BSc Data Science and Analytics

Bachelor of Science (Honours / Honours with Research) with Global Qualification

Data Science and Analytics with Industry- Integration Certification from GUVI HCL


Eligibility

Candidates must have successfully completed their 10 + 2 (Class 12) or equivalent examination from a recognized board.

Overview

The Bachelor of Science in Data Science is a rigorous academic programme designed to cultivate advanced analytical capabilities among aspiring data scientists. The curriculum is meticulously structured to develop profound scientific reasoning and critical analytical skills, enabling students to conduct sophisticated research and generate evidence-based insights through comprehensive data interpretation.

The programme integrates sophisticated qualitative and quantitative analytical methodologies, empowering students to deconstruct complex data patterns and extract meaningful trends. Students will acquire advanced computational techniques, including statistical analysis, data mining, and machine learning, to transform raw data into strategic intelligence across diverse financial systems, social dynamics, and organizational infrastructure.

For those seeking a BSc Data Science syllabus or information on BSc Data Science subjects, our curriculum is designed to encompass a wide range of data-related concepts and methodologies. It offers comprehensive training through hands-on projects and practical exercises. Additionally, we provide insights into BSc Data Science colleges in India and specific guidance on the best BSc Data Science colleges in Bangalore for students looking to pursue their dreams. Our programme also highlights BSc Data Science eligibility criteria to help aspiring data scientists understand their path.

We understand the importance of accessibility, offering online and offline BSc Data Science courses in Bangalore and ensuring inclusivity for learners. Our focus on interdisciplinary learning ensures that students acquire technical skills and a holistic understanding of how data science intersects with various industries and domains. Through industry partnerships and guest lectures, students receive valuable insights into the practical challenges and opportunities in the field.

When considering BSc Data Science and Analytics colleges in Bangalore, our programme stands out for its innovative approach, ensuring students are well-prepared for the evolving global economy. Our curriculum fosters creativity, enabling students to develop skills in advanced analytics methods, programming languages like Python and R, and business problem-solving using tools like Tableau and SAS. As one of the best BSc Data Science colleges in Bangalore, we are committed to delivering affordable yet high-quality education, empowering students to tackle challenges and seize opportunities in data science.

The programme offers two main tracks:
(i) a 3-year undergraduate degree and
(ii) a 4-year undergraduate degree with Honours, emphasising research.

Certification Offered:

Industry-Integration Certification from GUVI  HCL

The BSc Data Science & Analytics with additional certification programme from GUVI HCL is designed to strengthen practical skills and impart industry-relevant knowledge. It equips learners with essential competencies for a successful career in data science, emphasizing data analysis and visualization techniques to help students interpret and present data effectively. GUVI's courses provide an opportunity to expand knowledge and gain hands-on experience in data science, enhancing career prospects in this dynamic field. The collaboration will be available starting from the second semester onwards. Upon successful completion, students will receive a GUVI HCL certificate co-branded with their institution

Program code: 003A
Course code : 3A06
Course Commencement : Jul 2026

Study Campus

School of Sciences
#34, 1st Cross
J C Road
Bangalore - 560027
P +91 80434 30100


Admissions Office

JAIN Knowledge Campus
# 44/4, District Fund Road
Jayanagar 9th Block Campus
Bangalore - 560 069
P : +91 73378 80218
P : +91 98440 73343

Curriculum Structure

  • English – I
  • Core papers
  • Database management system*
  • Basic mathematics*
  • Management concepts and Marketing management
  • Economics – I
  • ICT for analytics – I* / Academic writing

  • English – II
  • Core papers
  • Descriptive statistics*
  • Financial statement analysis
  • Economics – II
  • Environment studies
  • Mind management and Human values (compulsory)

  • Probability theory and Theoretical distribution
  • Structural query language
  • Business analytics
  • Business analytics programming
  • Financial management
  • Communicative English
  • ICT for analytics – II / Data visualization

  • Business forecasting
  • Sampling distributions and Statistical inference
  • Research methodology
  • Analytics narration / Statistical tools - SPSS
  • Financial analytics / Psychology
  • Marketing analytics / Cultural studies

  • Financial management
  • Business simulation
  • Analytics for logistics
  • Data manipulation and Data Cleaning using R / Big Data analytics
  • Analytical tools – Python / Deep learning
  • Business environment / Digital marketing

  • Design of experiments and Multivariate analysis
  • Econometrics
  • Predictive modeling using SaS / Artificial intelligence
  • Advanced analytics / Data mining
  • Operations research / Project
  • HR analytics / Gandhian thoughts

Course Highlights

  • Develop concepts and designs in a lively studio environment, conversing, making and drawing alongside others.

