Professional Development Program (PDP) on Machine Learning & Business Analytics Laboratory Applications

17th – 22nd November 2025

 

📘 Overview

The School of Computing, in collaboration with the Mechanical Engineering Department, MVGR College of Engineering (Autonomous), successfully organized a six-day Professional Development Program (PDP) on Machine Learning and Business Analytics Laboratory Applications from 17th to 22nd November 2025.

The program aimed at strengthening faculty expertise in modern Machine Learning (ML) techniques and equipping them with hands-on skills to integrate ML-driven laboratory experiments into academic curricula.

 

🎯 Objectives of the Program

The PDP focused on enabling participants to:

  • Understand foundational concepts of Supervised, Unsupervised, Semi-supervised, and Reinforcement Learning.
  • Gain familiarity with qualitative and quantitative data forms.
  • Develop practical exposure to ML techniques such as regression, classification, clustering, and NLP.
  • Learn to compare ML models and evaluate performance through metrics and visualization tools.
  • Apply ML to real-world applications in engineering, science, and business analytics.

 

🧪 Key Technical Sessions & Applications

Participants engaged in intensive hands-on sessions covering Python, ML algorithms, and dataset exploration. Applications included:

🔹 Supervised Learning

  • Predicting housing prices
  • Estimating human height/weight
  • Handwritten digit recognition
  • Detecting Parkinson’s disease
  • Email spam classification
  • Identifying fake vs real restaurant reviews

🔹 Unsupervised Learning

  • Customer segmentation
  • Fraud detection using K-Means clustering

🔹 Model Comparison

  • Performance evaluation of ML models on wine quality datasets

🔹 Reinforcement Learning

  • Path optimization using Q-Learning in Gridworld

🔹 Natural Language Processing

  • Sentiment analysis for movie review data

🔹 Specialized Applications

  • Building product recommendation systems

 

💡 Tangible Outcomes and Benefits

For Faculty

  • Enhanced proficiency in Python, NumPy, Pandas, Scikit-learn, TensorFlow, and Keras
  • Capability to design & evaluate ML experiments and integrate them into lab manuals and curricula
  • Ability to incorporate project-based, experiential learning into teaching
  • Strengthened interdisciplinary collaboration across engineering and science departments
  • Contribution to the creation of datasets, ML codes, video tutorials, and digital courseware

For Students

  • Improved mentoring support for AI/ML projects, internships, hackathons, and research
  • Access to faculty-trained, modernized ML laboratory facilities
  • Exposure to real-world datasets and industry-aligned ML tools

The program also acts as a foundation for advanced training in Deep Learning, AI Ethics, and Data Visualization.

 

👥 Participation

A total of 89 faculty members from various departments — including Civil, Mechanical, IE&CT, DE, ECE, CSE, EEE, and Chemical Engineering — actively participated in the program.
The participant group represented diverse academic backgrounds, reinforcing the interdisciplinary nature of Machine Learning.

 

📸 Highlights

  • Brochure & poster launch
  • Engaging coding sessions conducted in ML/BA laboratories
  • Hands-on training using real datasets
  • Interactive Q&A sessions with resource persons
  • Valedictory ceremony on 22nd november 2025

 

🏆 Organizing Committee

Chief Patron

  • Sri P. Ashok Gajapathi Raju, Chairman, MANSAS

Patron

  • Dr. K. V. L. Raju, Correspondent, MANSAS

President(s)

  • Sri P. S. Sitharama Raju, Director
  • Dr. Y. M. C. Sekhar, Principal

Advisory Committee

  • Dr. V. Nagesh, IE&CT
  • Dr. P. Srinivasa Rao, IE&CT
  • Dr. P. Satheesh, DE
  • Dr. C. Kalyana Chakravarthy, CSE
  • Dr. T. Pavan Kumar, CSE

Convener

  • Dr. Anjanadevi B, HOD – IE&CT
  • Dr. V. Jyothi, Associate Professor & HOD - DE
  • B. Aruna Kumari, Professor & HOD - CSE
  • K. Praveen Professor & HOD – Mech

Coordinators

Mr. Srikanth Ganta - Prof., IE&CT

Dr. B. Srinivas - Prof., IE&CT

Dr. S Atchuta Rao - Prof., DE Dept

Dr. G. Satyanarayana Reddy - Assoc. Prof., DE Dept

Mrs. K. Sobha Rani - Prof. (TP) , CSE Dept

Mr. R. Ravikanth - Assoc. Prof., (TP) , CSE Dept

Co-Coordinators

Dr. M. Chandra Sekhar - Assoc. Prof., IE&CT Dept

Mr. D. Nagendra Kumar - Assoc. Prof.,(TP), IE&CT Dept Dr. Y. Home Prasanna Raju- Assoc. Prof., IE&CT Dept Dr. K. Santosh Jhansi - Assoc. Prof., CSE Dept

Mrs. M. Beulah Rani - Assoc. Prof.(TP), CSE Dept Mrs. N. Sowjanya Kumari - Asst Prof., DE Dept Mr. V. Kiran Kumar - Asst Prof., DE Dept

Organizing Committee

Mrs. Swarna - Assoc. Prof., IECT

Mrs. B. Sujatha - Assoc. Prof., IECT Mr.M. Srinivasa Rao - Asst. Prof., IECT Mrs. P. Ramya - Asst. Prof., IECT

Mr. R. Ravi - Asst. Prof., IECT

Mr. L. Kiran Kumar - Asst. Prof., IECT

Mrs. D. Gayatri - Asst. Prof., IECT

Mrs. M. Sai Vasanthi - Asst. Prof., IECT Mrs. M. Symala Kumari - Asst. Prof., IECT Mrs. G. Bhagya Laksmi - Asst. Prof., IECT Mrs. A. Bhanusri - Asst. Prof., IECT

Mrs. Priyanka Balaga - Asst. Prof., IECT Mrs. M.S.B. Deepthi - Asst. Prof., IECT Mrs. D. Sheetal Sharma - Asst. Prof., IECT Ms. P S S Geetika - Asst. Prof., IECT

Mr. S B V V Varalaxmi - Asst. Prof., IECT

Ms. K Kiranmai - Asst. Prof., IECT

Ms. G Srirupa - Asst. Prof., IECT

Ms. Ch. Gunalakshmi - Asst. Prof., IECT Mr. M Satish Kumar - Asst. Prof., IECT Mrs. P. Sandhya - Asst. Prof., IECT

Ms. N.Ch. Meghana - Asst. Prof., IECT

Mr. K V Subba Raju - Assoc. Prof. (TP), CSE Mr. K.A. Prasada Raju - Assoc. Prof.(TP), CSE Mr. P.L.N. Raju - Assoc. Prof.(TP), CSE

Dr. P. Rama Santosh Naidu - Distinguished Asst. Prof, CSE Mr. T. Chaitanya Kumar - Distinguished Asst. Prof, CSE Mr. M. Vamsi Krishna - Sr. Asst.Prof., CSE

Mr. N. Narendra Kumar - Sr. Asst.Prof., CSE

Mr. R. Ravi Kumar - Sr. Asst.Prof., CSE Mr. T. Govindararao - Asst. Prof., DE Mr. Sura Paparao - Asst. Prof., DE

 

🎉 Conclusion

The Professional Development Program on Machine Learning & Business Analytics Laboratory Applications proved to be a highly impactful initiative, enriching faculty capabilities and strengthening MVGR’s commitment to emerging technologies and skill-oriented education.

The College looks forward to conducting more such interdisciplinary knowledge-building programs in the future.

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