B.Tech Computer Science & Engineering (Data Science)

About B.Tech Computer Science & Engineering (Data Science)

B.Tech in Computer Science and Engineering (Data Science) is an undergraduate program that blends the principles of computer science and engineering with a specialized focus on data science. This innovative program equips students with the knowledge and skills to collect, process, analyze, and extract valuable insights from large and complex data sets.

Students learn fundamental computer science concepts, programming, and algorithmic thinking, along with data-related disciplines such as statistics, machine learning, and data mining. They gain expertise in data visualization, database management, and data-driven decision-making. With the rapid growth of data in today’s digital world, graduates of this program are well-prepared to tackle real-world challenges across various industries. They can pursue careers as data scientists, data analysts, machine learning engineers, and more, contributing to data-driven innovation and decision-making. The program’s interdisciplinary nature enables graduates to bridge the gap between technology and data, making them highly sought-after professionals in the field of data science and analytics.



    Course Highlights

    Course LevelUndergraduate Degree
    Full-FormBachelor of Technology in Data Science
    Duration4 years
    Eligibility70% aggregate in 10+2 standard with PCM and Math as a mandatory subject with 50% score
    Admission ProcessEntrance Exam/Merit Based
    Course FeeRanges from INR 2-3 Lakhs
    Average SalaryUp to 10 Lakhs per annum
    Top Recruiting CompaniesAmazon, Microsoft, Wipro, Infosys, TCS, IBM, HCL, Quick Heal, SYNTEL and others
    Job PositionsData Scientist, Machine Learning Engineer, Data Analyst, Business Intelligence, Analyst Data Engineer, Big Data Engineer, Data Analytics Consultant, Data Science Researcher, Predictive Analytics Specialist
    Higher Study OptionsM. Tech in Data Science, M. Sc in Data Science, M.S. in Data Analytics, M. Tech in Big Data Analytics, M. Tech in Data Engineering, MBA in Data Science and Business Analytics


    B.Tech Computer Science & Engineering (Data Science): Admission Process (2024-25)

    • Eligibility: Ensure that you meet the eligibility criteria, which usually includes completing 10+2 or an equivalent examination with a strong foundation in mathematics, physics, and chemistry. Specific eligibility requirements may vary by institution.
    • Entrance Exams: Some universities and colleges may require you to appear for entrance exams like JEE Main, JEE Advanced, or state-level engineering entrance exams. These exams evaluate your knowledge and aptitude in science and mathematics.
    • Application: Fill out the application form for the B. Tech program at your chosen institution. You can usually do this online through the institution’s official website.
    • Entrance Exam Scores: If applicable, provide your entrance exam scores in the application form. Institutions often use these scores as a basis for admission.
    • Merit List: Based on your entrance exam scores and 10+2 results, the institution will generate a merit list. Admission may be granted based on your rank in this list.
    • Counseling: If the institution conducts counseling sessions, participate as required. During counseling, you’ll have the opportunity to choose your preferred specialization, including Data Science if offered.
    • Document Verification: Ensure you have all necessary documents, including your 10+2 certificates, entrance exam scorecards, identity proof, and other required paperwork for verification.
    • Payment of Fees: Once you are offered admission, you’ll need to pay the required fees to confirm your seat in the program.
    • Commencement of Classes: Attend orientation and the start of classes as per the institution’s schedule.

    B.Tech Computer Science & Engineering (Data Science): Eligibilty

    Eligibility CriteriaDetails
    Educational Qualification– Successful completion of 10+2 (or equivalent) with a strong foundation in mathematics, physics, and chemistry. Specific subject requirements may vary by institution.
    Entrance ExamSome institutions may require you to appear for engineering entrance exams such as JEE Main, JEE Advanced, or state-level exams. Entrance exam requirements can vary.
    Minimum Aggregate MarksMany institutions have a minimum aggregate marks requirement for 10+2, often in the range of 50% to 75%.
    Age Limit (if applicable)Some institutions may have an age limit for B. Tech admissions, typically not exceeding 25 years. Age criteria can vary by institution.
    Nationality and Domicile (if applicable)Eligibility for government or state quota seats may be restricted to specific nationalities and domiciles. Foreign nationals may have separate admission processes.
    Specific Subject Requirements (if any)Some institutions may specify subject prerequisites or offer additional weightage for subjects like mathematics and science.


    Top B.Tech Computer Science & Engineering (Data Science) Course/College in Uttarakhand




    B.Tech Computer Science & Engineering (Data Science): Specialization

    • Data Analysis: Learning how to clean, preprocess, and analyze data using statistical and machine learning techniques.
    • Data Visualization: Creating informative and compelling data visualizations to communicate findings effectively.
    • Machine Learning: Studying algorithms and models for tasks like predictive analytics, pattern recognition, and natural language processing.
    • Big Data Technologies: Exploring tools and technologies for managing and processing large datasets, such as Hadoop and Spark.
    • Data Mining: Identifying patterns and trends in data to extract valuable knowledge.
    • Data Warehousing: Understanding the design and management of data warehouses for storing and accessing data.
    • Business Intelligence: Applying data analysis to support business decision-making.
    • Database Management: Learning about database systems, including relational databases and NoSQL databases.
    • Predictive Analytics: Using data to make predictions and forecasts for various applications.
    • Data Ethics and Privacy: Exploring the ethical considerations and privacy issues related to data collection and analysis.
    • Project Work: Many programs include hands-on projects or a final-year project related to data science, where students can apply their skills in real-world scenarios.


