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Eligibility

Passed with min % in PCM for GEN & % for SC/ST/OBC

Duration

4 Year

About B. Tech CSE (AI & DS)

The Artificial Intelligence and Data Science has shown high growth in the last few years so at the apollo University for the B. Tech CSE (AI & DS) students, mainly focuses on various courses that deals with core technologies like, Machine Learning, Artificial Intelligence, Data warehouse, Data Mining, Scripting Language, Product Development, Mathematical modelling. The Students can acquire skills to perform decisions based on data analysis and gains depth subject knowledge on statistics, data science, computer science and logic as data science is connected with artificial intelligence through machine learning. The students have an opportunity to make them ready to fit for the industry and can start their career as data scientists, data analysts.

Why Choose B. Tech CSE (AI & DS)?

A B.Tech in Computer Science Engineering (CSE) in Artificial Intelligence and Data Science (AI & DS) can be a good choice for students who are interested in these fields, as it can lead to a variety of career paths and opportunities:  

  • Career prospects

    AI and data science are areas with great future prospects and can lead to high-paying jobs.  

  • Industry-ready

    Students learn through industry expert lectures, faculty mentorship, and industry internships, which can help them be ready for the industry.  

  • Analytical and critical thinking skills

    Students develop these skills, which can help them navigate industries like healthcare and finance.  

  • Data science is essential for businesses

    Data science helps businesses understand trends and patterns from large datasets, and forecast business outcomes.  

  • Core technologies

    Students learn about core technologies like machine learning, artificial intelligence, data warehouse, data mining, scripting language, product development, and mathematical modeling.  

    Eligibility Criteria

    Aspirants seeking admission to 4 years full-time B.Tech program should meet the following criteria as specified by the institute.

    Academic Requirement:

  • A candidate should have passed 10+2 or equivalent examination with Mathematics & Physics as compulsory subjects with either Chemistry /Biotechnology/Computer Science/Biology and recognized by any State Board / Central Board or any other accepted by SASTRA as equivalent to 10+2 or its equivalent examination, with a minimum aggregate of 60% marks in Mathematics, Physics and Chemistry /Biotechnology/Computer Science/Biology obtained in a single sitting.

    Scope of B.Tech in Artificial Intelligence and Data Science 

    In India, there are countless opportunities for higher education and jobs for students with a degree from B.Tech in artificial intelligence colleges in both the public and private sectors. The scope and earning opportunities offered by the best colleges for B.Tech in artificial intelligence and data science in India is quite lucrative due to the academic relevance and rising demands of graduates passing out from these institutions.

    B. Tech Artificial Intelligence and Data Science job opportunities include a wide range of offerings in various sectors of engineering and technologythat lead to high earnings for graduates. B. Tech Artificial Intelligence and Data Science syllabus includes fundamental technologies such as machine learning, artificial intelligence, data warehouses, and data mining in which higher salaries are guaranteed due to a higher demand for experts in these fields. B. Tech Artificial Intelligence and Data Science Scope in India makes it easy for fresh graduates to earn a typical pay starting from INR 5 LPA to 15 LPA. However, an experienced applicant may anticipate a salary as high as 40 LPA for a B.Tech in Artificial Intelligence and Data Science in India at prestigious organizations like Amazon, Tata Consultancy Services, IBM, Wipro, Infosys, etc.

A B.Tech in Computer Science Engineering with a specialization in Artificial Intelligence (AI) and Data Science (DS) opens up a wide range of career opportunities. Here are some potential career paths and roles:

1. Data Scientist

  • Role: Analyze complex data sets to derive actionable insights, create predictive models, and assist in strategic decision-making.
  • Skills Required: Statistical analysis, machine learning, data visualization, programming in Python or R.

2. Machine Learning Engineer

  • Role: Design and implement machine learning algorithms and models, optimize and deploy machine learning systems.
  • Skills Required: Strong understanding of algorithms, data preprocessing, experience with frameworks like TensorFlow, PyTorch.

3. Artificial Intelligence Engineer

  • Role: Develop AI systems and applications, including natural language processing, computer vision, and robotics.
  • Skills Required: Knowledge of AI techniques, programming skills, experience with AI tools and frameworks.

4. Data Analyst

  • Role: Collect, process, and perform statistical analyses on data to help organizations make data-driven decisions.
  • Skills Required: Data wrangling, statistical analysis, proficiency in SQL, data visualization tools like Tableau or Power BI.

