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 Overview
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.
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.
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.
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.
What is Artificial Intelligence and Data Science?
- Artificial intelligence (AI) and data science are two very different things. Artificial intelligence is the process of creating machines that can think like humans, or at least mimic human behavior in some way. Data science is the application of techniques from statistics, mathematics, computer programming and other fields to solve real-world problems using information technology. Artificial intelligence (AI) is a term used to describe the simulation of human intelligence processes in machines. It typically involves sophisticated algorithms that enable computers to perform tasks that normally require human intelligence, such as visual perception, speech recognition and decision making. However, AI can be applied in many more areas than just these three specific processes. Data science is a field of knowledge which applies advanced statistical and mathematical techniques to large datasets in order to extract knowledge from them that was previously not there. This data can be structured like a spreadsheet but can also be unstructured like text or video data.
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
Electives
Students can choose from the following electives:
Professional elective-1
- Business Intelligence
- Advanced JAVA Programming
- Natural Language Processing
- Data Security and Privacy
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 - 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
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 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