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MCA with specialization in Artificial Intelligence and Data Science

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Level
Postgraduate
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Duration
2 Years
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Fee Structure
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MCA with specialization in Artificial Intelligence and Data Science

Admission Procedure

Merit prepared on basis of the qualifying exam

Provisional Admission

As per AICTE norms.

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About The Program

The Master of Computer Applications with specialization in Artificial Intelligence & Data Science is a two-year postgraduate program that provides advanced knowledge and hands-on expertise in cutting-edge areas of computing.

The program covers core courses such as Artificial Intelligence, Machine Learning, Natural Language Processing, Data Analytics, Cloud Computing, Computer Networks, and Database Systems, along with electives in areas like Cyber Security, Blockchain, Generative AI, and Software Project Management.

The curriculum integrates laboratory-based learning, research seminars, mini-projects, and a capstone project, ensuring that students gain both theoretical understanding and applied skills. Students are also encouraged to participate in industry internships, hackathons, certifications, and research publications, fostering innovation and employability.

Graduates of this program are equipped for diverse roles such as AI Engineer, Data Scientist, Machine Learning Specialist, Cloud Engineer, Business Analyst, and Researcher. They are equally prepared to pursue doctoral-level studies and contribute to academic, industrial, and societal advancements. The program also emphasizes soft skills, ethics, and general proficiency to ensure holistic professional development.

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)

PEO-1

Professional Competence

Equip graduates with a strong understanding of computer applications, software development, and information technology, enabling them to excel in various IT roles and contribute to their organizations' technological advancements.

PEO-2

Ethical and Responsible Practice

Instill ethical standards and social responsibilities in graduates, encouraging them to use their skills to create sustainable and inclusive technological solutions that address societal needs while adhering to professional ethics.

PEO-3

Lifelong Learning and Adaptability

Encourage graduates to engage in lifelong learning to keep up with the fast-changing field of computer applications and new technologies, ensuring their skills and knowledge remain current and relevant.

PEO-4

Leadership and Teamwork

Develop strong leadership, communication, and teamwork skills in graduates, enabling them to effectively lead and collaborate in diverse teams, manage projects efficiently, and contribute to their organizations' strategic goals.

Program Outcomes (POs)

After the successful completion of the program, the MCA with specialization in Artificial Intelligence & Data Science graduate will be able to:

PO1

Foundation Knowledge

Apply knowledge of mathematics, programming logic and coding fundamentals for solution architecture and problem solving.

PO2

Problem Analysis

Identify, review, formulate and analyse problems for primarily focussing on customer requirements using critical thinking frameworks.

PO3

Development of Solutions

Design, develop and investigate problems with as an innovative approach for solutions incorporating ESG/SDG goals.

PO4

Modern Tool Usage

Select, adapt and apply modern computational tools such as development of algorithms with an understanding of the limitations including human biases.

PO5

Individual and Teamwork

Function and communicate effectively as an individual or a team leader in diverse and multidisciplinary groups. Use methodologies such as agile.

PO6

Project Management and Finance

Use the principles of project management such as scheduling, work breakdown structure and be conversant with the principles of Finance for profitable project management.

PO7

Ethics

Commit to professional ethics in managing software projects with financial aspects. Learn to use new technologies for cyber security and insulate customers from malware

PO8

Life-long Learning

Change management skills and the ability to learn, keep up with contemporary technologies and ways of working.

Program Specific Outcomes (PSOs)

In addition to these POs, three Program Specific Outcomes (PSOs) are formulated:

PSO-1

Software Development

Demonstrate proficiency in designing, developing, and deploying advanced software applications using the latest programming languages, frameworks, and tools to solve complex problems in various industries.

PSO-2

Ethical and Inclusive Technology Solutions

Apply ethical principles and practices to develop inclusive and sustainable technology solutions, ensuring their work positively impacts society and adheres to professional standards.

PSO-3

Adaptability to Emerging Technologies

Continuously update their knowledge and skills in emerging technologies such as artificial intelligence, machine learning, and cloud computing, staying current with industry trends and advancements.

Career Pathways

The MCA with Specialisation in Artificial Intelligence and Data Science prepares graduates for key roles in the AI and data science industry, including:

  • Data Scientist
  • AI Engineer
  • Machine Learning Specialist
  • Business Intelligence Analyst
  • Big Data Analyst
  • Cybersecurity Specialist
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

  • Python Programming
  • Programming and Problem-Solving
  • Advanced Database Management Systems
  • Advanced Operating Systems
  • Discipline-Specific Elective – I
  • Full Stack Development
  • Human-Computer Interaction
  • Internet of Things
  • Career Skills – I
  • Python Programming Laboratory
  • Advanced DBMS Laboratory
  • Programming and Problem-Solving Laboratory
  • Mandatory Specialization Course
  • Probability and Statistics
  • First Semester Audit and Bridge Courses
  • Fundamentals of Computers
  • Linear Algebra
  • Introduction to DBMS
  • Introduction to Operating Systems

Semester 2

  • Artificial Intelligence
  • Data Structures
  • Computer Networks
  • University Open Elective / Generic Elective – I
  • Career Skills – II
  • Mini Project – I / Research Seminar
  • Artificial Intelligence Laboratory
  • Computer Networks Laboratory
  • Data Structures Laboratory
  • General Proficiency
  • Mandatory Specialization Course
  • Data Warehousing and Mining

Semester 3

  • Machine Learning – I
  • R Programming
  • Design and Analysis of Algorithms
  • Discipline-Specific Elective – II
  • Mobile Application Development
  • C# and .NET
  • Software Testing and Quality Assurance
  • DevOps on Cloud
  • Career Skills – III
  • Mini Project / Research Seminar
  • Design and Analysis of Algorithms Laboratory
  • Machine Learning – I Laboratory
  • R Programming Laboratory
  • Mandatory Specialization Course
  • Data Analytics and Visualization
  • Third Semester Audit Courses
  • Competitive Programming

Semester 4

  • Machine Learning – II
  • Discipline-Specific Elective – III
  • Cyber Security and Cyber Law
  • Blockchain and Its Applications
  • Generative AI
  • Soft Computing
  • Computational Complexities
  • University Open Elective / Generic Elective – II
  • Internship / Dissertation / Capstone Project
  • Machine Learning – II Laboratory
  • General Proficiency
  • Mandatory Specialization Course
  • Natural Language Processing

Frequently Asked Questions

The MCA with Specialisation in AI & DS is a postgraduate degree program that focuses on Artificial intelligence, machine learning and data science.

The MCA with Specialisation in AI & DS degree program usually has a duration of 2 years, divided into four semesters.

The core subjects include data structures, programming languages, database management systems, operating systems, computer networks, software engineering, and cloud computing along with Artificial intelligence, machine learning, python programming and data science.

Yes, it has an excellent scope as IT, AI, cloud computing, and data science continue to expand globally, creating opportunities in both corporate and research sectors.

Graphic Era (Deemed to be University) is among the best colleges in India and is highly rated for its industry-oriented curriculum, research-driven approach, and strong placement record. Recognized as one of the leading university for MCA with Specialisation in AI & DS in Uttarakhand.

  • MCA focuses on general computer applications, programming, and software development.
  • MCA with Specialisation in AI & DS focuses on Artificial Intelligence, Machine Learning, and Data Science along with core MCA subjects.

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