B.Sc Computer Science (Data Science)

OVERVIEW OF THE PROGRAMME

The Data Science Program is meticulously crafted to provide students with an in-depth understanding and hands-on experience in the cutting-edge field of data science. It combines rigorous instruction in statistical analysis, machine learning algorithms, and data processing with practical applications to solve real-world problems. Through engaging coursework and collaborative projects, students develop a strong foundation in both the theoretical and practical aspects of data science, including data visualization, predictive modeling, and data mining. The program is designed to empower students with the skills necessary to analyze large datasets, uncover hidden patterns, and make data-driven decisions. With a focus on preparing students for successful careers in this dynamic and rapidly evolving field, the program emphasizes critical thinking, problem-solving, and effective communication. The aim is to produce highly skilled data scientists who are ready to contribute to industry, academia, and research by leveraging big data to drive innovation and progress.

About the progamme 

B.Sc in data science is a three year under graduate program offered by Rathinamcollege of arts and science,Coimbatore. Datascience is in degree for who seek programmer in software industry.The field of data science continues to evolve rapidly, driven by advancements in technology, increased data availability, and growing demand for data-driven insights in both the public and private sectors. As such, data science professionals require a diverse skill set, including proficiency in programming languages like Python or R, familiarity with data manipulation and visualization libraries, and a strong understanding of statistical concepts and machine learning algorithms.Data science involves various stages such as data collection, cleaning, exploration, analysis, visualization, interpretation, and communication of findings. Some common techniques and tools used in data science include machine learning, statistical modeling, data mining, natural language processing, and big data analytics.

Concepts such as statistics,of many data science techniques. Next, learn to code. Programming is a fundamental skill for data scientists. Python and R are the most popular languages in the field, but knowing SQL can also be beneficial.  Data science is the study of data to extract meaningful insights for business. It is a multidisciplinaryapproach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data.

PEO, PO and PSO

Program Educational Objectives (PEO):

The B.Sc. Data Science program describe accomplishments that graduates are expected to attain within five to seven years after graduation.

  • PEO1 : Our graduates will excel with professional skills, fundamental knowledge, and advanced futuristic technologies to become Data Scientists, Data Analyst, AI Research Scientists, or Entrepreneurs
  • PEO2 : Our graduates will establish their knowledge by adopting Data Science Technologies to solve complex real-world problems with accurate, thoughtful solutions
  • PEO3 : Our graduates will engage in lifelong learning to excel in their profession with social and ethical awareness and responsibility

Program Outcomes (PO):

On successful completion of the B.Sc. DataScience

  • PO1: Apply analytical and critical thinking to identify, formulate, analyze, and solve Complex real world problems in order to reachnuanced authenticated conclusions
  • PO2: Possess the ability to demonstrate advanced independent critical enquiry, analysis and reflection of modern statistical methodology and computing
  • PO3: Have a set of flexible and transferable skills for different types of employment, both within the Information Technology sector and beyond, in both global and local organizations
  • PO4: Develop and implement data analysis strategies base on the oretical principles, ethical considerations, and deep, detailed and broad knowledge of the underlying data and its implications in the context from which the data was taken
  • PO5: Be critical and creative thinkers, with an aptitude and appreciation for continue dself-directed learning in the evolving world of data science, artificial intelligence and social media
  • PO6: Design and develop research-based solutions for complex problems with specified needs with appropriate ethical consideration for public health, safety, culture, society, and the environment.
  • PO7: Establish the ability to listen, read, proficiently communicate and articulate nuanced data and information through traditional and digital channels to audiences with diver seperspectives
  • PO8: Articulate and evaluate appropriate legal and ethical standard spertaining to all forms of communications, network security and human rights.
  • PO9:  Showcase an understanding of the inter disciplinary nature of data, information and community and its influence innovation and progress within the current local or global context.
  • PO10:  Be able to initiate and implement constructive change in their communities with their skills in data and information, including various professions and workplaces.

Program Specific Outcomes (PSO):

After the successfull completion of B.Sc. Data Science program the students are expected to

  • PSO1: Ability to design, develop, implement and apply Analytical skills related to Research and Real-world problems
  • PSO2: Ability to apply tools and techniques to provide successful solutions in the multi disciplinary field
  • PSO3: Ability to critique the role of  information and analytics for a innovative career, research activities and consultancy/

Career Opportunities

Data Scientist: Data scientists are at the heart of extracting actionable insights from complex datasets. They use a combination of programming, statistical skills, and machine learning to analyze data and predict trends.

Data Analyst: Data analysts focus on processing and performing statistical analysis on existing datasets. Their work often involves creating visualizations, dashboards, and reports to help businesses make informed decisions.

Machine Learning Engineer: These professionals specialize in creating algorithms and predictive models to make predictions or automate decision-making based on data. They work closely with data scientists to implement and optimize machine learning projects.

Data Engineer: Data engineers build and maintain the architecture (like databases and large-scale processing systems) that allows for the efficient analysis and processing of large data sets. They ensure that data flows smoothly from source to database to analytics.

Business Intelligence Analyst: BI Analysts use data analytics and visualization tools to develop insights into the business performance and market trends. They help in strategic planning by providing data-based recommendations to the management.

Quantitative Analyst (Quant): In the finance sector, quants use data analytics to model and predict financial markets, helping companies in risk management, investment management, and trading strategies.

Data Analytics Consultant: These consultants work across industries, advising businesses on how to use data analytics to improve processes, increase efficiency, and boost profits. They often work on a project basis and may serve multiple clients.

