Placements @ SRIT

2021-22 Placements: DBS - 49(8.9 LPA), CTS - 181 (4(6.75 LPA), 18 (4.25 LPA), 159 (4.0 LPA)), Wipro - 239(3.5 LPA), Infor - 10 (6.5 LPA), Infosys- 43(3(6.5 LPA), 40 (3.6 LPA)), TCS - 119(Ninja - 115 (3.36 LPA) & Digital - 4 (7.0 LPA)), Capgemini - 39 (4.0 LPA), EPAM - 1(6.0 LPA),Astrazeneca - 1(5.56 LPA), Hitachi - 1(5.0 LPA), Accolite - 1(5.0 LPA), IBM - 36 (4.25 LPA), Hexaware - 17 ( 2 (5.0 LPA) & 15 (4.0 LPA)), Mindtree - 12 (4.0 LPA), HCL - 11(3.5 LPA) , KPIT - 5(4.0 LPA), Virtusa -1(4.0 LPA), Quest Global - 4(3.0 LPA), Zensar - 2(3.3 LPA)

2021-22 Placements: DBS - 49(8.9 LPA), CTS - 181 (4(6.75 LPA), 18 (4.25 LPA), 159 (4.0 LPA)), Wipro - 239(3.5 LPA), Infor - 10 (6.5 LPA), Infosys- 43(3(6.5 LPA), 40 (3.6 LPA)), TCS - 119(Ninja - 115 (3.36 LPA) & Digital - 4 (7.0 LPA)), Capgemini - 39 (4.0 LPA), EPAM - 1(6.0 LPA),Astrazeneca - 1(5.56 LPA), Hitachi - 1(5.0 LPA), Accolite - 1(5.0 LPA), IBM - 36 (4.25 LPA), Hexaware - 17 ( 2 (5.0 LPA) & 15 (4.0 LPA)), Mindtree - 12 (4.0 LPA), HCL - 11(3.5 LPA) , KPIT - 5(4.0 LPA), Virtusa -1(4.0 LPA), Quest Global - 4(3.0 LPA), Zensar - 2(3.3 LPA)

CSE - Artificial Intelligence & Machine Learning

Intro of CSE - AI & ML Program

Artificial Intelligence and Machine Learning is an immensely growing discipline that deals with a comprehensive study of designing, developing, supporting, and managing computer hardware, software and communication networks. Artificial Intelligence specialization will create engineers, who can build solutions, with intelligence as humans. With 5 million job openings a year, AI is called the skill of the century. The B.Tech Programmer with a specialization in AI and Machine Learning will have core courses from Computer Science and courses from emerging areas like artificial neural networks, deep learning, natural language processing, and cyber-physical systems.

Artificial Intelligence and Machine Learning is offered as a specialized UG program by the Department of Computer Science and Engineering at SRIT from the AY 2020-2021 with an intake of 60, increased to 120 in 2021. The curriculum of this program is designed by involving many senior academicians and leading industry experts. This program presents a solid foundation in the principles and technologies that underlie many facets of AI, including logic, knowledge representation, probabilistic models, machine learning, deep learning, extreme learning, language and speech processing etc.

This program aims to prepare the engineering graduates having potential knowledge with comprehensive practical experience in the areas of AI/ML in collaboration with leading industries (like Google, Amazon, IBM).

20 k+
Students
150 +
Courses
2 k+
Teachers

PROGRAM OVERVIEW

Computer Science and Engineering ( Artificial Intelligence & Machine Learning ) Program Overview

VISION:

To evolve as a leading department by offering best comprehensive teaching and learning practices for  students to be self-competent technocrats with professional ethics and social responsibilities.

MISSION:

DM 1: Continuous enhancement of the teaching-learning practices to gain profound knowledge in theoretical & practical aspects of computer science applications.

DM 2: Administer training on emerging technologies and motivate the students to inculcate self-learning abilities, ethical values and social consciousness to become competent professionals.

DM 3: Perpetual elevation of Industry-Institute interactions to facilitate the students to work on real-time problems to serve the needs of the society.

An SRIT graduate in Computer Science & Engineering, after three to four years of graduation will:

PEO 1: Lead a successful professional career in IT / ITES industry / Government organizations with ethical values.

PEO 2: Become competent and responsible computer science professional with good communication skills and leadership qualities to respond and contribute significantly for the benefit of society at large. 

PEO 3: Engage in life-long learning, acquiring new and relevant professional competencies / higher academic qualifications.

PO’s & PSO’s

PO 1: Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO 2: Problem Analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

PO 3: 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.

PO 4: 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.

PO 5: Modern Tool Usage: 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 limitations.

PO 6: 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.

PO 7: 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.

PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO 9: Individual And Team Work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO 10: 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.

PO 11: 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.

PO 12: 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.

Program Specific Outcomes

At the end of the B. Tech program in Computer Science and Engineering ( Artificial Intelligence and Machine Learning ), the graduate will be able to:

PSO1: Apply concepts to design and develop multi-disciplinary computing systems and applications.  

PSO2: Develop models in machine learning, deep learning, and big data technologies using AI knowledge and modern tools.

PSO3: Provide a solid foundation and enhance their abilities to qualify for higher education, research, and employment in Artificial Intelligence and Machine Learning with ethical values.

 

  Achievements:

1Department of CSE Accredited by NBA in 2018.
2Department of CSE has been Permanently Affiliated by JNTUA in 2018.

COURSE STRUCTURE

Computer Science and Engineering ( Artificial Intelligence & Machine Learning ) Course Structure

E-CONTENT

Computer Science and Engineering ( Artificial Intelligence & Machine Learning )  Course E-CONTENT

FACULTY

Computer Science and Engineering ( Artificial Intelligence & Machine Learning ) Faculty 

STUDENTS

Computer Science and Engineering ( Artificial Intelligence & Machine Learning ) Students