M.Sc. Information Technology

A Master of Science (M.Sc.) in Information Technology is a postgraduate academic degree program that focuses on advanced studies in the field of information technology (IT). This program is designed to provide students with a deep understanding of various aspects of IT, including software development, database management, networking, cybersecurity, and information systems.

Studying for a Master's in Information Technology (IT) can offer several significant advantages, both in terms of personal and professional development. Here are some key reasons why pursuing a Master's in Information Technology can be important:

Eligibility Criteria

• Candidates should have passed with a minimum of 50% marks (45% in case of SC/ST candidates) in B.Sc – Comp. Science / BCA /B.Sc. – IT / B.Sc. – CT or equivalent examination from a recognized university preferably with mathematics at 10+2 level or at Graduation level.

Scope and Objectives

An MSc in IT with a specialization in Data Science prepares graduates for high-level careers in data science, analytics, and machine learning. The program covers advanced topics such as deep learning, big data technologies, statistical modeling, and artificial intelligence. Graduates can pursue careers as data scientists, machine learning engineers, or data consultants in industries like finance, healthcare, e-commerce, and telecommunications. The program also equips students with research skills, enabling them to contribute to cutting-edge innovations in data science. With the growing reliance on data-driven strategies across industries, the demand for data science professionals is expected to rise. Graduates may also pursue doctoral studies or certifications in specialized areas like AI or data engineering.

• To offer in-depth knowledge of advanced data science techniques, including machine learning, deep learning, and big data technologies.
• To provide practical experience in managing large datasets and deriving insights using tools like Hadoop, Spark, and TensorFlow.
• To develop the ability to apply data science methodologies to solve complex problems in various industries, including finance, healthcare, and retail.
• To prepare graduates for high-level roles as data scientists, machine learning engineers, and data consultants.
• To cultivate research skills, enabling students to contribute to innovations in data science and AI.
• To prepare students for further academic research (PhD) or advanced certifications in areas such as AI, data engineering, or specialized fields of data science.
• To promote teamwork, communication, and project management skills by engaging students in collaborative projects and internships.

Programme Structure
Semester  I

• Advanced Java Programming
• Relational Database Management Systems
• Data Analytics
• Artificial Intelligence

Practical Learning Experience

• Advanced Java Lab
• RDBMS Lab

Semester II

• Mobile Computing
• Software Project Management
• Python Programming
• Cyber Security and Ethical Hacking
• Research Methodology

Practical Learning Experience

• Mobile Computing Lab
• Python Lab
• Research Publication

Semester III

• Machine Learning
• Pattern Recognition
• Natural Language Processing
• Cyber Forensics
• Block Chain Technology

Practical Learning Experience

• Machine Learning Lab
• Cyber Forensics Lab

Semester Iv

• Cloud Management
• Virtual Reality and Augmented Reality
• Project Documentation and Viva-voce