Department Profile

Department of Computer Science with Data Analytics

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

Category:

CS with DA

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

Highlights

1. Curriculum Design is on par with the Industry (R, Python, SQL, Tableau, PowerBI, Microsoft Excel, Big Data Analytics, Machine Learning etc..)
2. Training on various coding platforms like codechef, hackerRank, Leetcode etc.. and soft skill
3. Excellent Placement Training

Association

Association Name : Association of Data Science and Analytics

ASSOCIATION OF DATA SCIENCE AND ANALYTICS

Dr. E. RAMADEVI

MCA, MPhil, PhD

Associate Professor & Head

EMail: ramadevi@ngmc.org

Ms. M. Sivakami Sundareswari

MCA

Assistant Professor

EMail: sivakamisundareswari@ngmc.org

Mr .S. Earnest Rajadurai

M.Sc. MPhil, B.Ed,(PhD)

Assistant Professor

EMail: earnest@ngmc.org

Program Educational Objectives (PEOs)
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
Programme Outcomes (POs)
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 common 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.

B.Sc. Computer Science with Data Analytics Effective from the year 2022 onwards

Program Specific Outcomes (PSOs)
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.

Research & Awards (Details)	PDF File
Dr. E. Rama Devi has given the invited talk titled "Role of Modern Mathematics in the Theory of Computation" at the International Conference on History of Modern Mathematics conducted by Institute for Advanced Study in History of Science, North West University, Xian, China from 18 – 24th August 2019
Dr. E. Rama Devi organized a workshop on Data Mining using R Tool sponsored by TNSCST on Jan 2020
Dr. E. Rama Devi completed a course on IBM Professional Certificate in Data Science by Coursera in the month of June 2022
Dr. E. Rama Devi completed the NPTEL course on Python for Data Science in the year 2023

A Survey on Machine Learning Algorithms

Dr. E. Rama Devi, M. Meenakrithika,

The International Journal of Analytical and Experimental Modal Analysis (IJAEMA) ISSN No.0886-9367

Dec 2019

FILE (PDF)

Review on Machine Learning Algorithms

Dr. E. Rama Devi, M. Meenakrithika

The International Journal for Research in Science Engineering and Technology ISSN 2394-739X

2020

FILE (PDF)

Identification of malware using enhanced malware detection pre-processing techniques

Dr. E. Rama Devi, M. Meenakrithika

International Journal of advanced science and Technology ISSN: 2005-4238 (Print) ISSN: 2207-6360 (Online)

2020

FILE (PDF)

A Novel Portable Executable malware Detection using Random Forest with feature set generation algorithm (RF-FSGA),

Dr. E. Rama Devi, M. Meenakrithika

Design Engineering ISSN: 0011-9342

2021

FILE (PDF)

Current Challenges and New Directions in Sentiment Analysis on Web Based Media Information

Dr.E. Rama Devi, K. Brindha

Design Engineering ISSN: 0011-9342

2021

FILE (PDF)

Analysis and Performance of various Data Mining Techniques used for malware detection and classification

Dr. E. Rama Devi, M. Meenakrithika

Journal of Education: Rabindra Bharathi University, ISSN 0972-717

2021

FILE (PDF)

Farmer Product Direct Selling System

Dr.E. Rama Devi, P. Madhan kumar

International Journal of Creative Research Thoughts ISSN: 2320-2882

2022

FILE (PDF)

Survey on Twitter Sentiment Analysis using Machine Learning

Dr.E. Rama Devi, K. Brindha

International Journal for Research in Science, engineering and Technology ISSN: 2394-739X

2022

FILE (PDF)

Weight Based Pre-Processing Algorithm (Wbpa) For Data Pre-Processing In Sentiment Analysis

Dr.E. Rama Devi, K. Brindha

Journal of Pharmaceutical Negative Results ISSN: 2229-7723

2022

FILE (PDF)

A novel hybrid approach for twitter sentiment analysis in Machine Learning

Dr.E. Rama Devi, K. Brindha

Technical Security Journal ISSN: 1434 – 9728

2023

FILE (PDF)

Twitter Sentiment Analysis for Feature Extraction using Support Vector Machine (SVM) with TF-IDF

Dr. E. Rama Devi, K. Brindha

Journal of Survey in Fisheries Sciences, ISSN: 2368-7487

2023

FILE (PDF)

Twitter Data Feature Selection using Enhanced Genetic Algorithm

Dr. E. Rama Devi, K. Brindha

Tuijin Jishu/Journal of Propulsion Technology, ISSN: 1001-4055

2023

FILE (PDF)

Ensemble Random Forest With LSTM Neural Network (ERF-LSTM) Method For Classification Of Twitter Sentiment Analysis

Dr. E. Rama Devi, K. Brindha

Journal of Nonlinear Analysis and Optimization : ISSN : 1906-9685

2024

FILE (PDF)

Summer Camp for School Children on Fun Filled Learning with AI Tools

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