BCA Artificial Intelligence and Machine Learning

Duration
3 Years Full-Time Program
Eligibility

The candidate seeking admission for B.Sc. Data Science should have passed (10 +2)/PUC or equivalent examination with mathematics or statistics as one of the subjects with minimum of 40% marks in aggregate. The same applies to SC/ST quota.

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BCA  Artificial Intelligence and Machine Learning

Programme Overview

This is a unique program that combines the fields of computer science, mathematics, and statistics. The objective of this program is to prepare students to analyze data effectively and enable data-driven decisions. The program provides students with the training they need in data collection, exploration, manipulation and storage, analysis, and presentation in order to navigate data-rich workplace environments. It enhances the mathematical, analytical, and technical skills to interpret and understand big, complex data sets and their relevance to real-life decisions. The industry-oriented curriculum equips the students with hands-on training in the fields of knowledge discovery, data analytics, artificial intelligence, machine learning, deep learning, natural language processing, programming, and visualization tools.

Course Curriculum

  • 01Applied Mathematics - MAT2007
  • 02Problem Solving using C - CSA1001
  • 03Digital Computer Fundamentals - ECE2009
  • 04Web Design and Development - CSA1002
  • 05Communicative English - ENG1003
  • 06Introduction to Soft Skills - PPS1001
  • 01Programming in Python - CSA1004
  • 02Statistical Methods and Techniques - MAT1006
  • 03Data Structures and Algorithms - CSA2001
  • 04Data Structures and Algorithms Lab - CSA2100
  • 05Technical Written Communication - ENG2005
  • 06Computer Networks - CSA2004
  • 07Computer Organization - CSA2002
  • 08Employability for Young Professionals - PPS1006
  • 01Relational Database Management Systems - CSA2003
  • 02Relational Database Management Systems Lab - CSA2101
  • 03Object Oriented Programming using Java - CSA1005
  • 04Graph Theory - MAT2028
  • 05Analysis of Algorithms - CSA2005
  • 06Artificial Intelligence - CSA2020
  • 07Operating Systems and Unix Programming - CSA1006
  • 08Being Corporate Ready - PPS2002
  • 09Environmental Studies and Sustainable Development - CHE1020
  • 01Minor Course - I - CSAXXXX
  • 02Fundamentals of Software Engineering - CSA2006
  • 03Minor Course - II - CSAXXXX
  • 04Machine Learning Algorithms - CSA3002
  • 05Android Mobile Applications Development - CSA3003
  • 06Essentials of Cloud Computing - CSA2008
  • 07Problem Solving through Aptitude - PPS3001
  • 08Business Communication - ENGXXXX
  • 01Deep Learning - CSA3071
  • 02Minor Course - III - CSAXXXX
  • 03Minor Course - IV - CSAXXXX
  • 04Minor Course - V - CSAXXXX
  • 05Minor Course - VI - CSAXXXX
  • 06Multi-Disciplinary Course - I - XXXXXXX
  • 07Multi-Disciplinary Course - II - XXXXXXX
  • 08Summer Internship - CSA3100
  • 01Minor Course - VII - CSAXXXX
  • 02Social Media Analytics - CSA2003
  • 03Minor Course - VIII - CSAXXXX
  • 04Multi-Disciplinary Course - III - XXXXXXX
  • 05Generative AI - CSA2102
  • 06Project – CSA3100

Programme Educational Objectives

After three years of successful completion of the program, the graduates shall be:

PEO 01: Demonstrate success as a computer professional with innovative skills, having moral and ethical values.

PEO 02: Engage in lifelong learning through software development.

PEO 03: Serve as a leader in the profession through consultancy, extension activities and/ or entrepreneurship.

Programme Outcomes (POs)

On successful completion of the Program, the students shall be able to:

PO 1: Application of Domain Knowledge: Apply the domain knowledge such as mathematics, science and software engineering fundamentals into the Computer Application related professions.

PO 2: Problem Solving & Analysis: Identify, Formulate, Analyse and Solve Complex Scenarios related to Computer Applications.

PO 3: Design/development of Activities: Conceive, Design and Develop various activities of Computer Applications.

PO 4: Conduct Investigations of Events: Carry out Investigation of an event and draw logical conclusions based on critical thinking and analytical reasoning.

PO 5: Modern Tool usage: Effectively apply relevant ICT Tools and digital tools to carry out Computer Application Attributes.

PO 6: Research: Identify suitable Research Methods and report the findings.

PO 7: Profession and Society: Apply the knowledge of the values and beliefs of multicultural society and a global perspective in the profession.

PO 8: Ethics: Identify ethical issues and embrace ethical values in conduct of Profession.

PO 9: Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO 10: Communication: Express thoughts and ideas effectively in writing and oral communication.

PO 11: Project Management and Finance: Ability to work independently, identify appropriate resources required for a project, and manage a project through to completion.

PO 12: Life-long Learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of societal and technological change.

Programme Specific Outcomes

On successful completion of the Program, the students shall be able to:

PSO 01: Capable of demonstrating comprehensive knowledge and understanding of Computer Applications, Data Science and AI/ML techniques.

PSO 02: Identify, formulate and apply appropriate techniques in the areas related to Software development, big data, Network, Cloud computing technologies and related domains of varying complexities in real-time applications.

PSO 03: Conceive, Design and Develop Various Computer Applications and be able to apply data science and AI/ML techniques in specific domains such as healthcare, finance, agriculture, marketing, etc.

Student handbook

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Program Regulations

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USP

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Career Opportunities

  • AI Engineer

    Design and develop artificial intelligence systems and solutions.

  • Machine Learning Engineer

    Build machine learning models and algorithms for data-driven insights.

  • Data Scientist

    Analyze and interpret complex data using advanced techniques to inform decision-making.

  • Deep Learning Specialist

    Develop and optimize deep learning models for complex data analysis.

  • Natural Language Processing (NLP) Engineer

    Enhance human-computer interaction using language processing techniques.

  • Computer Vision Engineer

    Develop systems that interpret and understand visual data from the world.

  • Robotics Process Automation (RPA) Developer

    Design and implement automated processes for businesses using robotic technology.

  • AI Researcher

    Conduct research to push the boundaries of artificial intelligence technologies.

  • AI Consultant

    Advise businesses on how to implement AI solutions for optimization and growth.

  • Algorithm Developer

    Create and optimize algorithms to solve complex problems efficiently.

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