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Best Data Science Colleges in India

B.E. | Artificial Intelligence and Data Science

Course Overview

1.What is Artificial Intelligence and Data Science specialization in Engineering?
Artificial Intelligence and Data Science is a new branch of study that deals with scientific methodologies, processes, and techniques drawn from different domains like statistics, cognitive science, and computing and information science to extract knowledge from structured data and unstructured data. This knowledge is applied in making various intelligent decisions in business applications. Artificial Intelligence and data science engineering colleges in Bangalore focus on collecting, categorizing, strategizing, analyzing and interpreting data. It is a specialised branch that deals with the development of data-driven solutions, data visualization tools and techniques to analyse big data. It also incorporates the concepts of machine learning and deep learning model building for solving various computational and real-world problems.

2. Who should study Artificial Intelligence and Data science study?
AI and Data science is the current trend ruling the business world and it is highly paid career now. Artificial Intelligence and data science is a suitable course for those who would like to develop various intelligent business solutions. Big data solutions has changed the way how business models to be built and run. This study contributes much in manufacturing, e-commerce, banking, finance, transport and healthcare industry.

3. What will I study in this course?
In CMR IT, one of the best b tech artificial intelligence and data science colleges in Bangalore , you will learn how to design, create and implement AI and DS based software solutions to solve actual business problems. This course helps to explore concepts such as AI, Data Analytics, Data visualization, Machine Learning, Deep Learning, semantic web and social network analytics, Blockchain Technologies, and Data Security and Privacy.

4.What are the career opportunities after the completion of this course?/What will I do once I graduate?
AI and DS graduates will be able to design, and develop intelligent business applications to solve various industrial problems. They use the latest tools and open source technologies to recommend the required solutions. They can figure out how to evaluate the ethical, legitimate, proficient and social standards of engineering knowledge and practices. These graduates can also exhibit their domain knowledge in data handling, knowledge extraction, mobile and distributed application development, intelligence web/ecommerce development, database administration, computer hardware, networking, education and training and decision support systems using AI and Data Science tools and techniques.

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

The Artificial Intelligence and Data Science syllabus is as following:

I & II Semester

  • Calculus and Linear Algebra
  • Engineering Physics
  • Basic Electrical Engineering
  • Elements of Civil Engineering and Mechanics
  • Engineering Graphics
  • Engineering Physics Laboratory
  • Basic Electrical Engineering Laboratory
  • Technical English-I
  • Engineering Chemistry
  • C Programming For Problem Solving
  • Basic Electronics
  • Elements of Mechanical Engineering
  • Engineering Chemistry Laboratory
  • C Programming Laboratory
  • Advanced Calculus and Numerical Methods
  • Technical English-II

III Semester

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

IV Semester

  • Mathematical Foundations for Computing
  • Design and Analysis of Algorithms
  • Microcontroller and Embedded Systems
  • Operating Systems
  • 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 Networks
  • Database Management Systems
  • Principles of Artificial Intelligence
  • Database Management Systems Laboratory 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
  • Open Elective Course-I
  • Machine Learning Laboratory
  • Mini Project
  • Innovation/Entrepreneurship/Societal Internship

VII Semester

  • Data Visualization
  • 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.

ELECTIVES

Students can choose from the following electives:

PROFESSIONAL ELECTIVE-1

  • Business Intelligence
  • Advanced JAVA Programming
  • Natural Language Processing
  • Data Security and Privacy

OPEN ELECTIVE COURSE - I (LIST OF SUBJECTS OFFERED BY AI&DS to other department students)

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

PROFESSIONAL ELECTIVE-2

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

PROFESSIONAL ELECTIVE-3

  • Augmented Reality
  • Multiagent Systems
  • Deep Learning
  • Robotic Process Automation Design and Development
  • NoSql Data Base

OPEN ELECTIVE COURSE - II (LIST OF SUBJECTS OFFERED BY AI&DS to other department students)

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

Ability Enhancement Courses

Ability Enhancement Course - III

  • Mastering Office
  • Programming in C++

Ability Enhancement Course - IV

  • Web Programming
  • Unix Shell Programming
  • R Programming

Ability Enhancement Course - V

  • Angular JS and Node JS
  • C# and .Net Framework
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Evaluation Criteria

TESTS

  • The Continuous Internal Evaluation (CIE) is prescribed for maximum of 40 marks. Marks prescribed for test shall be 30 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 fourteenth week of each semester. Each test shall be conducted for a maximum of 30 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 10 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 40 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 one practical test (10 marks) to be conducted at the end 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.

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