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B.Tech Artificial Intelligence Colleges in Bangalore

BE| Computer Science and Engineering (Artificial Intelligence and Machine Learning)

Course Overview

1. What is Artificial Intelligence and Machine Learning specialization in Engineering?
Artificial Intelligence and Machine Learning is a branch of study or discipline which includes theories, standards, methods and innovations of various different domains like mathematics, cognitive science, electronics and embedded systems to make intelligent systems that mimic human behaviour. Artificial intelligence ai and machine learning focus on collecting, categorizing, strategizing, analyzing and interpreting data. It is a specialised branch that deals with the development of embedded systems like robotics and IoT based applications. It also incorporates the concepts of machine learning and deep learning model building for solving various computational and real-world business problems.

2. Who should study Artificial Intelligence and Machine Learning study?
 Artificial Intelligence and Machine Learning is an appropriate course for those who like to develop various innovative and intelligence solutions to solve complex industrial and business problems. This can contribute in industrial automation, information technology and other sectors like healthcare, agriculture, wearable, space, and meteorology through analysis of raw data, extract intelligence from that and design, develop, support and testing of AI and ML based systems along with embedded applications.

3. What will I study in this course?
At CMR IT, one of the best b tech artificial intelligence colleges in Bangalore, you will learn how to design, create and implement AI and ML-based software solutions to solve real-world problems. This course helps to explore concepts such as AI, Machine Learning, Deep Learning, Image Processing, Virtual Reality and IoT and its applications.

4. What are the career opportunities after the completion of this course?/What will I do once I graduate?
Artificial intelligence ai and machine learning graduates will be able to design, create and implement intelligent software applications to solve real-world business and industrial problems. They use the latest tools and open source technologies to recommend apt solutions. They can figure out how to evaluate the ethical, legitimate, proficient and social standards of engineering knowledge and practices. AI and ML graduates can also showcase their expertise in knowledge management, mobile and distributed application development, intelligence web/e-commerce development, database administration, computer hardware, networking, education and training and decision support systems using machine learning concepts with the help of the latest tools and technologies.

Programme Duration

Programme Duration
4 years (8 semesters)

Programme Type
Full-time

Eligibility Criteria

The candidate should have passed the 2nd PUC/12th/Equivalent Exam with English as one of the languages and obtained a minimum of 45% of marks in aggregate in Physics and Mathematics along with Chemistry/Biotechnology/Biology/Electronics/Computers (40% for Karnataka reserved category candidates).

Candidate must also qualify in one of the following entrance exams: CET/ COMED-K/JEE/AIEEE

Course Structure

Program Structure of AIML based on scheme 2022

I & II Semester

  • Mathematics-I for CSE Stream
  • Applied Physics for CSE stream
  • Principles of Programming Using C
  • Introduction to Electronics Communication
  • Introduction to Internet of Things (IOT)
  • Introduction to Python Programming
  • Communicative English
  • Professional Writing Skills in English
  • Samskrutika Kannada/ Balake Kannada
  • Indian Constitution
  • Innovation and Design Thinking
  • Scientific Foundations of Health

III Semester

  • Mathematics for Computer Science 
  • Digital Design & Computer Organization
  • Operating Systems
  • Data Structures and Applications
  • Data Structures Lab
  • Engineering Science Course III
  • Social Connect and Responsibility 
  • Ability Enhancement Course/Skill Enhancement Course – III 
  • NSS/Physical Education/Yoga

IV Semester

  • Analysis & Design of Algorithms
  • Artificial Intelligence 
  • Database Management Systems
  • Analysis & Design of Algorithms Lab
  • Engineering Science Course IV
  • Ability Enhancement Course/Skill Enhancement Course- IV
  • Biology For Engineers 
  • Universal human values course
  • NSS/Physical Education/Yoga

V Semester

  • Software Engineering & Project Management
  • Computer Networks
  • Theory of Computation 
  • Data Visualization Lab 
  • Professional Elective Course I
  • Mini Project 
  • Research Methodology and IPR
  • Environmental Studies and E-waste Management
  • NSS/Physical Education/Yoga

VI Semester

  • Microcontrollers & Embedded Systems
  • Machine Learning -I 
  • Professional Elective Course II
  • Open Elective Course I
  • Project Phase I
  • Machine Learning Lab
  • Ability Enhancement Course/Skill Development Course V 
  • Indian Knowledge System
  • NSS/Physical Education/Yoga

VII Semester

  • Deep Learning
  • Machine Learning -II 
  • Cryptography & Network Security
  • Professional Elective Course III
  • Open Elective Course II
  • Major Project Phase-II

VIII Semester

  • Professional Elective (Online Courses) Only through NPTEL
  • Open Elective (Online Courses) Only through NPTEL
  • Internship (Industry/Research) (14 – 20 weeks)

