B.Tech - CSE (Artificial Intelligence)

Overview 

The B.Tech Artificial Intelligence subjects focus on a comprehensive understanding of the development of efficient and error-free codes, based on which a machine can perform tasks with less human interaction. The B.Tech Artificial Intelligence syllabus is divided into 8 semesters consisting of core and elective subjects, practicals/laboratory work, industrial training, projects, and seminars.

The core B.Tech Artificial Intelligence subjects include Engineering Mechanics, Data Structures and Algorithms, Artificial Intelligence, Big Data Analytics, Machine Learning, Web Technology, Deep Learning, etc. Students can also choose elective subjects such as Software Architecture, Quantum AI, Human-Computer Interface, Pattern Recognition, Cognitive Computing, etc.

The B.Tech Artificial Intelligence course helps students develop technical skills in the field of artificial intelligence, algorithms, big data analytics, machine learning, etc., and build a career as a data scientist, data engineer, software designer, data interpreter, etc.

Some Highlights of B.Tech - CSE (Artificial Intelligence)

Top Colleges offeringB.Tech - CSE (Artificial Intelligence) in India

dian Institute of Technology Hyderabad
Indraprastha Institute of Information Technology Delhi
Noida Institute of Engineering and Technology (NIET, Greater Noida)
Ramaiah Institute of Technology
Indian Institute of Technology (IIT), Jodhpur
Indian Institute Of Technology Delhi (IIT Delhi)
Manipal Institute of Technology
Indian Institute of Information Technology, 
Coimbatore Institute of Technology

Before enrolling in a B.Tech Artificial Intelligence course, students must be aware of the industry demand, market size, and future growth potential of the industry. Listed below are a few points that give us insight into why to choose the B.Tech Artificial Intelligence course:

As per a report published by PR Newswire, the whole artificial intelligence industry is expected to grow from USD 21.46 billion in 2018 to USD 190.61 billion by 2025.
According to a report in The World Economic Forum, graduates who want to work in system analyst roles are expected to witness a growth of 10% in the next few years.
As per a Bureau of Labour Statistics report, engineering career opportunities are expected to grow 7% nationwide by 2026.

Admission Process

The B.Tech Artificial Intelligence admission is conducted based on the entrance exam scores and merit. Most of the top institutions such as IIT Roorkee, NIT Surathkal, VIT Vellore, etc. accept admission via entrance exams.

Listed below is the admission procedure for the B.Tech Artificial Engineering course:

Step 1: Students must have valid scores in the required entrance examination as mandated by the desired colleges.
Step 2: Students are required to fill out and submit the application form for the respective colleges.
Step 3: Based on the merit and entrance exam scores, students will be called for counseling or further rounds of selections such as Group Discussion or Personal Interviews (if any).
Step 4: After the merit list is released, selected students must submit the documents for verification and pay the admission fee.

Eligibility

Eligibility criteria for a B.Tech in Computer Science and Engineering (CSE) with a focus on Artificial Intelligence (AI) varies by college and university. However, some common requirements include:

10+2: Candidates must have passed 10+2 with at least 60% aggregate marks.
Science stream: Candidates must have completed 10+2 in the Science stream.
Subjects: Candidates must have studied Physics, Mathematics, and English, and ideally Computer Science, as major subjects. If English was not studied as a subject, the condition may be waived if the qualifying exam was in English medium or an equivalent subject.
Entrance exams: Candidates must qualify for an entrance exam such as JEE Main, JEE Advanced, LPUNEST, or CUET

Career Opportunity 

• Data Engineer
  
• Software Tester
  
• Data Scientist
  
• Data Analyst
  
• Software Engineer
  
• Information Network Manager
  
• Systems Analyst
  
• Data Architect
  
  

Semester 1

Physics
Chemistry
Basic Electronics and Electrical Engineering
Fundamentals of Programming Languages
Communication Skills
Mathematics

Semester 2

Problem Solving by Programming
Computational Statistics
General Biology
Engineering Graphics and Design
Engineering Mechanics
Project-Based Learning – I
Workshop and Manufacturing Practices - Laboratory

Semester 3

Discrete Structure
Data Structures and Algorithms
Software Engineering and Project Management
Database Management Systems
Project Based Learning-II
Universal Human Values-II

Semester 4

Artificial Intelligence
Digital Logic Design and Processor Architecture
Computer Networks
R Programming
Foundations of Data Science

Semester 5

Big Data Analytics
Machine Learning
Web Technology
Design and Analysis of Algorithm
Elective-I
Skill Enhancement Course-I

Semester 6

Advanced Databases
Deep Learning
Machine Learning & Network Security
Information Retrieval
Elective-II
Skill Enhancement Course-II/ Internship

Semester 7

Ethics and Values
Elective-III
Skill Enhancement Course-III
Project- I/ Internship

Semester 8

Elective-IV
Skill Enhancement Course-IV
Project- II/ Internship