B. Tech in Data Science

A B.Tech. in Data Science typically covers a blend of subjects from computer science, mathematics, statistics, and data analysis. Some core subjects you might encounter include:

1. Programming Languages: Proficiency in languages like Python, R, SQL, or others used for data manipulation and analysis.

2. Statistics and Probability: Understanding statistical concepts, hypothesis testing, regression analysis, and probability theory.

3. Data Management: Database systems, data warehousing, data cleaning, and preprocessing techniques.

4. Machine Learning and Data Mining: Techniques and algorithms used for pattern recognition, predictive modeling, and extracting insights from data.

5. Data Visualization: Tools and methods for presenting data visually to aid in understanding and decision-making.

Practical Experience:

Data Science programs often involve hands-on projects, case studies, and practical assignments that allow students to apply their knowledge and skills to real-world data sets.

Capstone Projects:

Some programs may culminate in a capstone project where students work on a significant data science project, integrating their knowledge and skills gained throughout the program.

Fee Structure
The Academic Session 2024 – 28
FEESFirst (Rs)Second (Rs)Third (Rs)
FEESFourth (Rs)Fifth (Rs)Sixth (Rs)
FEESSeventh(Rs)Eighth (Rs)Note: Registration Fee, Examination fee &
Caution money not Included.

The basic course eligibility is to have at least 50% in Class XIIfrom any recognized board. 5% relaxation in ST SC OBC

Skills Developed

Throughout the program, students develop skills in data analysis, programming, statistical modeling, machine learning, data visualization, and critical thinking, which are highly sought after in the data-driven job market.

Career Avenues for  B.Techin Data Science

Graduates with a B.Techin Data Science can pursue various careers in industries such as finance, healthcare, technology, marketing, e-commerce, and more. Job roles might include data analyst, data scientist, business intelligence analyst, machine learning engineer, or data engineer.