credits (Thesis)

6 Credits (Project)

Total Credits

36 Credits

36 Credits

Expected Graduate Attributes

Graduates of the M.Sc./M.Engg. in CSE program will demonstrate:

• Depth of knowledge in advanced computer science and engineering.
• Research competence in designing and evaluating computing systems and algorithms.
• Professional readiness for leadership roles in academia, software industry, and research institutions.
• Innovation and creativity in applying computational techniques to solve societal and industrial problems.
• Global adaptability and commitment to ethical, sustainable, and human-centered computing practices.