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    Scholarships & exams

    support@collegese.com
    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Bachelor Of Science

    Sri Gowri Degree And Pg College Visakhapatnam
    Duration
    4 Years
    Bachelor Of Science UG OFFLINE

    Duration

    4 Years

    Bachelor Of Science

    Sri Gowri Degree And Pg College Visakhapatnam
    Duration
    Apply

    Fees

    ₹1,20,000

    Placement

    92.0%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Bachelor Of Science
    UG
    OFFLINE

    Fees

    ₹1,20,000

    Placement

    92.0%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹12,00,000

    Seats

    120

    Students

    1,200

    ApplyCollege

    Seats

    120

    Students

    1,200

    Curriculum

    Comprehensive Course Listing

    The Bachelor of Science program at Sri Gowri Degree And Pg College Visakhapatnam is structured over 8 semesters, with a carefully curated mix of core subjects, science electives, departmental electives, and laboratory courses. The following table outlines the course structure for each semester, including course codes, titles, credit structure (L-T-P-C), and prerequisites.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1SC101Introduction to Physics3-1-0-4-
    1SC102Chemistry Fundamentals3-1-0-4-
    1SC103Biology Basics3-1-0-4-
    1SC104Calculus and Differential Equations3-1-0-4-
    1SC105Physics Lab0-0-3-1-
    1SC106Chemistry Lab0-0-3-1-
    2SC201Organic Chemistry3-1-0-4SC102
    2SC202Quantum Physics3-1-0-4SC101
    2SC203Cell Biology3-1-0-4SC103
    2SC204Linear Algebra3-1-0-4SC104
    2SC205Organic Chemistry Lab0-0-3-1SC102
    2SC206Physics Lab II0-0-3-1SC101
    3SC301Biostatistics3-1-0-4SC204
    3SC302Genetic Engineering3-1-0-4SC203
    3SC303Environmental Chemistry3-1-0-4SC201
    3SC304Thermodynamics3-1-0-4SC101
    3SC305Research Methodology3-0-0-3-
    3SC306Biostatistics Lab0-0-3-1SC301
    4SC401Advanced Molecular Biology3-1-0-4SC302
    4SC402Computational Modeling3-1-0-4SC204
    4SC403Ecological Systems3-1-0-4SC203
    4SC404Electromagnetic Theory3-1-0-4SC101
    4SC405Mini Project0-0-6-2-
    4SC406Advanced Chemistry Lab0-0-3-1SC303
    5SC501Biotechnology Applications3-1-0-4SC302
    5SC502Data Analysis Techniques3-1-0-4SC301
    5SC503Climate Change and Sustainability3-1-0-4SC303
    5SC504Quantum Computing3-1-0-4SC202
    5SC505Internship0-0-0-3-
    6SC601Advanced Mathematical Modeling3-1-0-4SC402
    6SC602Genomics and Proteomics3-1-0-4SC401
    6SC603Environmental Impact Assessment3-1-0-4SC503
    6SC604Scientific Writing and Communication3-1-0-4-
    6SC605Final Year Project0-0-12-4-
    7SC701Research Ethics and Governance3-1-0-4-
    7SC702Scientific Data Visualization3-1-0-4SC502
    7SC703Advanced Environmental Science3-1-0-4SC503
    7SC704Quantum Field Theory3-1-0-4SC404
    7SC705Project Presentation0-0-3-2-
    8SC801Capstone Research0-0-12-4-
    8SC802Industry Internship0-0-0-3-

    Advanced Departmental Elective Courses

    The department offers a range of advanced departmental elective courses that allow students to specialize in their areas of interest. These courses are designed to provide in-depth knowledge and practical skills in specific scientific disciplines.

    One such course is 'Advanced Molecular Biology', which explores the molecular mechanisms of gene regulation, protein synthesis, and cellular signaling pathways. Students engage in hands-on experiments using modern techniques such as PCR, gel electrophoresis, and CRISPR gene editing. The course is led by Dr. Priya Sharma, a leading expert in molecular biology with over 15 years of research experience.

    'Computational Modeling' is another advanced elective that focuses on the application of mathematical and computational tools to solve complex scientific problems. Students learn to develop algorithms, perform simulations, and analyze data using software such as MATLAB, Python, and R. The course is taught by Dr. Arjun Mehta, who has extensive experience in computational biology and data science.

    'Biotechnology Applications' introduces students to the latest advancements in biotechnology, including drug development, agricultural biotechnology, and environmental biotechnology. The course includes laboratory sessions where students work on real-world projects, such as developing biodegradable plastics or designing new vaccines.

    'Data Analysis Techniques' provides students with advanced skills in statistical analysis and data interpretation. The course covers topics such as regression analysis, hypothesis testing, and machine learning. It is taught by Dr. Sunita Patel, a renowned expert in biostatistics with a strong background in pharmaceutical research.

    'Environmental Impact Assessment' is a course that teaches students how to evaluate the environmental consequences of development projects. The course combines theoretical knowledge with practical fieldwork, where students conduct environmental surveys and prepare impact assessment reports. The course is led by Dr. Ramesh Iyer, an expert in environmental science with extensive experience in policy-making.

    'Quantum Computing' is an emerging field that explores the principles of quantum mechanics and their application in computing. Students learn about quantum algorithms, quantum circuits, and quantum error correction. The course is taught by Dr. Prakash Kumar, a leading researcher in quantum physics with publications in top-tier journals.

    'Genomics and Proteomics' focuses on the study of genomes and proteins, with an emphasis on how these elements contribute to biological processes. Students learn to analyze genomic data, perform protein structure prediction, and understand the role of genetics in disease.

    'Scientific Writing and Communication' is designed to enhance students' ability to communicate complex scientific concepts effectively. The course covers scientific writing, presentation skills, and grant writing, preparing students for careers in research and academia.

    'Advanced Mathematical Modeling' delves into the mathematical foundations of modeling complex systems. Students learn to apply differential equations, optimization techniques, and numerical methods to model real-world phenomena in physics, biology, and engineering.

    'Scientific Data Visualization' teaches students how to present complex data in a clear and compelling manner. The course covers tools such as Tableau, Python libraries, and data visualization best practices, enabling students to create impactful visual representations of their research findings.

    'Capstone Research' is the culminating experience of the program, where students conduct independent research under the supervision of a faculty mentor. The course provides students with the opportunity to explore a topic of personal interest, conduct experiments, and present their findings in a formal research paper or presentation.

    Project-Based Learning Philosophy

    The department's philosophy on project-based learning is rooted in the belief that students learn best when they are actively engaged in solving real-world problems. This approach encourages students to apply theoretical knowledge to practical situations, fostering critical thinking, creativity, and collaboration.

    Mini-projects are introduced in the third year, where students work in teams to solve a specific scientific challenge. These projects are designed to be manageable yet challenging, allowing students to develop their research and problem-solving skills. Projects are selected based on student interests and faculty expertise, ensuring that students receive adequate mentorship.

    The final-year thesis or capstone project is a significant component of the program. Students are required to conduct original research, design experiments, analyze data, and present their findings. The project is supervised by a faculty mentor and must meet academic standards for research integrity and scientific rigor.

    The evaluation criteria for projects include the clarity of the research question, methodology, data analysis, presentation, and overall contribution to the field. Students are encouraged to present their work at national and international conferences, further enhancing their academic and professional development.

    The department also emphasizes the importance of interdisciplinary collaboration, encouraging students to work across different scientific disciplines to address complex challenges. This approach prepares students for careers in multidisciplinary environments and fosters innovation and creativity.