Artificial Intelligence & Data Science

About Department

Artificial Intelligence and Data Science (AI&DS) is a new, exponentially emerging field which consists of a set of tools and techniques used to extract useful information from data. AI&DS is a fast growing discipline and is full of rigorous practical analysis. The demand for undergraduates in AI and DS has experienced an increasing demand in the Global market over the last few years. Building human-level thought processes through the creation of artificial intelligence (AI) is the state-of-the-art in Computer Science. Intelligent machines are influenced by emerging technologies, smart devices, sensors, computing power, faster data processing, huge storage and human-machine interaction capabilities. Data Science (DS) is an interdisciplinary field with the ability to extract knowledge/insights from data - be it structured, unstructured, or semi-structured data. AI with DS, is in demand with the extensive usage of smart phones, innovations in social media, online banking, etc.., and more efficient and powerful solutions to smart environments including Internet of Things and Industry 4.0. AI and DS delivers data driven solution using computational principles, methods and systems for extracting knowledge from data and modern computational systems that demonstrate capabilities of perception, reasoning, learning and action that are typical of human intelligence.

B.Tech. Artificial Intelligence and Data Science programme kick-starts, in our College, from the academic year 2020 – 21 with a vision to build the intellectual capital of the society through research-based education, creating new knowledge and innovations. AI and DS course aims to indulge knowledge in not only the core technologies such as artificial intelligence, data warehousing, data mining and data modelling and also make ready students expertise in thrust areas such as machine learning and big data analytics. Students with this course can gain thorough knowledge in: Intelligent Systems, Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Text Technologies for Data Science, Data Analytics and Mining, Big Data Management, Data Visualization, Bayesian Data Analysis, Probabilistic Modeling and Reasoning, Cloud Technologies, Internet of Things, Statistical Learning and visualization skills.

This graduate program has a comprehensive coverage of applied mathematics used in data science and artificial intelligence while preparing the students to analyze, design and experiment solutions to problems. The curriculum targets technical and design skills, AI knowledge, and competencies needed to master strategic analytical methods and tools, and data management, with the objective of creating innovative strategies to solve challenging real-world problems.

Career opportunities in Artificial Intelligence and Data Science are Data Scientist, Knowledge Engineer, Data Engineer, Business Analyst, Data Analyst, Business Intelligence Engineer and Research Scientist.

The faculty members are highly motivated and devoted in delivering the highest quality professional education to students, and strive to excel in their research areas.

Vision
Mission

The vision of the Department of Artificial Intelligence and Data Science is to impart quality education and produce high quality, creative and ethical engineers, instill professionalism, enhance students' problem solving skills in the domain of artificial intelligence and data science with a focus to prepare them for the industry, engage them in potential research areas, to pursue and have continued professional growth to serve the greater cause of society.

To provide skill based education to master the students in problem solving and analytical skills to enhance their niche expertise in the field Artificial Intelligence and Data Science.
To educate the students with latest technologies to update their knowledge in the field of AI and Data science.
To enable students to experience content based learning with premier quality data science education, research and industrial collaboration.
To guide students in research on Artificial Intelligence and data science, with aim of having an ethical impact on society by tackling societal grand challenges.
To impart quality and value based education and contribute towards the innovation of computing system, data science to raise satisfaction level of all stakeholders

S.No.	Programme Educational Objectives
PEO1	To Formulate, analyze and solve Engineering problems with strong foundation in Mathematical, Scientific, Engineering fundamentals and modern computing practices through advanced curriculum.
PEO2	Analyze the requirements, realize the technical specification and design the Engineering solutions by applying artificial intelligence and data science theory and principles.
PEO3	Demonstrate technical skills, competency in AI and DS and promote collaborative learning and team work spirit through multi -disciplinary projects and diverse professional activities.
PEO4	Equip the graduates with strong knowledge, competence and soft skills that allows them to contribute ethically to the needs of society and accomplish sustainable progress in the emerging computing technologies through life-long learning.

Engineering Graduates will be able to

S.No.	PROGRAM OUTCOMES (POs)
PO1	Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO2	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.
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 modeling 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.

