The duration of the BCA (Hons.) programme shall be 4 years (8 semesters). The BCA (Hons.) includes courses categorised under various heads, such as Programme Core, Programme Elective, Project-based Learning, Ability Enhancement Course, Multi-Disciplinary Course, Value Added Course, and Skill Enhancement Course. This structured approach ensures students receive a comprehensive education covering essential courses/subjects.
The department’s mission revolves around achieving academic excellence by providing quality education, enhancing students’ mastery skills, and offering professional training to ensure their readiness for successful careers, with a strong emphasis on social commitment. At the outset of each academic year, the department's strategic planning aims to position itself as a centre of excellence in professional education while upholding a commitment to continuous quality assurance.
The department has enough labs to use on a timetable to meet curriculum requirements.
The practical work courses will be provided with labs every week.
A teaching faculty and a lab instructor are responsible for each laboratory.
Labs are equipped with sufficient hardware and use free and open-source software.
All Labs are equipped with whiteboards.
Labs are equipped with a UPS facility.
Each Lab is equipped with the Internet.
PROGRAM EDUCATIONAL OBJECTIVES (PEOs)
PEO 1: Equip students with a strong foundational knowledge in computing, mathematics, and
software development to enable them to excel in professional careers or higher studies in
computer applications.
PEO 2: Foster analytical skills to solve real-world problems by designing, developing, and
implementing computing solutions that are technically sound, economically feasible, and
socially responsible.
PEO 3: Cultivate professionalism, ethical responsibility, effective communication, and
teamwork skills while encouraging a commitment to lifelong learning to adapt to evolving
industry demands.
PROGRAM SPECIFIC OUTCOMES (PSOs)
PSO 1: Gain the ability to understand, apply, and integrate computing principles and
mathematical skills to solve industrial and societal challenges effectively.
PSO 2: Develop competencies in designing, developing, testing, and maintaining software
applications using the latest computing tools, technologies, and methodologies to meet current and future industry needs.
Upon completing the MCA program, graduates can pursue various roles, including:
Software Developer
Data Scientist
Computer Programmer
Mobile App Developer
System Analyst
Cloud Architect
Data Analyst
Database Administrator
Web Designer/Developer
Senior Technical Consultant
Project Manager
Database Management in the Banking Sector
Teaching and Academia
With this program, students are equipped to become proficient professionals in the evolving IT landscape, ready to make a meaningful impact across industries.
The Department is committed to adopting innovative teaching methodologies to enhance effective listening and boost student learning outcomes. We aim to create a learning-centered environment with varied strategies to make education more engaging, interactive, and effective. Here are some of the essential methods we use to foster active learning and student success:
Flipped Classroom
In the flipped classroom model, students engage with lecture materials at home, allowing classroom time to focus on projects, assignments, and collaborative learning. By completing traditional "homework" tasks in class, students gain a supportive environment for peer-to-peer interaction and collaborative problem-solving.
Think-Pair-Share (TPS)
The Think-Pair-Share (TPS) method promotes cooperative learning by encouraging students to think independently about a question, discuss their response with a partner, and share insights with the larger class. This process nurtures communication skills and ensures all students have an opportunity to contribute.
Think-Pair-Share-Re-Pair (TPR)
Building on the Think-Pair-Share method, the Think-Pair-Share-Re Pair (TPR) adds a step for deeper understanding. After the initial Think-Pair-Share, students’ re-pair with another partner to incorporate broader perspectives. This approach enhances critical thinking and broadens comprehension through diverse viewpoints.
Jigsaw Groups
The Jigsaw method divides students into small groups, each receiving unique information. Students become "experts" on their assigned section, then rearrange into new groups where each member shares their knowledge. This process continues until all groups completely understand the topic, fostering teamwork and comprehensive learning.
Video Lectures
Supplementing lectures with video content offers students an additional resource to reinforce learning. This is particularly beneficial for those needing to revisit concepts at their own pace. This approach supports diverse learning styles and helps students retain information through repeated review.
Each method reflects our commitment to dynamic, student-centered education, helping students build confidence, knowledge, and skills through collaborative and interactive learning experiences.
Add-on Course for BCA
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Course: Artificial Intelligence and Machine Learning |
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Module |
Course Content |
Total Hrs |
|
Module 1 |
Introduction to AI & ML |
8 hrs |
|
Module 2 |
Introduction to Data Science |
8 hrs |
|
Module 3 |
Python basic to advanced |
20 hrs |
|
Module 4 |
Python for Data Science |
20 hrs |
|
Module 5 |
Preprocessing and Feature Engine |
10 hrs |
|
Module 6 |
Exploratory Data Analysis |
15hrs |
|
Module 7 |
Machine Learning Basics |
20 hrs |
|
Module 8 |
Statistics for Data Science |
10 hrs |
|
Module 9 |
Neural Networks and Deep Learning |
8 hrs |
|
Module 10 |
Natural Language Processing (NLP) |
8 hrs |
|
Module 11 |
DBMS and SQL |
15 hrs |
|
Module 12 |
Web Deployment |
8 hrs |
|
Total Hours |
150 hrs |
|
