B. Tech Artificial Intelligence and Machine Learning

The B. Tech AI & ML is the simulation of human intelligence in robots that have been trained to think and act like humans. Course prepares the students to obtain various skills, such as website and software development, programming languages, Etc.


B. Tech Artificial Intelligence and Machine Learning syllabus includes subjects such as programming language, Machine learning algorithms, System programming, Database management, cloud computing, Artificial Intelligent, Internet technology, Multimedia technology, Optimization Techniques, Data structure, wireless communication, etc,

Program outcomes:

Engineering knowledge: To apply the knowledge of Deep learning algorithms to observe large volumes of unstructured data including text, photos and videos.

Ethics: To apply various computational thinking algorithms and commit to professional ethics and responsibilities for creating modern expert systems.

Individual and Team: To function effectively as an individual, and as a member or leader in diverse teams, and multidisciplinary settings.

Modern tool usage: To Create, select and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitation.

Innovative: Drives scientific and societal advancement through technological innovation and entrepreneurship.

Inspiring and Collaborative: To become a leader and a responsible citizen whose strengths come from an ability to draw on and contribute to diverse teams, expertise, and experiences.

Broadly Educated and Versatile: Able to draw upon foundational knowledge, learn, adapt and successfully bring to bear analytical and computational approaches to changing societal and technological challenges.

Cultural and Global Awareness: Recognize the applicability of computing and evaluate its impact on individuals, organizations, and global society.

Problem Solving: Identify problems and formulate solutions for systems and organizations while reconciling conflicting objectives and finding compromises.

Technical Expertise: Apply knowledge of computing and mathematics within technical domains.

Professional Practice: Evaluate and use appropriate methods and professional standards in computing practice.

Practical knowledge: Practical knowledge, which is an important part of technical education, can be achieved by a well-equipped Computer Laboratory. The Computer Laboratory is a basic component of the Institute’s infrastructure, providing a wide range of support to the students and faculties involved in research and other academic activities. The Laboratories provides the hands-on need of today’s industry requirements and what they learn in the classrooms. Our curriculum includes a wide variety of subjects to enhance the practical knowledge of the students, which are listed below:

  • AI techniques
  • Deep Learning algorithms
  • Design and analysis of algorithm
  • Object-oriented programming Language
  • Computer networks
  • Database management system
  • Operating system
  • Machine Learning Algorithms
  • Embedded systems
  • Web technology
  • Cloud Computing
  • Big data analysis
  • Artificial intelligent Laboratory

Industries Hiring B. Tech AI & ML Degree Holders:

  • Machine Learning Engineer
  • Data Engineer
  • AI Engineer
  • Deep-Learning Engineer
  • Data Scientist IT consultant
  • AI in Healthcare
  • AI in Finance
  • AI in Transportation

Jobs vacancies for B. Tech AI & ML degree Holders:

  • AI Expert
  • AI Data Analyst
  • AI Application Engineer
  • AI Research Scientist
  • Data Scientist
  • ML Engineer 
  • ML Scientist
  • Data Annotation Expert


The AI sector’s growth has created attractive job prospects for professionals. The need for AI and ML professionals has grown in tandem with the rising number of job possibilities in this industry.

After finishing their education, graduates will be able to perform in technical/ managerial roles ranging from design, development, problem solving to production in software industries and R&D sectors.