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B.Sc. Computer Science in Data Science
Program details
The B.Sc. Computer Science (Data Science) program offered by UPES School of Computer Science is meticulously crafted to provide students with a comprehensive understanding of various aspects of data science and its applications. This degree equips students with a solid foundation in forecasting, predictive modeling, and statistical fundamentals. The curriculum places a strong emphasis on the mathematical underpinnings essential for effective data analysis.
By offering exposure to a diverse range of industry-standard tools like NoSQL, Data Warehousing, PyTorch, Tableau, R, and Splunk, the program ensures that students gain practical skills that are directly applicable in real-world scenarios. Furthermore, the program delves deep into the realms of statistics and mathematical simulations, empowering students to excel in the dynamic field of predictive analytics and simulation work. These skills are not only in high demand across various industries but also play a pivotal role in shaping professionals capable of contributing to the creation of the Meta Verse.
In conclusion, UPES School of Computer Science's B.Sc. Computer Science (Data Science) program is designed to provide students with a comprehensive education that combines theoretical knowledge with practical skills. The curriculum covers a wide array of topics, including forecasting, predictive modeling, statistical analysis, and the utilization of essential data science tools. By nurturing a strong foundation in both mathematical principles and industry-relevant applications, the program prepares students to meet the demands of the rapidly evolving field of data science and predictive analytics, while also fostering their potential to contribute to cutting-edge developments such as Meta Verse technology.
Program Highlights
- Graduates will master technical skills and cultivate leadership qualities, positioning them as professional scientists capable of excelling in diverse careers.
- The B.Sc. Computer Science (Data Science)program fosters an environment where graduates gain interdisciplinary and multidisciplinary exposure, enabling them to effectively navigate diverse circumstances.
- Graduates will develop a commitment to lifelong learning, adapting and mastering new skills and techniques to address emerging challenges in technology.
- The B.Sc. Computer Science (Data Science)program equips graduates with the ability to analyze real-life problems scientifically, collaborating in multidisciplinary teams, and addressing challenges with an ethical mindset.
- Graduates will proficiently engage in system and application programming, applying computer system concepts, data structures, algorithms, and optimization techniques for effective problem-solving.
- The program empowers graduates to assess, design, propose, and develop analytical systems, enabling them to tackle real-world problems using computational knowledge.
Future Scope / Industry Trends
The future scope of the B.Sc. Computer Science (Data Science) program by UPES School of Computer Science is incredibly promising. As the world becomes increasingly data-driven, the demand for skilled data scientists is soaring across industries. This program equips students with a strong foundation in computer science principles along with specialized training in data science, preparing them to tackle complex data challenges. Graduates will possess the expertise to analyze large datasets, extract meaningful insights, and make data-driven decisions. With the rapid growth of IoT, AI, and machine learning, graduates will be well-positioned to develop innovative solutions in fields like healthcare, finance, e-commerce, and more. The program's practical approach, incorporating real-world projects and industry exposure, ensures that graduates are not only academically proficient but also industry-ready. Overall, the B.Sc. Computer Science (Data Science) program opens doors to diverse career paths, from data analysts and machine learning engineers to data consultants and research scientists, contributing significantly to the evolving landscape of technology and data-driven advancements.
Career Opportunities
The B.Sc. Computer Science (Data Science) program from UPES School of Computer Science equips graduates with a diverse skill set tailored for a range of industry roles. Graduates can pursue positions such as Data Analyst, Software Programmer, Business Analyst, Data Architect, Statistician, Automation Engineer, Data Engineer, and Simulation Architect. This comprehensive program provides a strong foundation in data science, enabling graduates to excel in various sectors requiring data-driven decision-making and technical expertise. Whether analyzing data, developing software solutions, or designing simulations, graduates are well-prepared to contribute effectively to the evolving landscape of technology and data-driven industries.
Placements
The B.Sc. Computer Science (Data Science) program at UPES School of Computer Science offers outstanding placements, providing students with a strong foundation in data science and its applications. The program's industry-aligned curriculum equips students with essential skills in programming, statistics, machine learning, and data analysis. With a focus on practical learning and real-world projects, graduates emerge well-prepared for the demands of the data-driven job market. UPES' strong industry connections and dedicated placement cell play a pivotal role in securing attractive job opportunities for students. Leading tech companies and organizations actively recruit graduates, recognizing their proficiency in data science. This program's consistent track record of impressive placements underscores its commitment to producing job-ready professionals who can excel in various data science roles across diverse industries.
Fee Structure
Click here for detailed Fee Structure.
