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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 CMRIT, 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 syllabus 2021

I & II Semester

  • Advanced Calculus and Numerical Methods 
  • Calculus and Differential Equations
  • Engineering Chemistry 
  • Engineering Physics 
  • Problem-Solving through Programming 
  • Basic Electronics & Communication Engineering
  • Basic Electrical Engineering 
  • Elements of Civil Engineering and Mechanics 
  • Engineering Visualization 
  • Elements of Mechanical Engineering
  • Engineering Chemistry Laboratory 
  • Engineering Physics Laboratory 
  • Basic Electrical Engineering Laboratory 
  • Communicative English 
  • Computer Programming Laboratory 
  • Professional Writing Skills in English 
  • Scientific Foundations of Health / Innovation and Design Thinking

III Semester

  • Transform Calculus, Fourier Series and Numerical Techniques 
  • Data Structures and its Applications
  • Analog and Digital Electronics
  • Computer Organization and Architecture
  • Object Oriented Programming with JAVA Laboratory
  • Samskrutika Kannada
  • Balake Kannada
  • Constitution of India and Professional Ethics
  • Ability Enhancement Course-III
  • Social Connect and Responsibility

IV Semester

  • Mathematical Foundations for Computing
  • Design and Analysis of Algorithms
  • Microcontroller and Embedded System
  • Operating System
  • Biology For Engineers
  • Python Programming Laboratory
  • Samskrutika Kannada
  • Balake Kannada
  • Constitution of India and Professional Ethics
  • Ability Enhancement Course-IV
  • Universal Human Values
  • Inter/Intra Institutional Internship

V Semester

  • Automata Theory and compiler Design
  • Computer Network
  • Database Management Systems
  • Principles of Artificial Intelligence
  • Database Management Systems Lab with Mini Project
  • Research Methodology & Intellectual Property Rights
  • Environmental Studies
  • Ability Enhancement Course-V

VI Semester

  • Software Engineering and Project Management
  • Data Science and its Applications
  • Machine Learning
  • Professional Elective Course-I
  • OpenElective Course-I
  • Machine Learning Lab
  • Mini Project

VII Semester

  • Advanced AI and ML
  • Cloud Computing
  • Professional Elective Course-II
  • Professional Elective Course-III
  • Open Elective Course-II
  • Project work

VIII Semester

  • Technical Seminar
  • Research Internship/Industry Internship
  • National Service Scheme (NSS)*
  • Physical Education (PE) (Sports and Athletics)*
  • Yoga*

      * – To be completed during the intervening period of III semester to VIII semester.

Ability Enhancement Courses

Ability Enhancement Course-III

  • Mastering Office
  • C++ Programming

Ability Enhancement Course – IV

  • Web Programming
  • Unix Shell Programming
  • R Programming

Ability Enhancement Course - V

  • Angular and React JS
    C# and Dot Net
  • Framework

ELECTIVE

  • Students can choose from the following electives

PROFESSIONAL ELECTIVE-1

  • Business Intelligence
  • Advanced JAVA Programming
  • Natural Language Processing
  • Computer Graphics and Visualization

PROFESSIONAL ELECTIVE -2

  • Social Network Analysis
  • Digital Image Processing
  • Fullstack Development
  • Blockchain Technology
  • Internet of Things

PROFESSIONAL ELECTIVE -3

  • Augmented Reality
  • Multiagent Systems
  • Predictive Analytics
  • Robotic Process Automation Design and Development
  • NoSql Data Base

OPEN ELECTIVE - I

  • Introduction to Data Structures
  • Introduction to Database Management Systems
  • Programming in JAVA
  • Introduction to Cyber Security

OPEN ELECTIVE – II

  • Programming in Python
  • Introduction to AI and ML
  • Introduction to Big Data
  • Introduction to Data Science

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