5. Big Data Engineer

  • Role: Develop and manage large-scale data processing systems, work with big data technologies such as Hadoop and Spark.
  • Skills Required: Big data technologies, database management, data warehousing, distributed computing.

6. Business Intelligence (BI) Developer

  • Role: Design and develop BI solutions to help businesses understand their performance and make informed decisions.
  • Skills Required: BI tools (e.g., Tableau, Power BI), SQL, data warehousing, reporting.

7. Software Developer/Engineer (AI & DS)

  • Role: Develop software applications that leverage AI and data science techniques, including AI-driven features and functionalities.
  • Skills Required: Programming skills, knowledge of software development life cycle, experience with AI libraries.

8. Robotics Engineer

  • Role: Design, build, and maintain robots and robotic systems that can perform tasks traditionally done by humans.
  • Skills Required: Robotics, machine learning, control systems, programming.

9. Computer Vision Engineer

  • Role: Develop systems and algorithms to enable computers to interpret and understand visual information from the world.
  • Skills Required: Image processing, machine learning, computer vision libraries.

10. Natural Language Processing (NLP) Engineer

  • Role: Create and implement NLP algorithms to enable computers to understand and generate human language.
  • Skills Required: Text mining, machine learning, NLP libraries, language models.

11. Cybersecurity Analyst (AI Focus)

  • Role: Protect systems and data from cyber threats using AI techniques for threat detection and response.
  • Skills Required: Cybersecurity fundamentals, AI for security, network security, threat analysis.

12. Quantitative Analyst

  • Role: Use data analysis and mathematical models to inform financial decisions and risk management.
  • Skills Required: Quantitative modeling, statistical analysis, programming, finance knowledge.

13. AI Research Scientist

  • Role: Conduct cutting-edge research in AI, develop new algorithms, and publish findings in academic and industry forums.
  • Skills Required: Deep learning, research methodology, publications, advanced mathematical skills.

14. Product Manager (AI & DS)

  • Role: Oversee the development and deployment of AI and data science products, manage project lifecycle, and collaborate with engineering teams.
  • Skills Required: Product management, project management, understanding of AI/DS technologies, communication skills.

15. Consultant (AI & DS)

  • Role: Provide expert advice to businesses on how to implement AI and data science solutions to solve specific problems or improve processes.
  • Skills Required: Consulting experience, domain knowledge, AI/DS expertise, client management.

These roles span various industries, including technology, finance, healthcare, retail, and more. The skills acquired during a B.Tech in CSE with AI & DS can lead to careers in both technical and strategic positions.

Syllabus for B.Tech in Artificial Intelligence and Data Science

The syllabus for B. Tech artificial intelligence and data science is listed in the table below. The same curriculum is followed by many public and private colleges. There may be variations in the electives available.

Semester I

Semester II

Multivariable Calculus and Linear Algebra

Probability and Statistics

Physics for Computer Science

Engineering Chemistry

Introduction to Data Science

Introduction to Python Programming

Programming for Problem-Solving

Basics of Electrical and Electronics Engineering

Practical /Term Work / Practice Sessions/ MOOCs – Entrepreneurship, IoT and Applications, Computer-Aided Engineering Drawing

Basics of Civil and Mechanical Engineering

--

Practical /Term Work / Practice Sessions/ MOOCs – Biology for Engineers, Design Thinking

Semester III

Semester IV

Analog and Digital Electronics

Design and Analysis of Algorithms

Programming in Java

Unix Operating System

Data Structures

Database Management System

Discrete Mathematics and Graph Theory

Computer Organization and Architecture

Agile Software Development and DevOps

Numerical Techniques and Optimization Methods

Practical /Term Work / Practice Sessions/ MOOCs – Communication Skills, Indian Constitution and Professional Ethics, Universal Human Values

Practical /Term Work / Practice Sessions/ MOOCs – Management Science, Environmental Science, Basics of Kannada / Advanced Kannada

Semester V

Semester VI

Artificial Intelligence and Applications

Theory of Computation

Neural Networks and Deep Learning

Big Data Analytics

Machine Learning

IoT and Cloud

Professional Elective-I – Web and Text Mining, Pattern Recognition, Security in IoT, Advanced IoT Programming, Object Oriented Concepts with C++/Java, UI/UX Design, and Data Visualization

Professional Elective I – Cognitive Computing, Business Intelligence, Industrial and Medical IoT, Industrial and Medical IoT, Advanced Computer Architecture, Parallel Computing, and High-Performance Computing