Big Data Engineer/Architect: Big Data Engineers or Architects handle the management and organization of big data environments. Their work involves designing, building, and maintaining scalable and secure big data ecosystems.

AI Specialist: Specialists in artificial intelligence develop AI models and applications, often working closely with machine learning engineers and data scientists to integrate AI capabilities into various products and services.

Curriculum Structure

Ability Enhancement Course
S.No Course Code Course Pre-requesite Offering Department Mandatory
1 Environmental Studies – General Yes
2 Women Studies – Commerce II Yes
3 Constitution of India – Commerce I Yes
4 Human Rights – General Yes
5 Yoga – Tamil Yes
6 NCC – Viscom Yes
7 Communicative English – English Yes
8 Quantitative Apptitude – Mathematics Yes
S.No. Sem Part Sub Type Course Code Course Name Credit Hours INT EXT Total
1 1 1 L1   Language – I 3 5 50 50 100
2 1 2 L2   English – I 3 5 50 50 100
3 1 3 Core    Programming in C 4 5 50 50 100
4 1 3 Core     C lab 4 4 50 50 100
5 1 3 Allied   Allied-I
 Mathematics for Computer Science 		4 5 50 50 100
6 1 4 SEC   Skill Enhancement Courses – I Database Management System / Practical – Database Management System Lab 4 4 50 50 100
7 1 4 AEC   Ability Enhancement Course I Environmental Studies or Universal Human Values & Professional Ethics 2 2 50 0 50
            24 30 350 300 650
                     
1 2 1 L1   Language – II 3 5 50 50 100
2 2 2 L2   English – II 3 5 50 50 100
3 2 3 Core    Problem Solving and Python Programming 4 5 50 50 100
4 2 3 Core     Problem Solving and Python Programming  Lab 4 4 50 50 100
5 2 3 Elective   Elective  – I Entreprenuership Development 4 4 50 50 100
6 2 3 Allied   Discreate Mathematics 4 5 50 50 100
7 2 4 AEC   Ability Enhancement Course II Design Thinking 2 2 50 0 50
8 2 5 Ext   Extension Activity – I (NASA) 1 0 25 0 25
            25 30 375 300 675
                     
1 3 1 L1   Language – III 3 4 50 50 100
2 3 2 L2   English – III 3 4 50 50 100
3 3 3 Core    Data Engineering 4 6 50 50 100
4 3 3 Core     Data Engineering Lab 4 4 50 50 100
5 3 3 Allied   Quantitative Aptitude 4 5 50 50 100
6 3 4 SEC   Applied Data Structures 4 5 50 50 100
7 3 4 AEC   Ability Enhancement Course III Soft Skill-1 2 2 50 0 50
8 3 3 ITR   Internship / Industrial Training (Summer vacation at the end of II semester activity) 2 0 50 0 50
9 3 5 Ext   Extension Activity – II (NASA) 1 0 25 0 25
            27 30 425 300 725
                     
1 4 1 L1   Language – IV 3 4 50 50 100
2 4 2 L2   English – IV 3 4 50 50 100
3 4 3 Core    Programming in R Language 4 6 50 50 100
4 4 3 Core     Programming in R Lab 4 4 50 50 100
5 4 3 Allied   Maths for data Science 4 5 50 50 100
8 4 3 Elective    Elective II – Data Mining 4 5 50 50 100
7 4 4 AEC   Ability Enhancement Course IV Soft Skill-2 2 2 50 0 50
8 4 5 Ext   Extension Activity – III (NASA) 1 0 25 0 25
            25 30 375 300 675
                     
1 5 3 Core    Data Visualization  4 6 50 50 100
2 5 3 Core     Data Visualization Lab 4 6 50 50 100
3 5 3 Elective    Elective III – Image Analytic 4 6 50 50 100
  5 3 PRJ   Project 0 6 0 0 0
4 5 4 SEC   Machine Learning Techniques 4 6 50 50 100
5 5 3 ITR   Internship / Industrial Training (Summer vacation at the end of IV semester activity) 2 0 50 0 50
6 5 5 Ext   Extension Activity – IV (NASA) 1 0 25 0 25
            19 30 275 200 475
                     
1 6 3 Core    Natural Language Processing 4 6 50 50 100
2 6 3 Core     Natural Language Processing Lab 4 4 50 50 100
3 6 3 Elective    Elective IV – Deep Learning 4 6 50 50 100
4 6 3 PRJ   Core Project 8 8 100 100 200
5 6 4 SEC   Big Data Acquisition and Analysis 4 6 50 50 100
            24 30 300 300 600
          Total credit 144 180 2100 1700 3800
                     
                 
Additional Credits
S.No. Sem Part Sub Type Course Code Course Name Credit Hours INT EXT Total
1 2 6 VAC   VAC – Microsoft CoE Course / NPTEL 2 2 50 0 50
3 4 6 IDC   VAC – Microsoft CoE Course / NPTEL 2 2 50 0 50
4 5 6 VAC   VAC – Microsoft CoE Course / NPTEL 2 2 50 0 50
                     
                     
Certificate on Minor Discipline
S.No. Sem Part Sub Type Course Code Course Name Credit Hours INT EXT Total
1 2 6 MD   Course – I 5 2 0 100 100
2 3 6 MD   Course – II 5 2 0 100 100
3 4 6 MD   Course – III 5 2 0 100 100
4 5 6 MD   Course – IV 5 2 0 100 100