S.No.	Programme Specific Outcomes
PSO1	Understand, analyze and develop essential proficiency in the areas related to artificial intelligence and data science in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems.
PSO2	Implement Artificial Intelligence and data science techniques such as search algorithms, neural networks, machine learning and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship.
PSO3	Apply the skills in the areas of health care, education, agriculture, intelligent transport, environment, smart systems and in the multi-disciplinary area of Artificial Intelligence and Data Science.

Artificial Intelligence & Data Science is a four-year Bachelor of Technology (B. Tech) degree offered by the department. The B. Tech program's curriculum consists of core courses, department elective courses, seminars, laboratory experiments, and projects. The curriculum provides enough freedom for students to choose optional courses that expose them to different specialties in Artificial Intelligence & Data Science.

S.No	Program Name	Year of Establishment	Current Intake
1	B. Tech	2020	120

AI-DS

List of BoS Members
S.No.	Name of the Member	Role in Board of Studies	Category
1	Dr. P Phanindra Kumar Reddy, Assoc. Professor & Head Dept. of AI & DS, A.I.T.S. Rajampet.	Chairman	Ex-officio
2	Dr S Ravi Chandra, Assoc. Professor, NIT Warangal	Member	Subject Expert
3	Dr Vikram Pudi, Professor, IIIT Hyderabad	Member	University Nominee
4	Mr. A Ramesh Babu, Asst. Professor, AI & DS Department, AITS, Rajampet	Member	Internal Member
5	Mr. P Nagendra, Asst. Professor, AI & DS Department, AITS, Rajampet	Member	Internal Member
6	Dr. E Poovammal, Professor & HoD, SRm University, Chennai	Member	Subject Expert
7	Mr. S Ramanjaneyulu, Executive Manager, Deloitte, Hyderabad	Member	Industry Expert
8	Mr. N Arun Kumar Reddy , Senior Engineer, Qualcomm, Hyderabad	Member	Alumni Member

BoS-15 Minutes

BoS-14 Minutes

BoS-16 Minutes

1	NEUMANN LAB	Number of Clients : 71 System Configuration: LENOVO 35972J4 Dual Core DESKTOPINTEL H61 Chipset, Intel Core Dual Core G202 Processor, 2GB DDR3 RAM, 500GB HDD

Sl.No	Name of the faculty	Designation	Date of joining
1	Dr. P. Phanindra Kumar Reddy	Associate Professor & HOD	18.06.2008
2	B. Panduranga Raju	Assistant Professor	18.06.2007
3	A. Ramesh Babu	Assistant Professor	30.08.2010
4	S. Ashok Kumar	Assistant Professor	01.08.2015
5	P. Nagendra	Assistant Professor	20.06.2016
6	B. Venkatesu Goud	Assistant Professor	21.04.2022
7	N. Swathi	Assistant Professor	15.06.2023
8	U. Naresh Kumar	Assistant Professor	01.09.2023
9	S. Prasanna	Assistant Professor	03.10.2023
10	M. Joshna	Assistant Professor	05.10.2023
11	D Sai Shireesha	Assistant Professor	28-08-2024
12	M Nandinin	Assistant Professor	03-10-2024

Sl.No	Inst. ID	Name of the faculty	Designation	Qualification	Date of joining
1	AITS051006	Dr. P. Phanindra Kumar Reddy	Associate Professor & Head	M.Tech, Ph.D.	18.06.2008
2	AITS121005	B. Panduranga Raju	Assistant Professor	M.Sc.(CS), M.Tech.	18.06.2007
3	AITS051013	A. Ramesh Babu	Assistant Professor	M.Tech.	30.08.2010
4	AITS121012	S. Ashok Kumar	Assistant Professor	M.Tech.	01.08.2015
5	AITS121013	P. Nagendra	Assistant Professor	M.Tech.	20.06.2016
6	AITS051047	B. Venkatesu Goud	Assistant Professor	M.Tech.	21.04.2022
7	AITS051079	N. Swathi	Assistant Professor	M.Tech.	15.06.2023
8	AITS051048	U. Naresh Kumar	Assistant Professor	M.Tech.	01.09.2023
9	AITS1F1026	S. Prasanna	Assistant Professor	M.C.A.	03.10.2023
10	AITS1F1027	M. Joshna	Assistant Professor	M.C.A.	05.10.2023
11	AITS1F1028	P. Renuka	Assistant Professor	M.C.A.	11.03.2024