Department of Computer Science with Data Analytics – SF

B.Sc  Computer Science with Data Analytics 

About the Course

The Department of Computer Science with Data Analytics was established in the year 2022 with the goal of giving students the skills and competences necessary to adapt to a rapidly changing environment as well as to develop a compassionate attitude. With companies having excessive data, the whole process of managing, storing, and interpreting data for useful information is very important but a bit difficult. That is why qualified and experienced data analysts are given the responsibility of doing the same. The Department offers  Computer Science with Data Analytics programme with the sanction strength of UG 40 students. The program also    emphasizes a thorough understanding of the concepts of data analytics and data science and a comprehension of the specialty. The department’s main goal is  to provide its students with top-notch placements, research and teaching opportunities and to expand the boundaries of computer science and automation research. The department  provides a spectrum of basics to advanced mathematical methods and their applications to both conventional and IT industries that enable to tackle emerging problems. The graduates will develop an in-depth understanding of data analytics and the techniques for analysis of quantitative and qualitative data to arrive at solutions. They will be able to identify patterns, predict trends, and analyze data from various sectors such as manufacturing, banking and finance, retail, and healthcare. The academic track of the program is a blend of core and advanced specialist subjects.

Highlight of the programme

  • · Highly Experienced and certified Faculties who alter their knowledge, views, and insights to keep their teaching current, relevant, and engaging for their students.
  • · The curriculum places a strong emphasis on imparting practical knowledge combined with real-world experience and a suitable predisposition toward cutting edge     research and application development in computer science and data analytics that are judged fit for the industrial demands of the twenty-first century.
  • · The curriculum is designed with a proper blend of research and industry-relevant subjects taught through collaborative learning. It has been designed to bridge the     gap between Industry and academics and is meticulously reviewed by many industry experts, academicians and other stakeholders
  • ·  Well-equipped and upgraded laboratories and smart classrooms.
  • ·  Students are instructed to practice in the code development platforms like codechef, Leetcode, hacker Rank etc.. to gain the technical knowledge
  • ·  Students are advised to do certification courses in the platforms like great learning, simplilearn etc.. and MOOC courses like NPTEL, Spoken tutorial etc.
  • ·  Students have to undergo minimum of 2 Value Added Course to help students obtain and develop innovative and creative abilities as well as a more holistic                viewpoint and a better knowledge of contemporary industry concerns.
  • ·  Compulsory project to get the real time exposure.
  • ·  Excellent Library with all relevant books of data science and data analytics
  • ·  Excellent Placement Training from the industry experts
  • ·  Signed an MoU with Vodafone Idea Foundation which provides the free technical course and guidance for the students
  •     Extension Activities – Summer Camp for School Children

Key Expertise Offered

  • Foundation of Data Science
  • Basic Programming Languages (C, Java)
  • Statistical  Programming Languages (R, Python)
  • SQL and NO SQL Data Base
  • Microsoft Excel
  • Linear Algebra for Data Science
  • Statistical Analysis (Descriptive, Inferential, Hypothesis testing)
  • Data Visualization (Power BI, Tableau)
  • Predictive Analysis using R and Python
  • Data Mining and Warehousing
  • Advanced Data Analysis using Big Data Analysis and Machine Learning
  • Essential Data Analyst Soft Skills like communication skills, problem solving abilities and critical thinking

Top 10 Global Data Science Recruiters

  • Google
  • Amazon
  • Microsoft
  • Capgemini
  • Infosys
  • Wipro
  • Cognizant
  • TCS
  • IBM
  • Accenture

Programme Outcome

Upon completion of the programme, Graduates could take roles such as:

  • Data Scientist
  • Data Analyst
  • Data Architect
  • Data Engineer
  • Business Analyst
  • Statistician
  • Database Administrator
  • Data Storyteller
  • Machine Learning Scientist/Engineer
  • Power BI/Tableau Developer

Vision

To prepare the next generation of practitioners and researchers for a data centric world and to achieve the academic excellence and research in the field of Data Science at the national and global levels.

Mission

To develop professionals who are skilled in the area of Data science and analytics
To impart quality and value–based education and contribute towards the innovation of Computing expert systems.
To apply new advancements in high performance computing hardware and software
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Dr.E.Ramadevi

Assistant Professor & Head
EMail:
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Meenakrithika M

Assistant Professor
WhatsApp-Image-2026-07-14-at-9.59.30-AM

Mrs M.Nandhiya

Assistant Professor
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Mrs.C.Akila

Assistant Professor
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Dr. A. Albina

Assistant Professor

2026-2029

2025-2028

2024-2027

Association Name : Association of Data Science and Analytics

ASSOCIATION OF DATA SCIENCE AND ANALYTICS

On successful completion of the B.Sc. Computer Science with Data Analytics
PO1
 Disciplinary knowledge: Capable to apply the knowledge of mathematics, algorithmic
principles and computing fundamentals in the modeling and design of computer based systems
of varying complexity.

PO2
 Scientific reasoning/ Problem analysis: Ability to critically analyze, categorizes, formulate and
solve the problems that emerges in the field of computer science with Data Analytics

PO3
 Problem solving: Able to provide software solutions for complex Data Analysis problems or
processes that meet the specified needs with appropriate consideration for the public health and
safety and the cultural, societal and environmental considerations

PO4
 Environment and sustainability: Understand the impact of software solutions in environmental and societal context and strive for sustainable development
PO5
 Modern tool usage: Use contemporary techniques, skills and tools necessary for integrated
solutions

PO6
 Ethics: Function effectively with social, cultural and ethical responsibility as an individual or as a team member with positive attitude.
PO7
 Cooperation / Team Work: Function effectively as member or leader on multidisciplinary
teams to accomplish a com
mon objective.
PO8
 Communication Skills: An ability to communicate effectively with diverse types of audience
and also able to prepare and present technical documents to different groups.

PO9
 Self–directed and Life–long Learning: Graduates will recognize the need for self–motivation
to engage in lifelong learning to be in par with changing technology

PO10
 Research: Enhance the research culture and uphold the scientific integrity and objectivity.

The B.Sc. Computer Science with Data Analytics program describe accomplishments that graduates are expected to attain within five to seven years after graduation.
PEO1
 Develop in depth understanding of the key technologies in data science and business analytics:
data mining, machine learning, visualization techniques, predictive modeling, and statistics

PEO2
 Apply principles of Data Science to the analysis of business problem
PEO3
 Demonstrate knowledge of statistical data analysis techniques utilized in business decision
making.

PEO4
 To enhance communicative skill and inculcate the spirit through professional activities and to solve the complex problems in data analysis
PEO5
 To embed human values and professional ethics in the young minds and contribute towards nation building

After the successful completion of B.Sc. Computer Science with Data Analytics program, the students are expected to
PSO1
 Impart education with domain knowledge and key technologies in data science and business analytics like data mining, machine learning, No SQL, visualization techniques, predictive modeling, and statistics effectively and efficiently in par with the expected quality standards for Data analyst professional.
PSO2
 Ability to apply the mathematical, technical and critical thinking skills in the discipline of
Data analytics to find solutions for complex problems.