T.Y.B.Sc. - Data Science and Analytics (Honours) - Semester-V and Semester-VI Syllabus - 2026-2027

Oct 22, 2026

Veer Narmad South Gujarat University, Surat provides the Computer Science and Information Technology faculty syllabus for T.Y. B.Sc. (Data Science and Analytics) (Honours) for Semester-V and Semester-VI under NEP-2020, to be implemented from the academic year June 2026–2027. The syllabus defines program aims, program outcomes (PO1–PO6), and program specific outcomes (PSO1–PSO8) covering statistics, computing, programming, visualization, modeling, database/big data tools, and ethical data governance. It also specifies semester structure and course mapping across minor, major, and skill enhancement categories.

LanguageEnglish

CategoryExam

FormatPDF

Pages43

Reading Time1 h 48 min

AccessFree to download

Program Overview

Objective of Program

Program Outcomes (PO)

Program Specific Outcomes (PSO)

Semester-V Structure

Course List and Marks Pattern

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Veer Narmad South Gujarat University, Surat Computer Science and Information Technology Faculty Syllabus for T.Y. B.SC. (DATA SCIENCE AND ANALYTICS) (HONOURS) (Semester-V and Semester-VI) as per the NEP-2020 To be implemented from Academic Year: June, 2026-2027 | VEER NARMAD SOUTH GUJARAT UNIVERSITY, SURAT
B.Sc.(Data Science and Analytics) Semester-5 and Semester-6 | | | --- | --- | | Name of Program | Bachelor of Computer Science in Data Science and Analytics | | Program Abbreviation | B.Sc.(Data Science and Analytics) | | Duration | Four-year Integrated Program with Multi-Level Entry and Exit option | | Eligibility Criteria | As per University Criteria | | Pre-requisite | Second Year of B.Sc.(Data Science and Analytics) | | Medium of Instruction | English | | Objective of Program | The B.Sc.(Data Science and Analytics) program aims to provide strong foundations in data science, statistics, and computing. It develops analytical and problem-solving skills to address real-world data-driven challenges. The program equips students with programming and technical skills required for data analysis and model implementation. It emphasizes transforming data into meaningful insights through visualization and analytics. Practical learning is promoted through labs, projects, and case studies. Ethical and responsible use of data is strongly emphasized. The program enhances communication and teamwork skills for effective presentation of insights. Students are encouraged toward independent learning and innovation. The curriculum prepares learners for industry roles, entrepreneurship, higher studies, and research. Overall, the program builds competent data professionals ready for evolving technological landscapes. | | Program Outcome (PO) | PO1: To build strong foundations in mathematics, statistics, computing, and core data science principles for data-driven analysis.
PO2: To develop analytical, critical thinking, and problem-solving skills for interpreting and extracting insights from data.
PO3: To equip students with practical programming, data analysis, visualization, and modeling skills using modern tools and technologies.
PO4: To enable the design and implementation of data-driven solutions for realworld and interdisciplinary problems.
PO5: To promote ethical, responsible, and secure use of data, including awareness of privacy, governance, and professional ethics.
PO6: To prepare graduates for careers, higher education, research, and lifelong learning in data science, analytics, and related fields. | | Program Specific Outcomes (PSO) | PSO1: Apply statistical and computational techniques to collect, preprocess, and analyze structured and unstructured datasets.
PSO2: Design and implement data analytics solutions using programming languages, libraries, and frameworks relevant to data science.
PSO3: Develop and evaluate predictive and descriptive models using machine learning and analytical techniques.
PSO4: Create meaningful data visualizations and dashboards to communicate analytical findings effectively to technical and non-technical stakeholders. PSO5: Integrate databases, data warehouses, and big data tools for efficient data storage, retrieval, and processing.
PSO6: Apply ethical principles, data privacy laws, and governance frameworks while handling and analyzing data.
PSO7: Work effectively as an individual and as part ofa team to solve real-world data-driven problems through projects and case studies. | | | PSO8: Demonstrate self-learning ability and adaptability by exploring emerging tools, technologies, and research trends in data science and analytics. | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Mapping between POs and PSOs | | | PSO1 | PSO2 | PSO3 | PSO4 | PSO5 | PSO6 | PSO7 | PSO8 | | | | | PO1 | | | | | | | | | | | | | PO2 | | | | | | | | | | | | | PO3 | | | | | | | | | | | |

FAQs

What is the program duration and academic structure for T.Y. B.Sc. (Data Science and Analytics) (Honours)?

The program is a four-year integrated program with multi-level entry and exit options. The document specifies structure for Semester-V and Semester-VI under NEP-2020.

What skills and competencies are emphasized in the program outcomes (PO1–PO6)?

The outcomes focus on foundations in mathematics, statistics, computing, analytical problem-solving, practical programming and modeling, design of data-driven solutions, and ethical, secure data use for careers and lifelong learning.

Which outcomes are targeted by the program specific outcomes (PSO1–PSO8)?

PSOs cover data collection/preprocessing and analysis, analytics solution implementation with programming tools, development and evaluation of predictive and descriptive models, creation of dashboards for communication, integration of databases/data warehouses/big data tools, and application of ethics and privacy governance.

Oct 22, 2026

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