Master of Computer Application (MCA )
The Master of Computer Applications (MCA) is a postgraduate two year degree in computer application. It’s a popular choice for students who want to delve deeper into the field of computer science and its applications. Our college technical training department serves various training programs in different contexts, but its primary objectives include for students benefits like Professional Development, Skill Development, Increased Productivity and Adoption of New Technologies. College Technical Trainings are: Python, Advance Data Structure, OOPs with Java, Database with SQL etc additional AKTU course curriculum.
MCA degree can enhance career prospects and open up opportunities for advancement. Many employers prefer candidates with a master’s degree for higher-level positions, leadership roles, and specialized technical roles.
Post Graduating MCA degree from Allenhouse Institution of Technology can enhance your credibility in the eyes of employers. It demonstrates your commitment to advancing your education and acquiring specialized knowledge in the field.
Course Curriculum of Two Year MCA Program:
First Year (1st Semester)
- Fundamental of Computers & Emerging Technologies Problem Solving using C.
- Principles of Management & Communication.
- Discrete Mathematics Computer Organization & Architecture.
- Problem Solving using C Lab.
- Computer Organization & Architecture Lab.
- Professional Communication Lab.
First Year (2nd Semester)
- Theory of Automata & Formal Languages.
- Object Oriented Programming.
- Operating Systems.
- Database Management Systems.
- Data Structures & Analysis of Algorithms.
- Cyber Security.
- Object Oriented Programming Lab.
- DBMS Lab.
- Data Structures & Analysis of Algorithms Lab.
Second Year (3rd Semester)
- Artificial Intelligence.
- Software Engineering.
- Computer Network.
- Elective – 1 (Cryptography & Network Security, Data Warehousing & Data Mining, Software Project Management, Cloud Computing, Compiler Design).
- Elective – 2 (Web Technology, Big Data, Simulation & Modeling, Software Testing & Quality Assurance, Digital Image Processing).
- Artificial Intelligence Lab.
- Mini Project.
Second Year (4th Semester)
- Elective – 3 (Privacy & Security in Online Social Media, Soft Computing, Pattern Recognition, Data Analytics, Software Quality Engineering).
- Elective – 4 (Blockchain Architecture, Neural Network, Internet of Things, Modern Application Development, Distributed Database Systems).
- Elective – 5 (Mobile Computing, Computer Graphics and Animation, Natural Language Processing, Machine Learning, Quantum Computing.
- Project.
Our Teaching Team
Professor & Head of Department
Data Structure and Algorithm, DBMS, Computer Organization, Neural Network.
Qualification:
Ph.D(CS), MCA, M.Tech (CSE)
Assistant Professor
DBMS, Operating System
Qualification:
M.Tech (CSE), B.Tech
Assistant Professor
Software Engineering
Qualification:
M.Tech (CSE), B.Tech
Assistant Professor
OOPs with JAVA, Data structures using C & Python,Database with SQL
Qualification:
M.Tech (CSE), Ph.D (P), B.Tech
Assistant Professor
Computer Network, DAA, Software Engineering
Qualification:
M.Tech (CSE), Ph.D (P), B.Tech
Assistant Professor
Image Processing, Artificial Intelligence, DBMS
Qualification:
Ph.D, M.Tech(CSE), B.Tech
Assistant Professor
Data Structure using C and C++
Qualification:
M.Tech, B.Tech
Assistant Professor
DBMS
Qualification:
M.Tech(CSE),B. Tech
Assistant Professor
DBMS, Operating System
Qualification:
M.Tech (CSE), Ph.D (P), B.Tech
Assistant Professor
Data Structure, DAA
Qualification:
M. Tech(CSE), Ph.D(P), B. Tech
Assistant Professor
DAA, Data Structure, Computer Network
Qualification:
Ph.D(CSE)-(P), M. Tech(CSE)
Assistant Professor
Machine Learning, Data Analytics, Python Programming
Qualification:
M.Tech(Cyber Security),B. Tech
Assistant Professor
Artificial Intelligence and Machine Learning
Qualification:
M.Tech, Ph.D(P), NET, GATE
Assistant Professor
Data Structure, C Programming, Computer Networking
Qualification:
MBA, M.Tech, Ph.D(P), B. Tech
Associate Professor
Machine Learning, Deep Linking, Neural Networks, Data Structures, Computer Organization
Qualification:
Ph.D, M.Tech, B. Tech
Associate Professor
AIML
Qualification:
Ph.D, M.TECH, B.TECH
Assistant Professor
DBMS
Qualification:
MCA, M.Tech(P), BCA, NET
Assistant Professor & PDP Trainer
Computer Science & Networks
Qualification:
B. Tech
Assistant Professor
DBMS
Qualification:
M. Tech, Ph.D Pursuing
Assistant Professor
OOPs with Java, Springboot Framework, NoSQL(MongoDB)
Qualification:
M. Tech
Assistant Professor
Machine Learning, Data Structure
Qualification:
M. Tech, Ph.D(P), NET, GATE
Assistant Professor
Data Structure, DAA, TOC
Qualification:
M.Tech, MCA
Assistant Professor
C Programming, Data Structure
Qualification:
M. Tech
Assistant Professor
C Programming, Data Structure, DAA
Qualification:
M. Tech