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Department of Artificial Intelligence & Machine Learning


Srinivas University started the BTech program in AIML to provide access to Srinivas University's quality education to learners across the country. Machine learning aims at building computer programs that automatically improve with experiences. In statistical language, it is simply learning from data that we generate in our day-to-day life. Machine learning is related to diverse disciplines as it is all about automating the process of problem-solving to a more significant extent. It is usually studied as a part of Artificial Intelligence thus relating it to computer science. As already stated it deals with data that we generate thus connecting it to the statistics and mathematics domain.

In general, problems it tries to solve may have originated in any areas like DNA analysis, medical diagnosis, product recommendations, stock trading and credit card fraud detection. Machine learning grew out of pattern recognition. However, it has progressed dramatically over the past two decades.

In AI systems, it has emerged as a popular method to develop software for various fields like computer vision, speech recognition, natural language processing etc. To all intents and purposes, AIML is a growing field and the demand for skilled resources in the market is very high. Srinivas Univerisy has a rich history of providing high-quality education  and AIML program is uniquely transcribed and designed to underline the fact that Srinivas University is within the reach of everyone.

This BTech program is meticulously compiled and is aligned with the goals of Outcome-Based Education, Choice Based Credit System and the National Educational Policy-2020, cognizant of making Srinivas University a MetaVerse through innovative 
approaches to enhance the quality of education.


To be a centre of excellence in Computer Science and Engineering with quality education and research, responsive to the needs of industry and society.


To achieve academic excellence through innovative teaching-learning practice.

To inculcate the spirit of innovation, creativity and research.

To enhance employability through skill development and industry-institute interaction.

To develop professionals with ethical values and social responsibilities.

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Mr. Ranjit Kolkar
Assistant Professor and Head of the Department

Welcome to the exciting world of the AI ML Department at SUIET! Our faculty members are dedicated to fostering a stimulating learning environment for your academic and professional growth. With a practical and comprehensive curriculum, advanced research opportunities, and cutting-edge technologies, we strive to equip you with the skills and expertise in Artificial Intelligence and Machine Learning. Embrace the challenges, explore new frontiers, and unleash your potential in this rapidly evolving field. We are here to mentor and support you on your journey to becoming a successful AI ML professional.

  • Graduates will be

    PEO1: Competent professionals with knowledge of Computer Science & Engineering to pursue variety of careers and higher education.

    PEO2: Proficient in designing innovative solutions to real life problems that are technically sound, economically viable and socially acceptable.

    PEO3: Capable of working in teams, adapting to new technologies and upgrading skills required to serve the society with ethical values.

    • PSO1: Programming and software development skills: Ability to employ modern computer languages, computing environments and standard practices for analysing, designing and developing optimal solutions to deliver quality software products.

    • PSO2: Domain specific skills: Ability to apply techniques to develop computer based solutions in various domains like Artificial Intelligence, Machine Learning, Network Engineering, Image Processing, Web Technologies and Data Sciences.

  • PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization for the solution of complex engineering problems.

    PO2: Problem analysis: Identify, formulate, review research literature and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences and engineering sciences.

    PO3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety and the cultural, societal and environmental considerations.

    PO4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data and synthesis of the information to provide valid conclusions.

    PO5: Modern tool usage: Create, select and apply appropriate techniques, resources and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.

    PO6: The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

    PO7: Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts and demonstrate the knowledge of and need for sustainable development.

    PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

    PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

    PO10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

    PO11: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects, and in multidisciplinary environments.

    PO12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

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Sneha Jha - AIML 4th Sem

Studying in the AIML Department at Srinivas University has been an incredible experience. The focus on hands-on learning and supportive faculty members have helped me develop practical AI and ML skills. Workshops, seminars, and hackathons have boosted my knowledge and confidence. Proud to be a part of this excellent platform for aspiring professionals.

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Shraddesh - AIML 4th Sem

The AIML Department at Srinivas University transformed my career path. Knowledgeable faculty, comprehensive curriculum, and research opportunities make it an excellent choice for AI and ML enthusiasts. Highly recommended!

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Sathwik R - AIML 4th Sem


The AIML Department at Srinivas University offers a holistic learning experience in AI and ML. Expert faculty, advanced infrastructure, and challenging projects prepare us for real-world scenarios. Grateful for the skills and knowledge gained to excel in this field.

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