  • Economic problem-solving skills to discuss the opportunities and challenges of the increasing globalisation of the world economy.

  • Ability to apply analytical techniques to analyse and interpret data.

  • Ability to use Python, R, etc., tools to solve business analytics problems.

  • Recognise the importance and value of various disciplines' mathematical and statistical thinking, training, and problem-solving approaches.

  • Ability to understand a problem with their knowledge of different functional management areas.

  • Analyse the efficiency and equity implications.

  • Ability to perform descriptive, predictive, and prescriptive analytics.

Career Enhancement Programs

Our career enhancement programmes follow industry standards, helping students develop skills needed for today's job market. Evaluation includes various assessments, such as assignments and exams. We focus on soft skills like communication and presentation to boost employability.

Career Outcomes

A degree in Data Science opens doors to abundant career opportunities. They can work on diverse profiles and in different fields like:

  • Data Analyst

  • Data Engineers

  • Developers & Consultants

  • Database Administrator

  • Machine Learning Engineer

  • Data Scientist

  • Data Architect

  • Statistician

  • Business Analyst

  • Data and Analytics Manager

  • Data modelling

  • Business intelligence development

FAQ's

Is Data Scientist a stressful job?


Data Science can be stressful as data scientists often have to work with large amounts of data, complex problems, and tight deadlines. They also need to keep up with evolving technologies. However, if one can manage time properly and prioritise their tasks, it can be handled well.

What are the subjects in Data Science?


Data science courses cover a variety of subjects, including Statistics, Programming, Machine Learning, and Artificial Intelligence.

Who is eligible for Data Analyst?


To be eligible for a Data Analytics programme, students must enrol in a Bachelor's degree (Bachelor of Science (BSc) in Data Science and Analytics. Additionally, students can specialise in the field by opting for a Master of Business Administration (MBA) or Postgraduate Diploma in Data Science and Analytics.

Is Data Science Coding?


Yes. Data science heavily involves coding, a significant instrument in the employment of, study, synthesis, and visualisation of data to provide useful information.

Is Data Science Math heavy?


Yes. Data Science is built on Math, including calculus, linear algebra, and statistics. Data scientists use Math to analyse data, build models, and discover insights. Therefore, students need to gain proficient knowledge in subjects such as Mathematics, Statistics, And Programming.

Can I do Data Analyst after the 12th?


Yes. Students can become data analysts after Class 12th by opting for a Bachelor’s programme in the relevant field, such as a BSc in Data Science and Analytics.

Is Data Science difficult to study?


Yes. Data science can be challenging to study, but it's also a rewarding field with a high demand for skilled professionals.

Is Data Science a high-paying job?


Yes. Data Science offers high-paying jobs in different sectors, especially in top tech and analytics firms. Some of the most high-paying job roles include data scientists, machine learning engineers, and data analysts.

Who is eligible for BSc Data Science?


To be eligible for a BSc in Data Science programme, students need to score a minimum of 55% in 10+2 from a recognised board in the Science stream. Students must have Mathematics and Statistics as core subjects in their 10+2.

Can I do a BSc in Data Science without Maths?


No. Students cannot pursue a BSc in Data Science without some Math. Statistics, calculus, and linear algebra are the most relevant areas of the Math for Data Science syllabus.

What is the salary of BSc Data Science?


The salary for a data scientist in India can range from INR 4 - 57 LPA, depending on experience and job role

Is Data Science a good career?


With the help of Data Science, it is possible to turn a business problem into a research project, which can then be converted back into an actual solution. Due to the existence of so many Data Science positions and the lucrative compensation, a Data Science career is one of the most sought-after ones.

Is Data Science in demand?


Yes. Data Science is in high demand, and various industries have a strong job outlook. The field is growing rapidly as companies use data to improve quality and financial growth

Is Data Science hard?


Data Science can be challenging, requiring proficiency in various technologies and tools, such as SQL, Python, R, and machine learning libraries. But it's not impossible to learn. With the proper preparation and determination, students can thrive and build a strong foundation for a successful career.