Understanding the Syllabus of a B.Tech in AI & ML Program

Home BTech Understanding the Syllabus of a B.Tech in AI & ML Program

Technology is at a pace that humans never imagined in the beginning era and one of the biggest assets of today’s technology is Artificial Intelligence. With the latest trends such as ChatGPT, edge AI, Cybersecurity AI, and much more, Artificial Intelligence has come a long way to a global market value of USD 136.55 billion in 2022.

If you are someone planning on making your career in this industry, then it is time for you to know about the course BTech in AI and ML. This article will elaborate on the BTech in AI and ML syllabus along with future career scope details.

BTech in AI and ML at Universal AI University:

Universal AI University with a huge range of technological courses offers BTech in AI and ML courses for students. Around 9% of engineering students have opted for this course in the past five years within India.

 

Here are the BTech Artificial Intelligence course details.

 

Course Description:

The BTech in AI and ML course is a 4-year undergraduate-level course that involves inculcating knowledge on data extraction strategies, algorithms, methodologies, and incorporation of acquired data in developing automated systems and robotics using artificial intelligence.

 

BTech in AI and ML syllabus and course modules are designed with a motive to create a strong foundation on various concepts of AI such as IoT, etc.

Eligibility Criteria and Admission Procedure:

The essential BTech in Artificial Intelligence eligibility criteria are as follows:

 

  • Candidates should have completed 10+2 with physics, chemistry, and mathematics as compulsory subjects and one optional science subject.

 

  • Candidates should have scored a minimum of 50% aggregate in 10+2. 

 

Admission to BTech in AI and ML at Universal AI University is provided by conducting the UBSAT entrance test. 

 

Now, let us get to the main part of the article.

Syllabus of BTech in AI and ML:

The BTech in AI and ML syllabus is curated by industrial experts having immense expertise in the field of artificial intelligence and machine learning.

 

AIML subjects in BTech are designed in such a way that students gradually learn from the fundamental level to the advanced level concepts in artificial intelligence and machine learning.

Here is the Artificial Intelligence and Machine Learning syllabus for BTech.

 

Core subjects Elective subjects
Computer System Architecture

Data and Analysis of Algorithms

Data Communications and Computer Networks

Web Technologies

Applied Statistical Analysis for AI and ML

Neural Networks

Pattern Recognition

Machine Learning

Language Processing

 Robotics

Automata

Deep Learning

Sensors

Internet of Things

C/C++

Java

Robotics

OOPS Lab

WKSP 2.0

 

Let us get into the deeper side of what each subject in BTech AI and ML teaches students for better understanding of the BTech in AI and ML syllabus.

 

Subjects Description
Computer System Architecture Computer System Architecture educates students on how systems are designed, built and operated to understand the various components and workings of the computer system. This subject is a foundational level subject.
Data Analysis and Algorithm Data Analysis and Algorithms help students understand the functioning of a product and develop efficient problem-solving skills in the field of AI and ML.
Data Communications and Computer Networks Data Communication and Computer Networks introduce students to concepts such as network concepts, system administration and maintenance, security issues and operating systems.
Web Technologies Web Technologies subjects deal with various website techniques, architecture and other aspects of website building.
Applied Statistical Analysis for AI and ML Applied Statistical Analysis for AI and ML subjects trains students in identifying and constructing trivial patterns and codes, helps in predictive validation, etc in terms of AI.
Pattern Recognition As AI and ML majorly deal with pattern construction and operation, students will be trained on how to identify a pattern and decode and understand the operational schema in AI.
Neural Networks Neural Networks are an efficient way of making computer systems work impeccably and this subject will train students in it.
Language Processing Language Processing is one of the major facets of AI and students are educated on various techniques involved in this process via this subject.
Robotics Robotics trains students in various aspects of robotics such as design, construction, operation and use of robots.
Automata Automata subject deals with the study of abstract machines along with the computational problems that can be solved using them.
Deep Learning Deep learning deals with how the computer handles the data from the context of the human brain.
Sensors Sensors educate students on the various types of sensors and their applications in the field of artificial intelligence and machine learning.
Internet of Things The Internet of Things describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks.
C/C++ C/C++ is the programming language that is considered fundamental in the field of artificial intelligence.
Java Java is an advanced-level programming language that enables students to design efficient artificial intelligence solutions for a wide range of problems.

 

On the whole, the BTech in AI and ML syllabus is designed in such a way that students gain all the fundamental knowledge that is considered crucial to establishing a career in the field of artificial intelligence.

 

Students can further strengthen their AI knowledge by pursuing higher education courses such as MTech in Artificial Intelligence, MTech in Machine Learning, MTech in Robotics, etc which will lead them to a great career in the field of computer science.

Conclusion:

Hope this article provides a complete idea of BTech in AI and ML syllabus which will help students in preparing themselves for better learning during the course. As technology is fast-forwarding establishing a great career scope, it is time for students to make use of it with a BTech in AI and ML degree.

FAQs:

  • What is the syllabus of B Tech AI and ML?

The syllabus of BTech in AI and ML includes subjects such as computer system architecture, data structures and algorithms, Internet of Things (IoT), C/C++, Java, language processing, etc.

  • What is the basic understanding of AI and ML?

The basic understanding of AI and ML includes the implementation of human knowledge in the form of codes and algorithms to develop artificial computer systems with huge value.

  • What is taught in BTech artificial intelligence?

Students are educated on various concepts such as computer system architecture, data structures and algorithms, language processing, applied statistics, web technologies, etc in BTech AI.

  • How to learn AI and ML step by step?

Step 1: Apply for BTech in AI and ML

Step 2: Complete the course to get thorough knowledge of AI and ML.