Curriculum
Semester 1
Course | L | T | P | Credit |
---|---|---|---|---|
Linux Lab | 0 | 0 | 4 | 2 |
Programming in C | 3 | 0 | 0 | 3 |
Programming in C Lab | 0 | 0 | 2 | 2 |
Digital Electronics | 4 | 0 | 0 | 4 |
Problem Solving | 2 | 0 | 0 | 2 |
Living Conversation | 2 | 0 | 0 | 2 |
Environmental Sustainability and Climate Change - I | 2 | 0 | 0 | 2 |
Mathematical Science – I | 3 | 1 | 0 | 4 |
TOTAL | 21 |
Semester 2
Course | L | T | P | Credit |
---|---|---|---|---|
Computing for Sciences | 3 | 0 | 0 | 3 |
Data Structures and algorithms | 4 | 0 | 0 | 4 |
Data Structures and algorithms Lab | 0 | 0 | 2 | 1 |
OOPs using C++ | 3 | 0 | 0 | 3 |
OOPs using C++ Lab | 0 | 0 | 2 | 1 |
Critical Thinking and Writing | 2 | 0 | 0 | 2 |
Environmental Sustainability and Climate Change - II | 2 | 0 | 0 | 2 |
Mathematical Science – II | 4 | 0 | 0 | 4 |
TOTAL | 20 |
Semester 3
Course | L | T | P | Credit |
---|---|---|---|---|
Elements of AIML | 2 | 0 | 0 | 2 |
Elements of AIML Lab | 0 | 0 | 2 | 1 |
Databases | 3 | 0 | 0 | 3 |
Databases Lab | 0 | 0 | 2 | 1 |
Design and Analysis of Algorithms | 3 | 0 | 0 | 3 |
Python Programming | 2 | 0 | 0 | 2 |
Python Programming Lab | 0 | 0 | 4 | 2 |
Exploratory-1 | 3 | 0 | 0 | 3 |
Design Thinking | 2 | 0 | 0 | 2 |
Discrete Mathematics & Linear Algebra | 3 | 0 | 0 | 3 |
TOTAL | 22 |
Semester 4
Course | L | T | P | Credit |
---|---|---|---|---|
Computer Organization and Architecture | 3 | 0 | 0 | 3 |
Java Programming Lab | 0 | 0 | 4 | 2 |
Operating Systems | 3 | 0 | 0 | 3 |
Exploratory-2 | 3 | 0 | 0 | 3 |
Probability, Computing and Statistics | 3 | 0 | 0 | 3 |
PE-1 | 4 | 0 | 0 | 4 |
PE-1 Lab | 0 | 0 | 2 | 1 |
TOTAL | 19 |
Semester 5
Course | L | T | P | Credit |
---|---|---|---|---|
Cyber Security | 2 | 0 | 0 | 2 |
Theory of Computing | 3 | 0 | 0 | 3 |
Exploratory-3 | 3 | 0 | 0 | 3 |
Start your startup | 0 | 0 | 4 | 2 |
PE-2 | 4 | 0 | 0 | 4 |
PE-2 Lab | 0 | 0 | 2 | 1 |
Project-1 | 4 | 0 | 0 | 4 |
TOTAL | 19 |
Semester 6
Course | L | T | P | Credit |
---|---|---|---|---|
Exploratory-4 | 3 | 0 | 0 | 3 |
Leadership and Teamwork | 2 | 0 | 0 | 2 |
PE-3 | 4 | 0 | 0 | 4 |
PE-4 | 4 | 0 | 0 | 4 |
Project-2 | 0 | 0 | 0 | 7 |
Summer Internship | 0 | 0 | 0 | 1 |
TOTAL | 21 |
Semester 7
Course | L | T | P | Credit |
---|---|---|---|---|
Compiler Design | 3 | 0 | 0 | 3 |
Research Methods | 3 | 0 | 0 | 3 |
Exploratory-5 | 3 | 0 | 0 | 3 |
PE-5 | 3 | 0 | 0 | 3 |
Project- 3 | 0 | 0 | 0 | 8 |
Research Seminar-1 | 0 | 0 | 0 | 1 |
TOTAL | 21 |
Semester 8
Course | L | T | P | Credit |
---|---|---|---|---|
Devops | 2 | 0 | 0 | 2 |
IT Ethical Practice | 3 | 0 | 0 | 3 |
Project-4 | 0 | 0 | 0 | 12 |
Research Seminar-2 | 0 | 0 | 0 | 2 |
TOTAL | 19 |
Major Elective 24 Credits
Course | L | T | P | Credit |
---|---|---|---|---|
Fundamentals of Data Science | 4 | 0 | 0 | 4 |
Fundamentals of Data Science Lab | 0 | 0 | 2 | 1 |
Data Visualization and Interpretation | 4 | 0 | 0 | 4 |
Data Visualization and Interpretation Lab | 0 | 0 | 2 | 1 |
Machine and Deep Learning | 4 | 0 | 0 | 4 |
Computational Linguistics a nd NLP | 4 | 0 | 0 | 4 |
Generative AI | 3 | 0 | 0 | 3 |
TOTAL | 24 |
Eligibility
Interested students must meet the following minimum eligibility criteria for B.Sc. Computer Science (Data Science) :50% marks in class X and XII withMathematics / Computer Science / Information Technology as one of the major Subject in Class XII.
Selection Criteria
The selection criteria for individuals who wish to enroll in the B.Sc. Computer Science (Data Science) program at UPES relies on the performance in Personal Interview.
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