GEU
Search Icon

BCA (Artificial Intelligence and Data Science)

facilities
Level
Undergraduate
facilities
Duration
3 Years
facilities
Fee Structure
Click Here
facilities Download Brochure
Apply Now
BCA (Artificial Intelligence and Data Science)

Admission Procedure

Merit prepared on basis of the qualifying exam

Provisional Admission

As per AICTE norms.

facilitiesFee Structure Apply Now
facilities Scheme of Teaching and Evaluation

About The Program

The Bachelor of Computer Applications (Artificial Intelligence and Data Science) is a specialized undergraduate program designed to build strong foundations in computer applications while offering advanced expertise in AI and Data Science.

The program blends core computer science subjects with interdisciplinary learning in mathematics, data analytics, machine learning, and emerging technologies. The Department offers well-equipped laboratories, modern computing facilities, and experienced faculty to provide high-quality teaching, learning, and research opportunities.

Students are also exposed to industry-relevant projects, internships, and collaborative learning experiences. With increasing demand for AI and DS expertise across sectors like healthcare, finance, e-commerce, cybersecurity, and research, graduates of this program will be well-positioned to pursue careers as AI engineers, data scientists, software developers, business analysts, and researchers.

The program also emphasizes holistic development by including soft skills, communication, ethical values, and exposure to multidisciplinary courses offered across the university. This ensures that graduates are not only technically skilled but also industry-ready professionals with a strong sense of social responsibility.

Eligibility

As per AICTE norms.

Teaching Pedagogies

The department adopts innovative, student-centric teaching pedagogies designed to enhance conceptual understanding, practical proficiency, and industry readiness. Our approach integrates modern educational practices with advanced technological tools to create an engaging and outcome-driven learning environment. Key pedagogical practices include:

  • Outcome-Based Education (OBE)

    All courses are structured around clearly defined learning outcomes to ensure measurable academic and professional growth.

  • Experiential & Hands-On Learning

    Emphasis on laboratory work, real-time projects, coding sessions, and technical workshops to strengthen practical understanding.

  • Project-Based & Problem-Based Learning

    Students work on industry-relevant problems, case studies, mini-projects, and capstone projects to develop analytical and solution-oriented skills.

  • Flipped Classroom & Blended Learning

    Classroom time is optimized through pre-class digital content, interactive discussions, and collaborative problem-solving activities.

  • Industry-Academia Engagement

    Regular expert lectures, masterclasses, internships, and certifications through collaborations with leading MNCs enhance industry exposure.

  • Use of Modern ICT Tools

    Smart classrooms, LMS platforms, virtual labs, simulation tools, and coding environments support interactive and technology-driven learning.

  • Continuous Assessment & Feedback

    Frequent quizzes, assignments, reviews, presentations, and peer evaluations help monitor progress and encourage continuous improvement.

  • Skill Development & Holistic Learning

    Focus on communication skills, teamwork, professional ethics, and lifelong learning to prepare students for global professional environments.

Specializations

  • Bachelor of Computer Applications (Artificial Intelligence and Data Science)

  • Bachelor of Computer Applications (Cyber Security)

Program Educational Objectives (PEOs)

PEO1

Technical Proficiency

Provide graduates with a strong foundation in computer applications, programming languages, and software development, enabling them to build, maintain, and improve software systems and applications.

PEO2

Practical Problem-Solving

Develop graduates' ability to apply theoretical knowledge to real-world problems, encouraging innovative thinking and practical problem-solving skills in various domains such as business, education, and healthcare.

PEO3

Professional Growth and Learning

Foster a commitment to professional growth and lifelong learning, preparing graduates to pursue advanced studies, certifications, and adapt to the evolving landscape of technology and industry demands.

PEO4

Effective Communication and Ethical Practice

Cultivate effective communication skills and ethical practices, enabling graduates to work collaboratively in teams, communicate technical concepts clearly, and uphold ethical standards in their professional careers.

Program Outcomes (POs)

After the successful completion of the program, the BCA graduate will be able to:

PO1

Fundamental Knowledge Application

Apply foundational knowledge of mathematics, management, and computer applications to solve basic real-world problems effectively.

PO2

Basic Problem Analysis

Identify and analyze problems using fundamental principles of mathematics and computer applications to develop initial solutions.