    B.Tech Computer Science & Engineering (Data Science): Syllabus

                     Semester I Core Subjects Elective Subjects
    – Mathematics I – English Communication Skills I
    – Physics I – Engineering Drawing
    – Chemistry – Computer Programming Lab I
    – Basics of Electrical and Electronics Engineering – Physics Lab
    – Engineering Graphics – Chemistry Lab
    – Basics of Programming – Workshop Practice
                    Semester II – Mathematics II – English Communication Skills II
    – Physics II – Data Structures and Algorithms
    – Environmental Studies – Object-Oriented Programming
    – Engineering Mechanics – Digital Electronics
    – Basics of Civil Engineering – Data Structures Lab
    – Basic Electronics Lab – Object-Oriented Programming Lab
                    Semester III – Mathematics III – Database Management Systems
    – Data Structures and Algorithms – Microprocessors and Microcontrollers
    – Digital Electronics – Software Engineering
    – Probability and Statistics – Computer Organization
    – Database Management Systems Lab – Microprocessors Lab
                        Semester IV – Computer Networks – Operating Systems
    – Operating Systems – Web Technologies
    – Object-Oriented Software Engineering – Artificial Intelligence
    – Software Engineering – Human-Computer Interaction
    – Computer Networks Lab – Operating Systems Lab
                   Semester V – Algorithms – Elective I (Data Mining, Big Data Analytics, etc.)
    – Machine Learning – Elective II (Natural Language Processing, Deep Learning, etc.)
    – Data Mining – Project Work
    – Elective I (Data Science Tools and Platforms) – Seminar
                     Semester VI – Big Data Technologies – Elective IV (Business Intelligence, Data Ethics, etc.)
    – Data Science Tools and Platforms – Elective V (Data Warehousing, Predictive Analytics, etc.)
    – Elective III (Cloud Computing, IT, etc.) – Project Work
    – Elective IV (Data Science Applications) – Seminar
    – Project Work

    B.Tech Computer Science & Engineering (Data Science): PG Programs

    • M. Tech in Data Science: This program focuses on advanced data analytics, machine learning, and data engineering.
    • M. Sc in Data Science: A Master of Science program dedicated to data science, covering statistical analysis, data mining, and machine learning.
    • M.S. in Data Analytics: A program that emphasizes the practical application of data analytics techniques to solve real-world problems.
    • M.Tech in Big Data Analytics: Specializing in big data technologies, data processing, and analysis of large datasets.
    • M.Tech in Data Engineering: Focusing on the management, processing, and engineering of data, including data warehousing and ETL (Extract, Transform, Load) processes.
    • MBA in Data Science and Business Analytics: Combines data science with business and management aspects, preparing students for leadership roles.
    • M.Sc in Artificial Intelligence and Data Science: Integrates data science with artificial intelligence and machine learning.
    • M.Tech in Machine Learning and Data Science: Offers an in-depth understanding of machine learning algorithms and their application to data analysis.
    • Master of Data Science (MDS): A comprehensive data science program covering data analysis, statistics, and machine learning.
    • M.Sc in Data and Information Science: Focuses on data-driven decision-making, data ethics, and information management.
    • M.Tech in Predictive Analytics: Specializes in predictive modeling and analytics for forecasting and decision support.

    B.Tech Computer Science & Engineering (Data Science): Scopes & Salary

    Job Role Job Description Average Salary Range (per annum) in India
    Data Scientist Analyze data to extract valuable insights, build machine learning models, and make data-driven decisions. ₹6 lakh to ₹18 lakh or more
    Data Analyst Collect, clean, and analyze data to generate reports and insights for business decision-making. ₹4.5 lakh to ₹12 lakh or more
    Machine Learning Engineer Develop and deploy machine learning models for tasks like image recognition and natural language processing. ₹6 lakh to ₹18 lakh or more
    Business Intelligence Analyst Create reports, dashboards, and visualizations to support business decisions and strategies. ₹4.5 lakh to ₹12 lakh or more
    Big Data Engineer Design, implement, and maintain big data infrastructure and solutions, often using tools like Hadoop and Spark. ₹5 lakh to ₹15 lakh or more
    Database Administrator Manage and maintain databases, ensuring data security, efficiency, and accessibility. ₹4 lakh to ₹12 lakh or more
    Predictive Analyst Use data to create predictive models for various applications, such as forecasting and risk assessment. ₹4.5 lakh to ₹14 lakh or more
    Business Analyst Collaborate with stakeholders to identify business needs and use data analysis to provide solutions. ₹4.5 lakh to ₹12 lakh or more
    Quantitative Analyst Apply statistical and mathematical models to financial and risk analysis, often in the finance industry. ₹6 lakh to ₹18 lakh or more
    Marketing Analyst Analyze marketing data to assess campaign effectiveness and inform marketing strategies. ₹4 lakh to ₹10 lakh or more
    Research Scientist Conduct research in data science, machine learning, and artificial intelligence, often in academic or research settings. ₹6 lakh to ₹20 lakh or more
    Software Developer (Data Science Tools) Develop software tools and applications for data science and analytics purposes. ₹4.5 lakh to ₹12 lakh or more

    B.Tech Computer Science & Engineering (Data Science) Top Recruiting Companies

    1. Google
    2. Microsoft
    3. Amazon
    4. Facebook
    5. Apple
    6. IBM
    7. Tata Consultancy Services (TCS)
    8. Infosys
    9. Wipro
    10. Cognizant
    11. Accenture
    12. HCL Technologies
    13. Oracle
    14. Deloitte
    15. Capgemini
    16. Genpact
    17. Mu Sigma
    18. Fractal Analytics
    19. ZS Associates
    20. NVIDIA

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