Artificial Intelligence (AI) is a computing concept that enables a machine to think and solve complex problems as we humans do with our natural intelligence. AI is the next phase of the industrial revolution and has established itself firmly in our society. Almost all branches of industry have been affected by the ongoing transformation through its algorithms.
Machine Learning explores the analysis and construction of algorithms that can learn from and make predictions on data. ML has proven valuable because it can solve problems at a speed and scale that cannot be duplicated by the human mind alone. With massive amounts of computational ability behind a single task or multiple specific tasks, machines can be trained to identify patterns in and relationships between input data and automate routine processes.
The AI & ML has opened up exciting new opportunities for interdisciplinary work across many fields including computer science, mathematics, statistics, and information science from which it draws foundational knowledge and the current demand for a career in AI & ML is considerable and growing daily.
The B.Tech (Artificial Intelligence and Machine Learning) course addresses this transformation by providing you as a student with the broad and in-depth skills required to work with and develop AI. You will be trained how to obtain, process and store enormous amounts of data, which is the root of AI and development processes.
VISION:
To become a Centre of Excellence in AI&ML, shaping professionals obliging to the research and proficient needs of national and international organizations and to bring up innovative ideas to solve real time problems through continuous research, innovation, and industry steered curriculum.
MISSION:
M1: To transform the students into technologically proficient and help them to absorb the innovative spirit.
M2: To impart premier quality, skill-based and value-based education to the students in the field of Artificial Intelligence and Machine Learning.
M3: To identify corporate requirements and enrich the students’ expertise with a strong theoretical and practical backdrop having an emphasis on hardware and software development with social ethics.
Program Educational Objectives (PEOs)
PEO1
To Formulate, analyse and solve Engineering problems with strong foundation in Mathematical, Scientific, Engineering fundamentals and modern AI&ML practices through advanced curriculum.
PEO2
Analyze the requirements, realize the technical specification and design the Engineering solutions by applying artificial intelligence and machine learning theory and principles.
PEO3
Demonstrate technical skills, competency in AI&ML and promote collaborative learning and team work spirit through multi-disciplinary projects and diverse professional activities along with imbibing soft skills and ethics.
Program Outcomes and Program Specific Outcomes of AI&ML Department (POs & PSOs)
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, 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 specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
PO4: Conduct investigations of complex problems: using research-based knowledge and research methods including design of experiments, analysis and interpretation of data and synthesis of 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 contextual knowledge to assess societal, health, safety, legal and cultural issues, and the consequent responsibilities relevant to professional engineering practice.
PO7: Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate knowledge of and need for sustainable development.
PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
PO9: Individual and Teamwork: Function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary 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 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. Any signatory needs to provide an overview of its learning outcomes and confirm that compliance of programs.
PSO1
The ability to understand, analyse and demonstrate the knowledge of human cognition, Artificial Intelligence, Machine Learning and data science in terms of real world problems to meet the challenges of the future.
PSO2
The ability to develop computational knowledge and project development skills using innovative tools and techniques to solve problems in the areas related to Deep Learning, Machine learning, Artificial Intelligence.
Machine Learning Mavericks Club
Exploring, Learning, Innovating Responsibly with Machine Learning
Vision:
To create a community of learners who are passionate about exploring and implementing machine learning technologies to solve real-world problems and drive innovation.
Mission:
- To provide a platform for students to learn and implement machine learning technologies in real-world scenarios.
- To organize technical workshops, seminars, and hackathons to enhance the technical skills of members.
- To encourage members to participate in machine learning competitions and projects.
- To collaborate with industry experts and academia to bring real-world experiences and knowledge to the club.
- To foster a culture of innovation and creativity in the field of machine learning and its applications.
- To provide opportunities for members to network with like-minded individuals and industry professionals.
- To promote the use of machine learning technologies for social good and community development.
(Overall, the Machine Learning Mavericks student club aims to provide a supportive community for students to explore, learn, and apply machine learning technologies to solve real-world problems and contribute to the field of AI and ML.)
Faculty Co-ordinator:
Mr. S. Sathish Kumar (Ph.D.), Assistant Professor, AI&ML Department
Student Co-ordinators:
AI&ML - Section A
Mr. B. Chandrashekar
Mr. Syed Faizanuddin
AI&ML - Section B
Mr. Om Verma
Mr. Koushik Pingilli
Expert lectures organized for students:
Sl.No.
|
Name of the Expert and Affiliation
|
Lecture Topic
|
Target group
|
Date(s)
|
1
|
S. Sathish Kumar, JBIET
|
Goal Setting
|
Students of AI&ML
|
29-10-2022
|
Guest lectures organized for students:
Sl.No.
|
Name of the Guest and Affiliation
|
Lecture Topic
|
Target group
|
Date(s)
|
-
|
Mr. E. Chaitanya, Senior Software Engineer, GAP Inc. Hyderabad
|
Industry Expert Guest Lecture on “The Growing Importance of Mobile E-Commerce"
|
2nd Year Students of AI&ML
|
21-04-2023
|
-
|
Mrs. Teena, a renowned System Administrator from ICE DATA SERVICES INDIA PRIVATE LIMITED, Hyderabad
|
Industry Expert Guest Lecture on “Introduction to System Administration"
|
2nd Year Students of AI&ML
|
21-04-2023
|
-
|
Mr. Om Verma, Mr. Koushik, Machine Learning Mavericks Club
|
One day Student forum on “Applications of AI & Introduction to Julia” on
|
2nd Year Students of AI&ML
|
12-04-2023
|
-
|
An Expert Team from “Bhaskar Medical College”, A Sister Institute of JBIET
|
One day Awareness Program on “Medical Emergencies”
|
2nd Year Students of AI&ML
|
21-03-2023
|
-
|
An expert team from Moinabad Police Station
|
One day “Self Defence Training program for Girl Students”
|
2nd Year Students of AI&ML
|
28-03-2023
|
Prizes won by the students in Paper contests:
Sl.No.