Open Elective – I Database Management Systems

Open Elective II – Data Structures

Practical /Term Work / Practice Sessions/ MOOCs – Predictive Analytics and Data Visualization Tools, Indian Tradition and Culture

Practical /Term Work / Practice Sessions/ MOOCs – Research-Based Mini Project, Mobile Application Development, Technical Documentation

Semester VII

Semester VIII

Professional Elective V

Capstone Project Phase 2

Open Elective III

Internship/Global Certification

Capstone Project Phase 1

MOOC / Competitive Exam

Internship/Global Certification

Open Elective IV

Admission Process for B.Tech CSE in AI & DS-2025

  1. Visit Our Website
    Go to admissionduniya.com to explore information about B.Tech CSE in AI & DS programs.

  2. Initial Consultation
    Contact us through our website for a personalized consultation regarding your interest in the B.Tech CSE in AI & DS program and any queries you may have.

  3. Program Selection
    We’ll assist you in choosing the right universities or colleges that offer B.Tech CSE in AI & DS, based on your academic background and career goals.

  4. Eligibility Assessment
    We assess your eligibility according to your previous academic qualifications and any required entrance exam scores.

  5. Documentation Preparation
    Our team will help you prepare all necessary documents, including transcripts, a statement of purpose, and letters of recommendation.

  6. Application Submission
    We guide you through the application process, ensuring all forms are completed accurately and submitted on time.

  7. Entrance Exam Preparation
    If applicable, we provide resources and support to help you prepare for any required entrance exams.

  8. Interview Preparation
    For colleges that conduct interviews, we offer coaching to help you present yourself confidently.

  9. Admission Confirmation
    Once you receive your acceptance letter, we assist with the enrollment process, including fee payment and registration.

  10. Pre-Departure Guidance
    If necessary, we provide advice on visa applications, accommodation arrangements, and other essential preparations.

  11. Ongoing Support
    Admission Duniya offers continuous support throughout your B.Tech CSE in AI & DS journey, ensuring you have access to resources and assistance whenever needed.

For more details and to start your application process, visit admissionduniya.com today!

FAQ

Answer: This is an undergraduate program that combines core computer science principles with specialized courses in artificial intelligence and data science, focusing on building skills in areas like machine learning, data analysis, and AI technologies.

Answer: Candidates typically need to have completed their 10+2 education with Physics, Chemistry, and Mathematics. Admission often requires entrance exam scores like JEE Main or state-level engineering entrance exams.

Answer: The curriculum includes core subjects like Programming, Data Structures, Algorithms, Database Management, and specialized courses such as Machine Learning, Data Mining, Artificial Intelligence, Deep Learning, and Big Data Analytics.

Answer: Graduates can pursue careers as Data Scientists, Machine Learning Engineers, AI Engineers, Data Analysts, Big Data Engineers, Business Intelligence Developers, and more, across various industries including technology, finance, healthcare, and manufacturing.

Answer: The program typically spans four years, divided into eight semesters.

Answer: Common entrance exams include JEE Main, state-level engineering entrance exams, and specific university entrance tests.

Answer: Some top institutes include IITs, NITs, BITS Pilani, Delhi Technological University (DTU), and private universities like VIT Vellore and Manipal Institute of Technology.

Answer: Yes, there is a growing demand for professionals skilled in AI and data science due to the increasing reliance on data-driven decision-making and advancements in technology across various sectors.

Answer: Essential skills include programming (Python, R), statistical analysis, machine learning, data visualization, knowledge of AI frameworks (TensorFlow, PyTorch), and strong problem-solving abilities.

Answer: Job roles include Data Scientist, Machine Learning Engineer, AI Engineer, Data Analyst, Big Data Engineer, Business Intelligence Developer, and Research Scientist.

Answer: Yes, graduates can pursue higher studies such as M.Tech, MS, or PhD in AI, Data Science, or related fields.

Answer: Internships are typically encouraged and can provide practical experience in AI and data science, offering opportunities to work on real-world projects and gain industry exposure.

Answer: Yes, the skills acquired are globally recognized, and graduates can find opportunities for international work or further studies in countries with advanced technology sectors.

Answer: The curriculum integrates AI & DS with core subjects by incorporating specialized modules and projects that apply AI and data science techniques to solve real-world problems, complementing foundational computer science knowledge.

Answer: Projects may include developing machine learning models, data analysis and visualization tasks, creating AI-based applications, and working on big data processing and analytics.

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