PO3

Solution Design and Development

Design solutions for standard problems and develop system components or processes, considering essential health, safety, and societal aspects.

PO4

Research and Problem Solving

Use basic research methods and data analysis techniques to investigate computing problems and draw preliminary conclusions.

PO5

Tool Utilization

Select and apply appropriate tools and software for routine computing tasks, understanding their basic functions and limitations.

PO6

Awareness of Sustainability

Understand the impact of software engineering solutions on society and the environment and appreciate the principles of sustainable development.

PO7

Ethical Practice

Adhere to ethical principles and professional norms in software development and computing practices.

PO8

Individual and Teamwork

Work effectively as an individual and as part of a team, demonstrating basic collaboration and leadership skills in various settings.

PO9

Effective Communication

Communicate effectively on computing activities, preparing clear reports and documentation, and delivering presentations to a general audience.

PO10

Project Participation

Apply basic project management principles to contribute effectively to team projects and understand the fundamental aspects of project planning and execution.

PO11

Foundation for Lifelong Learning

Recognize the need for ongoing learning and be prepared to engage in further education or training to keep up with technological changes.

PO12

Innovation and Practical Application

Identify opportunities for practical application of innovative ideas and contribute to solving problems in a way that adds value to projects and tasks.

Program Educational Objectives (PEOs)

In addition to these twelve POs, the BCA graduate will also be able to:

PSO1

Application Development

Design, develop, and deploy basic software applications using standard programming languages and development tools, addressing typical business and organizational needs.

PSO2

Fundamental Database Management

Demonstrate proficiency in managing and using database systems, including designing database schemas, querying databases, and ensuring data integrity for various applications.

PSO3

System Analysis and Design

Apply fundamental principles of system analysis and design to develop effective solutions for common computing problems, including requirements gathering, system modelling, and process design.

Career Prospects

The Bachelor of Computer Applications (Artificial Intelligence and Data Science) offers diverse career opportunities in IT and tech industries, including:

AI Consultant

AI support specialist

Data Analysist

Software Developer

Business Analyst

Graphic Era (Deemed to be University)

Placements

Graphic Era Deemed to be University has a strong connection to various industries, and its track record for successfully placing students in reputable positions is outstanding, with graduates being placed in internships and permanent roles. The university has formed valuable relationships with globally recognized companies such as Amazon, Microsoft, Google, Walmart, Adobe, and many more, providing students with ample opportunities to kick-start their careers.

Graduates from Graphic Era Deemed to be University can be confident in their ability to succeed in the workforce due to the exceptional training and real-world experience they gain from their internships and placements with these top-tier companies.

Notes: Semester 1 and 2 are applicable only for regular entry students. Lateral entry students begin from Semester 3.

Course Curriculum

Semester 1

  • Computational Thinking and Fundamentals of IT
  • Fundamentals of Python Programming
  • Mathematical Foundation for AI
  • Professional English Skills
  • University Open Elective / Generic Elective – 1
  • Digital Productivity Tools for Modern Workplaces Laboratory
  • Fundamentals of Python Programming Laboratory
  • Seminar – 1

Bridge Course – 1

  • Basic Mathematics -I

Mandatory Non-Graded Course

  • Environmental Science

Semester 2

  • Introduction to Data Science
  • Foundations of Artificial Intelligence
  • Probability and Statistics for Data Science
  • Programming Concepts Using C Language

Discipline-Specific Elective – 1

  • Discrete Mathematics
  • Introduction to Operating Systems
  • Cyber Security Essentials
  • Data Science using Python Laboratory
  • Programming Concepts Using C Laboratory
  • General Proficiency

Audit Course – 1

  • Indian Constitution

Bridge Course – 2

  • Basic Mathematics -II

Mandatory Non-Graded Course

  • Indian Knowledge System

Semester 3

  • Introduction to Data Structures
  • Introduction to Database Management Systems
  • Introduction to Machine Learning

Discipline-Specific Elective – 2

  • Introduction to Big Data
  • Secure Software Development
  • Fundamentals of Cloud Computing
  • Operating System and Security
  • Introduction to Soft Computing
  • Skills for Career Success – I
  • UHV-II
  • Introduction to Data Structures Laboratory
  • Database Management Systems and Machine Learning Laboratory
  • Mini Project – 1

