BCA Data Science

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 Data Science

Programme Overview

B.Sc. Data Science 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 for data collection, exploration, manipulation, 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
  • 02Digital Computer Fundamentals - ECE2009
  • 03Fundamentals of Data Science - CSA1003
  • 04Problem Solving using C - CSA1001
  • 05Web Design and Development - CSA1002
  • 06Communicative English - ENG1003
  • 07Introduction to Soft Skills - PPS1001
  • 08Kali Kannada / Tili Kannada - KAN1001 / KAN2001
  • 01Statistical Methods and Techniques - MAT1006
  • 02Programming in Python - CSA1004
  • 03Data Structures and Algorithms - CSA2001
  • 04Operating Systems and Unix Programming - CSA1006
  • 05Computer Networks - CSA2004
  • 06Technical Written Communication - ENG1005
  • 07Employability for Young Professionals - PPS1006
  • 01Relational Database Management Systems - CSA2003
  • 02Fundamentals of Software Engineering - CSA2006
  • 03Data Modelling and Visualization - CSA2018
  • 04Object Oriented Programming using Java - CSA1005
  • 05Artificial Intelligence - CSA2020
  • 06Discipline Elective 1 - CSAXXXX
  • 07Being Corporate Ready - PPS2002
  • 08Environmental Studies and Sustainable Development - CHE1020
  • 01R Programming for Data Science - CSA2019
  • 02Android Mobile Application Development - CSA3003
  • 03Data Warehousing and Data Mining - CSA2021
  • 04Discipline Elective 2 - CSAXXXX
  • 05Machine Learning Algorithms - CSA3002
  • 06Capstone Project - CSA3001
  • 07Problem Solving through Aptitude - PPS3001
  • 01Deep Learning - CSA3071
  • 02Big Data Analytics - CSA3004
  • 03Internet of Things - CSA3005
  • 04Natural Language Processing - CSA3014
  • 05Essentials of Cloud Computing - CSA2008
  • 06Discipline Elective 3 - CSAXXXX
  • 07Open Elective 1 - XXX XXXX
  • 01Computer Vision - CSA3036
  • 02Pattern Recognition - CSA3052
  • 03Open Elective 2 - XXX XXXX
  • 04Discipline Elective 4 - CSAXXXX
  • 05Internship - CSA3008

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

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

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

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

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

PO 12: 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-1: [Data Analysis]: Capable of demonstrating comprehensive knowledge using statistical and machine learning techniques to analyze data and derive meaningful insights and patterns.

PSO-2: [Design/ Development of Solutions]: Identify, formulate, and apply the knowledge of Machine Learning algorithms, Deep Learning algorithms, and Big Data technologies and tools for processing and analyzing large datasets.

PSO-3: [Data Science Applications]: Students should be able to apply data science techniques and translate data insights into actionable recommendations in specific domains, such as finance, healthcare, marketing, etc.

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Career Opportunities

  • Data Analyst

    Analyze and interpret data to provide insights and support decision-making.

  • Business Analyst

    Identify business needs and propose data-driven solutions.

  • Data Scientist

    Use advanced analytical techniques and algorithms to interpret complex data.

  • Data Engineer

    Design and build systems for collecting, storing, and analyzing data.

  • Machine Learning Engineer

    Develop algorithms and models for machine learning applications.

  • AI Specialist

    Design and implement artificial intelligence systems and solutions.

  • Big Data Analyst

    Analyze and interpret large datasets to identify trends and patterns.

  • Data Visualization Specialist

    Create visual representations of data to facilitate understanding.

  • Statistical Analyst

    Apply statistical methods to analyze and interpret data.

  • Operations Analyst

    Evaluate operational processes and recommend improvements based on data.

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