|
Student Details
|
Title of the paper
|
Dates and Place
|
Prize
Awarded
|
1
|
Om Verma, Kaushik Pingili
|
Multiclass Classification of Intellectual Quotes using
Transformers
|
11-03-2023, JBIET
|
First Prize
|
2
|
Malavika Joshi, Shada Manogna
|
Machine Learning-Based Credit Card Fraud Detection: Evaluating Standard and Hybrid Techniques with Majority Voting
|
11-03-2023, JBIET
|
Second Prize
|
Papers presented by the students in Conferences:
Sl.No.
|
Title of the paper
|
Name(s) of Author(s)
|
Details of Proceedings
(in IEEE format)
|
1
|
Machine Learning-Based Credit Card Fraud Detection: Evaluating Standard and Hybrid Techniques with Majority Voting
|
Malavika Joshi1, Shada Manogna2, Mrs. Beulah J Karthikeyan3*, Dr. Sankara Sarma KVSSRS4
|
Malavika Joshi, Shada Manogna, Mrs. Beulah J Karthikeyan, Dr. Sankara Sarma KVSSRS, Machine Learning-Based Credit Card Fraud Detection: Evaluating Standard and Hybrid Techniques with Majority Voting, International Journal of System Design and Information Processing (SDIP), ISSN: (Print): 2319-9288 | (Online): 2321-0591
|
2
|
Using multiple methods including Naïve Bayes, K-
Nearest Neighbours, and Decision Tree Algorithms
with Ensemble Learning to diagnose diabetes
|
Mahek Tikedar1, Rallapalli Lakshmi Chandana2 , Mrs. Beulah J Karthikeyan3*Dr. Sankara Sarma KVSSRS4
|
Mahek Tikedar, Rallapalli Lakshmi Chandana, Mrs. Beulah J Karthikeyan, Dr. Sankara Sarma KVSSRS4, Using multiple methods including Naïve Bayes, K-Nearest Neighbours, and Decision Tree Algorithms
with Ensemble Learning to diagnose diabetes, International Journal of System Design and Information Processing (SDIP), ISSN: (Print): 2319-9288 | (Online): 2321-0591
|
3.
|
Multiclass Classification of Intellectual Quotes using
Transformers
|
Om Verma1, Kaushik Pingili 2 , Dr. G. Arun Sampaul Thomas 3* , S. Sathish Kumar4
|
Om Verma, Kaushik Pingili, Dr. G. Arun Sampaul Thomas, S. Sathish Kumar, Multiclass Classification of Intellectual Quotes using
Transformers, International Journal of System Design and Information Processing (SDIP), ISSN: (Print): 2319-9288 | (Online): 2321-0591
|
4.
|
Exploring the Effectiveness of Supervised Learning
Algorithms for Identifying Suicidal Thoughts in
Textual Data
|
M. Sanjana Ninni1 , Harika Musku2 , S. Sathish Kumar3* ,G. Arun Sampaul Thomas
|
M. Sanjana Ninni, Harika Musku , S. Sathish Kumar ,G. Arun Sampaul Thomas, Exploring the Effectiveness of Supervised Learning
Algorithms for Identifying Suicidal Thoughts in
Textual Data, International Journal of System Design and Information Processing (SDIP), ISSN: (Print): 2319-9288 | (Online): 2321-0591
|
Student Club Activities:
Sl. No
|
Name of the Student Club
|
Activity Conducted
|
Date
|
No. of participants
|
1
|
Machine Learning Mavericks Club
|
One Day Student Forum on “Applications of AI & Introduction to Julia Programming”
|
12-04-2023
|
140
|
Industrial Visits
Sl. No
|
Name of the Industry
|
Date of Visit
|
Target group
|
No of students
|
Outcome
|
1
|
DRDL Hyderabad
|
17-04-2023
|
2nd Year Students of AI&ML
|
140
|
The visit offered our AI&ML students a chance to learn about DRDL's research and development and expand their knowledge of the defense technology industry.
|
Internships
Sl. No
|
Name of the Company
|
Student Details
|
Duration
|
Date From-to
|
No of students
|
Outcome
|
1
|
Verzio Pvt. Ltd.,
|
2nd Year Students of AI&ML
|
4 Weeks
|
2-1 (AY 2022-23 / I sem)
|
30
|
Students grasped AI&ML applications through project-based learning supported by the company.
|
2.
|
Lbits Pvt. Ltd.,
|
2nd Year Students of AI&ML
|
4 Weeks
|
2-1 (AY 2022-23 / I sem)
|
51
|
3.
|
Y-Hills solutions.,
|
2nd Year Students of AI&ML
|
4 Weeks
|
2-1 (AY 2022-23 / I sem)
|
23
|
4.
|
V-Cube Pvt. Ltd.,
|
2nd Year Students of AI&ML
|
4 Weeks
|
2-1 (AY 2022-23 / I sem)
|
36
|