The Bachelor of Science (B.Sc.) Data Science and Engineering syllabus at Sri Ramachandra Institute of Higher Education and Research (SRIHER), Chennai is designed to provide overall knowledge to the students with a strong foundation. Bachelor of Science (B.Sc.) Data Science and Engineering faculty at Sri Ramachandra Institute of Higher Education and Research (SRIHER) specially focus on in-depth learning to relevant subjects. At first semester syllabus of Bachelor of Science (B.Sc.) Data Science and Engineering at Sri Ramachandra Institute of Higher Education and Research (SRIHER), students learn the basics of programme. A strong foundation is very important for comprehensive learning. Bachelor of Science (B.Sc.) Data Science and Engineering syllabus at Sri Ramachandra Institute of Higher Education and Research (SRIHER), Chennai maintains a balance between theoretical knowledge and practical knowledge.
Bachelor of Science (B.Sc.) Data Science and Engineering first year students at Sri Ramachandra Institute of Higher Education and Research (SRIHER) are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. Sri Ramachandra Institute of Higher Education and Research (SRIHER), Chennai also provides practical training sessions, workshops, projects, and case studies to enhance student skills. Bachelor of Science (B.Sc.) Data Science and Engineering syllabus at Sri Ramachandra Institute of Higher Education and Research (SRIHER), Chennai is also frequently updated to give industry relevant training and knowledge to students. Sri Ramachandra Institute of Higher Education and Research (SRIHER) strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at Sri Ramachandra Institute of Higher Education and Research (SRIHER) enable Bachelor of Science (B.Sc.) Data Science and Engineering students to apply knowledge and skills in a controlled environment and get required experience.
According to syllabus of Bachelor of Science (B.Sc.) Data Science and Engineering progress, students learn advanced topics and complex concepts. The Bachelor of Science (B.Sc.) Data Science and Engineering curriculum at Sri Ramachandra Institute of Higher Education and Research (SRIHER), Chennai mainly focuses on analytical and critical thinking. As the Bachelor of Science (B.Sc.) Data Science and Engineering course unfolds, students develop several important skills that increases their employability. As per syllabus of Bachelor of Science (B.Sc.) Data Science and Engineering at Sri Ramachandra Institute of Higher Education and Research (SRIHER) also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.
Bachelor of Science (B.Sc.) Data Science and Engineering curriculum at Sri Ramachandra Institute of Higher Education and Research (SRIHER) includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The Bachelor of Science (B.Sc.) Data Science and Engineering syllabus at Sri Ramachandra Institute of Higher Education and Research (SRIHER) aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.
Additional curriculum at Sri Ramachandra Institute of Higher Education and Research (SRIHER)
Note: Given below syllabus is based on the available web sources. Please verify with the Sri Ramachandra Institute of Higher Education and Research (SRIHER), Chennai for latest Bachelor of Science (B.Sc.) Data Science and Engineering curriculum.
The Bachelor of Science (B.Sc.) in Data Science and Engineering program offers a comprehensive syllabus that combines the fundamental principles of computer science, mathematics, and data analysis with specialized courses in data engineering. In the initial years, students typically study core computer science topics such as programming, data structures, algorithms, and databases. They also delve into mathematics, statistics, and machine learning to develop a strong quantitative foundation. As they progress, the curriculum focuses on data engineering-specific subjects, including big data technologies, data warehousing, data integration, and cloud computing. Students gain hands-on experience through practical projects, where they work with real-world datasets and design data pipelines. Moreover, elective courses may allow students to explore areas like artificial intelligence, natural language processing, or business analytics. The program culminates in a capstone project or internship, where students apply their knowledge and skills to solve data-related challenges. Graduates are equipped with the expertise to work in various industries, including technology, finance, healthcare, and e-commerce, as data scientists, data engineers, or analysts, contributing to data-driven decision-making processes. Specific course offerings may vary among institutions, but the program typically integrates computer science and data engineering principles to prepare students for the rapidly evolving field of data science and engineering.
1st Year OR 1st & 2nd Semester Syllabus of Bachelor of Science (B.Sc.) Data Science and Engineering
S.no | Subjects |
1 | Effective
Communication |
2 | Engineering
Math's |
3 | Fundamentals
of Physics |
4 | Introduction to
Statistics |
5 | Environment
al Studies |
6 | Programming in Python |
7 | Data Visualization |
2nd Year OR 3rd & 4th Semester Syllabus of Bachelor of Science (B.Sc.) Data Science and Engineering
S.No | Subjects |
1 | Data
Analysis |
2 | Entrepreneurship |
3 | Data structure and Program Design Using C |
4 | Basics of computer science |
5 | Discrete Mathematics |
6 | Data Warehousing and Multidimensional Modelling |
3rd Year OR 5th & 6th Semester Syllabus of Bachelor of Science (B.Sc.) Data Science and Engineering
S.no | Subjects |
1 | Linear Algebra |
2 | Mathematical
Statistics |
3 | Introduction to
AI and ML |
4 | Business Intelligence and Data Visualization |
5 | Numerical Analysis |
6 | Machine
Learning |
7 | Big Data |
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