Semester 4

  • Web Application Development
  • Fundamentals of Data Analytics
  • Data Communication and Networks
  • Management Information Systems

Discipline-Specific Elective – 3

  • Data Handling and Visualisation
  • DevOps on Cloud
  • Introduction to JAVA Programming
  • Algorithm Design and Analysis Essentials
  • Introduction to Data Mining
  • Skills for Career Success – II
  • Web Application Development Laboratory
  • Data Analytics Laboratory
  • Mini Project – 2
  • General Proficiency

Semester 5

  • Introduction to Deep Learning
  • Programming with R
  • Introduction to Software Engineering
  • University Open Elective / Generic Elective – 2

Discipline-Specific Elective – 4

  • Skills for Career Success – III
  • Deep Learning Laboratory
  • Programming with R Laboratory
  • Mini Project – 3

Semester 6

  • Business Intelligence
  • Ethics of AI
  • Disaster Management
  • Network Security and Cyber Law

Discipline-Specific Elective – 5

  • Operations Research
  • Introduction to .NET Programming
  • Software Testing
  • Introduction to Cyber Forensics
  • Introduction to Cyber Security and Cyber Law
  • Capstone Project / Internship / Mini-Projects for Honours
  • General Proficiency

Semester 7

  • Advanced Python Programming
  • Advanced Database Management Systems

Discipline-Specific Elective – 6

  • Advanced Operating Systems
  • Security and Privacy in Cloud
  • Computer Network
  • Natural Language Processing

Discipline-Specific Elective – 7

  • Human Computer Interaction
  • Information Security
  • Mobile Computing
  • Software Project Management
  • Advanced Python Programming Laboratory
  • Advanced Database Management Systems Laboratory
  • Capstone Project

BCA (AI&DS) (Honours with Research)

  • Advanced Python Programming
  • Advanced Database Management Systems
  • Advanced Python Programming Laboratory
  • Advanced Database Management Systems Laboratory
  • Research Project Phase – I

Semester 8

  • Data Warehousing and Mining
  • Data Structures
  • University Open Elective / Generic Elective – 3

Discipline-Specific Elective – 8

  • Design Thinking
  • Artificial Intelligence
  • Business Analytics
  • Blockchain Technology
  • Capstone Project / Industry Internship
  • General Proficiency

BCA (AI&DS) (Honours with Research)

  • Data Warehousing and Mining
  • Data Structures
  • University Open Elective / Generic Elective – 3

Discipline-Specific Elective – 8

  • Design Thinking
  • Artificial Intelligence
  • Business Analytics
  • Blockchain Technology
  • Research Project Phase – II
  • General Proficiency

Frequently Asked Questions

BCA (AI&DS) is UG program designed to provide students with in-depth knowledge of computer applications, artificial intelligence, and data science. This specialized degree equips students with the expertise required to build intelligent systems, analyze complex data, and develop cutting-edge AI-driven solutions

Yes, the BCA(AI&DS) syllabus includes practical lab sessions, projects, and internships to give students hands-on experience in coding and application development.

General BCA focuses on core computer applications, programming, and software development, while BCA (AI&DS) includes these core subjects along with specialized study of Artificial Intelligence, Machine Learning, and Data Science, preparing students for emerging technology roles.

After BCA (AI&DS), students can pursue careers such as Data Analyst, Data Scientist, AI/ML Engineer, Business Intelligence Analyst, Software Developer, Data Engineer, or opt for higher studies like MCA (AI&DS), M.Sc. (IT/CS), or MBA.

Students gain skills in Python programming, data analysis, machine learning, problem-solving, and logical thinking.

BCA (AI&DS) covers subjects such as Programming in Python, Artificial Intelligence, Machine Learning, Data Science, Statistics, Big Data Analytics, Database Management Systems, Web Technologies, and Project Work.

Programs at GEU

program pic

Undergraduate

Programs

GEU link
program pic

Postgraduate

Programs

GEU link
program pic

Certificate

Programs

GEU link
program pic

Ph.D.

Programs

GEU link

Admissions 2026

GEU
Apply Now Download Prospectus

Contact Us

GEU
GEU

566/6, Bell Road, Society Area,
Clement Town, Dehradun,
Uttarakhand

GEU
1800 270 1280
GEU
enquiry@geu.ac.in
GEU