B. Sc (Data Science ) Program
Duration: Three Years
Overview
- Every facet of modern life from social networking to scientific research, finance to healthcare , produce an immense amount of data which needs to be analysed and turned into intelligence for actionable insight.
- B.Sc Data Science is a unique Program designed to impart the essential skills to cater to the fastest growing trends in the industry.
- The program will provide students with an opportunity to get exposed to the broad range of subjects leading to a high-level of data science skills.
- The curriculum is a blend of core and advanced specialised courses in statistics and predictive analytic using R, Python, Machine Learning , Data Visualisation with a strong foundation of Mathematics, Communication skills and entrepreneurship.
- Choice based electives from other Programs diversify the domain of knowledge in an interdisciplinary manner.
- Project intern-ship give the much needed hands on learning experience in the final semester, where they can analyse and draw actionable inferences from a raw data using the analytics based on statistical and mathematical understanding.
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- Expertise faculty with great experience in industry, academics, research, development and innovation
- Curriculum is based on the latest trends in the ever changing and evolving fields of Data Science
- Excellent placement cell for further opportunities
- State-of-the-art Computer Laboratory and Infrastructure
- Large numbers of Extra-curricular and Co-curricular engagement opportunities
Eligibility: Candidates who have completed 10+2 in Any stream (All Boards) with minimum 50% are eligible for admission to BSc-Data Science Program.
Admission Procedure: Eligible candidates are required to appear for an interaction with faculties of Data Science.
Course Structure | ||
---|---|---|
Semester – I | ||
Sr.No. | Course Name | Credits |
1 | Python Programming | 4 |
2 | Databases and My SQL | 4 |
3 | Statistics-I | 4 |
4 | Elementary Calculus | 2 |
5 | Matrix Theory | 2 |
6 | HR/ Management | 3 |
7 | Communication-I | 3 |
Semester – II | ||
Sr.No. | Course Name | Credits |
1 | Data Structures | 4 |
2 | Statistics-II | 4 |
3 | Object Oriented Programming | 4 |
4 | Ordinary differential equations | 2 |
5 | Advanced Calculus | 2 |
6 | Statistical modelling | 2 |
7 | Humanities | 2 |
8 | Communication-II | 2 |
Semester – III | ||
Sr.No. | Course Name | Credits |
1 | R programming for Data Science | 4 |
2 | Regression analysis and Bayesian statistics | 5 |
3 | Data Visualization and Tableau | 5 |
4 | Discrete Mathematics and Linear Algebra | 5 |
5 | General Elective-I | 3 |
6 | Operation Research | 2 |
7 | ID course | 2 |
Semester – IV | ||
Sr.No. | Course Name | Credits |
1 | Data mining and warehousing ( Using R / Python) | 3 |
2 | Data analytic using Hadoop | 3 |
3 | Machine Learning | 5 |
4 | Cloud computing | 3 |
5 | General Elective-II | 3 |
6 | Optimization Techniques | 2 |
7 | Environment Science | 2 |
8 | Khoj | 3 |
9 | ID course | 2 |
Semester – V | ||
Sr.No. | Course Name | Credits |
1 | Internet of things for Data Analytic | 4 |
2 | Deep Learning | 4 |
3 | Soft Computing | 4 |
4 | Big Data | 4 |
5 | Numerical methods and simulation | 5 |
6 | Entrepreneurship | 3 |
7 | Research methodology | 3 |
Semester – VI | ||
Sr.No. | Course Name | Credits |
1 | Intern-ship | 17 |
Semester | List of Electives |
Sem-III | Biostatistics |
Image processing | |
Econometrics | |
Text analysis | |
Sem-IV | Artificial intelligence |
Bioinformatics | |
Cyber Security |