B.Tech in Artificial Intelligence and Data Science Subjects

B.Tech in Artificial Intelligence and Data Science Subjects

Subjects of B.Tech in Artificial Intelligence and Data Science 

The curriculum adopted by B.Tech in Artificial Intelligence colleges are generally recognized by AICTE and UGC or through an affiliating University. KCC Institute of Technology and Management is affiliated to AKTU and approved by AICTE offers a curriculum that is at part with global standards and includes topics and subjects that are highly relevant to give students a competitive edge.  

The goal of the artificial intelligence and data science course curriculum is to teach students how to use networks, algorithms, Data analysis and programming techniques to build algorithms that can solve problems like a human. This is accomplished through studying topics related to artificial intelligence and data science such as software engineering, Data structure and algorithms, programming languages, database management, data mining, data warehouse, scripting language, machine learning, big data analytics, etc.

A unique selection of artificial intelligence and data science courses are offered by best colleges for B.Tech in Artificial Intelligence and Data Science. Popular degrees in artificial intelligence and data science in India include B. Tech Artificial Intelligence & Data Science and M. Tech Artificial Intelligence and data science.

Big data analytics, fuzzy technologies, and artificial neural networks are among the other topics that are addressed in this course. It helps students acquire the abilities needed to form conclusions based on data analysis.

Through AI and DS courses offered by KCC Institute of Technology and Management KCC ITM, students will gain skills in areas such as statistics, data science, machine learning, computer science, and logic.

Artificial intelligence is a component of data science. The field of data science uses artificial intelligence in its daily operations. The foundation of data science and artificial intelligence is based on machine learning.

B. Tech Artificial Intelligence and Data Science curriculum comprises 8 semesters of 6 month time period each. Through the study of topics like Data Structures & Algorithms, Software Engineering, Computer Networks, etc., the program focuses on important Artificial Intelligence and Data Science concepts. The advanced AI ideas covered in the B. Tech Artificial Intelligence and data science curriculum are explored through the study of topics like Database Systems, Cloud Computing, Big Data Analytics, Reinforcement Learning, etc.

B.Tech in Artificial Intelligence and Data Science Highlights

Course Level

Undergraduate

Duration

4 years

Eligibility

Candidates must have passed the 12th standard in the science stream or its equivalent from a recognized board

Average Fee

50,000- 1,50000 yearly

Average Salary

4 lakh to 6 lakh annually

Admission Criteria

Based on merit and entrance exam

 

Eligibility for admission in colleges for B.Tech in Artificial Intelligence and Data Science

  • Candidates must have successfully completed the 10+2 exam or an equivalent exam from an accredited university.
  • Candidates must have a minimum cumulative score of 55%.

 

Why Choose a B.Tech in Artificial Intelligence and Data Science?

Graduates with a degree from colleges offering B.Tech in Artificial Intelligence and Data science can find jobs with lucrative salaries in the fields soon after graduating.

  • The number of students taking this course is on the rise. Data science and artificial intelligence has emerged as one of the fastest-growing sectors in recent years.
  • With so many great options for jobs available today, it is one of the most challenging specializations to learn in the B.Tech CSE program.
  • Students may choose this course because it will help them become data scientists and analysts by preparing them for the workplace.

 

Syllabus for B.Tech in Artificial Intelligence and Data Science

The syllabus for B. Tech in 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

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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

 

Some important subjects in Artificial Intelligence and Data Science

  • Augmented Reality & Virtual Reality
  • Cognitive Computing
  • Machine Learning Techniques
  • Deep Learning
  • Robotic Process Automation
  • Robotics
  • Internet of Things
  • Introduction to Data Science
  • Data Visualization
  • Natural Language Processing
  • Geometric Modelling
  • Programming for Problem-Solving
  • Python Programming
  • Object Oriented Programming
  • Web Technology
  • Computer Communication Networks
  • Cryptography and Network Security
  • Data Structures and Algorithms
  • Database Management Systems
  • Distributed Computing
  • Business Analyst
  • Data Analyst
  • Intelligence Analyst
  • Data Manager
  • Information Security Analyst
  • Risk Analyst

 

Important skills you need

  • Good programming skills
  • Problem-solving skills
  • Knowledge of basic web development
  • Critical thinking and analytical skills
  • Basics of security, vulnerabilities and cryptography
  • Basics of machine learning
  • Strong data structure and algorithm skills

 

Top Colleges and Universities for B.Tech in Artificial Intelligence and Data Science

  • IIT Bhilai         
  • IIT Jodhpur     
  • IIT Hyderabad
  • IIIT Design and Manufacturing Kurnool, Andhra Pradesh     
  • IIIT Dharwad  
  • IIIT Lucknow   
  • IIIT Naya Raipur
  • GGSIPU
  • JMI
  • DTU

 

Is Coding Mandatory in B.Tech in AI and DS?

Data science does really require code. That’s the reason why most B.Tech Colleges have prioritized coding and programming languages in their curriculum. Large datasets can be extracted, analyzed, and worked with using programming languages like Python, SQL, and R by data scientists. Programming is also used to apply Machine Learning models for data visualization and forecasting. Data Scientists must have a fundamental understanding of programming or coding because it is a core ability in computer science.

Top Books for B.Tech in AI and DS

Book Name

Author

Python Data Science Handbook

Jake VanderPlas

Practical Statistics for Data Scientists

Peter Bruce, Andrew Bruce & Peter Gedeck

Introducing Data Science

Davy Cielen, Anro DB Meysman, Mohamed Ali

The Art of Statistics Learning from Data

David Spiegelhalter

Data Science from Scratch

Joel Grus

R for Data Science

Hadley Wickham & Garrett Grolemund

Think Stats

Allen B Downey

Introduction to Machine Learning with Python

Andreas C Muller & Sarah Guido

Data Science Job: How to Become a Data Scientist

Przemek Chojecki

Hands-on Machine Learning with Scikit-Learn and TensorFlow

Aurelien Geron

 

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