Elective Courses

Engineering Science Course III

  • Object Oriented Programming with Java 
  • Data Analytics with R
  • Python Programming for Data Science

Ability Enhancement Course/Skill Enhancement Course – III

  • Data Analytics with Excel
  • Project Management with Git
  • Ethics and Public Policy for AI
  • PHP Programming

Engineering Science Course IV

  • Discrete Mathematical Structures 
  • Optimization Technique
  • Metric Spaces
  • Algorithmic Game Theory

Ability Enhancement Course/Skill Enhancement Course – IV

  • Scala
  • MERN
  • MangoDB
  • Technical writing using LATEX

Professional Elective Course – I

  • Computer Vision
  • Unix System Programming
  • Information Retrieval 
  • Image and Video Processing

Professional Elective Course – II

  • Human-Centred AI
  • Blockchain Technology
  • Cloud Computing and Security
  • Time Series Analysis

Ability Enhancement Course/Skill Enhancement Course – V

  • Mobile Application Development with Flutter
  • Generative AI
  • UI/UX
  • DevOps  

Professional Elective Course – III

  • Scalable Data Systems
  • Data Engineering & MLOps
  • Parallel Computing 
  • Big Data Analytics 
Top ECE Engineering Colleges in Bangalore

Evaluation Criteria

TESTS

  • The Continuous Internal Evaluation (CIE) is prescribed for maximum of 50 marks. Marks prescribed for test shall be 20 and for assignment is 10. The CIE marks for test in a theory Course shall be based on three tests and generally conducted at the end of fifth, tenth and fifteenth week of each semester. Each test shall be conducted for a maximum of 20 marks and the final marks shall be the average of three tests. However, to support slow learners, improvement tests will be carried out to help them gain the average. The remaining 20 marks shall be awarded based on the evaluation of Assignments/ Unit Tests/ written quizzes that support to cover some of the Course/programme outcomes. Final CIE marks awarded shall be the sum of test marks and assignment marks making a maximum of 50 marks. 
  • In the case of Practical, the CIE marks shall be based on the laboratory journals/records (30 marks for continuous evaluation based on conduct of experiment, viva and report writing and two practical tests (20 marks) to be conducted during the course of the semester. 
  • The IA marks in the case of Mini Project (in 5th Semester), Projects and Seminars in the final year shall be based on the evaluation at the end of 8th semester. 

ASSIGNMENTS

  • Assignments are given to students after completion of each unit of the syllabus and comprehensively cover all of the important aspects of each topic in a particular unit.
  • Completing the prescribed assignments will greatly help students prepare for the internal assessments and the final exams. All the assignments will be evaluated and based on the performance of the students marks will be awarded for each course.
  • The Student Assistant for the course will neatly script solutions to assignments, and after due checking and correction by faculty, these solutions will be scanned and made available on the faculty webpage for all students to access and download.

Information & Downloads

FAQ

CSE with AI and ML is a Computer Science and Engineering program that integrates core computing subjects with specialized training in Artificial Intelligence and Machine Learning. Students learn programming, algorithms, data structures, and system design along with AI- driven technologies and intelligent system development.

Yes. Artificial Intelligence and Machine Learning are advanced specializations offered under Computer Science Engineering. The curriculum builds on core CSE foundations and applies them to intelligent systems, data-driven applications, and automation technologies

The program includes core Computer Science subjects such as programming, data structures, algorithms, operating systems, and databases, along with Artificial Intelligence, Machine

Learning, data science concepts, and domain-specific electives focused on intelligent applications

Both programs offer strong career opportunities. CSE Core focuses on broad computer science fundamentals, while CSE with AI and ML adds specialization in intelligent systems and data- driven technologies. The better choice depends on a student’s interest in emerging AI-focused roles.

Both programs are good, but they serve different interests. CSE with AI and ML is better suited for students who want a strong foundation in core Computer Science, such as programming, software development, and system,s along with specialization in Artificial Intelligence and Machine Learning.

Artificial Intelligence and Data Science is more suitable for students who are interested in working with data, analytics, machine learning models, and data-driven decision-making. The better choice depends on whether a student prefers a core computer science approach or a data-centric AI and analytics-focused approach.

Graduates can pursue roles in software engineering, AI system development, machine learning engineering, data-driven application development, and emerging technology domains. The specialization also supports higher studies and research in advanced computing fields.

Candidates who have completed 12th or equivalent education with Physics and Mathematics and qualified through recognised entrance examinations are eligible, as per university and regulatory guidelines.

Yes. At CMRIT, the CSE with AI and ML program combines strong computer science fundamentals with industry-aligned AI and ML learning, supported by practical exposure, projects, and placement assistance to prepare students for modern IT and technology careers.

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