Hands-on Skill Development Program on Machine Learning Applications
for Predictive Analytics in Agriculture and Rural Development
India’s agriculture supports nearly 60% of the rural population, yet faces persistent challenges including erratic weather, fluctuating yields, and limited access to data-driven decision-support systems.
Advances in Machine Learning (ML) and Predictive Analytics present powerful opportunities to enhance agricultural productivity and sustainability. However, rural and Scheduled Tribe (ST) youth often remain excluded from these emerging digital skills.
This program addresses the gap by equipping ST youth and women with hands-on ML training using real agricultural datasets—enabling predictive insights for crop yield, rainfall, and soil health while fostering inclusive, data-driven rural development.
Program Objectives
Impart foundational knowledge of data science, machine learning, and predictive analytics with real-world applications.
Develop hands-on expertise using Python, Pandas, Scikit-learn, and data visualization libraries for agricultural problem-solving.
Enable participants to collect, preprocess, and analyze agricultural datasets for forecasting rainfall, yield, soil quality, and market trends.
Encourage innovation through mini-projects and team-based activities addressing real rural and agricultural challenges.
Promote inclusion and digital literacy among ST youth and women through accessible training and mentorship.
Build a sustainable ecosystem of data-skilled professionals supporting rural entrepreneurship and agricultural modernization.
Key Outcomes / Expected Impact
Capacity Building
Participants gain hands-on ML training, certified competencies in data handling, and develop 4–5 mini-projects addressing real agricultural challenges.
Skill Application & Employability
Enhanced employability and self-employment opportunities through exposure to AI/ML tools relevant to agri-tech and data services.
Long-Term Impact
Digital inclusion, improved agricultural productivity, increased participation of ST women in STEM, and sustainable skilling ecosystems.
Program Schedule
Day 1
Introduction to Data-Driven Decision Making
- Overview of Data Science, AI, and ML
- Role of Predictive Analytics in Agriculture and Rural Development
- Introduction to Data Sources (Soil, Weather, Crop, Market)
- Setting up Python Environment (Anaconda, Jupyter)
Day 2
Data Handling and Preprocessing
- Data Collection, Cleaning, and Organization
- Working with Agricultural Datasets (CSV, APIs)
- Exploratory Data Analysis using Pandas and Matplotlib
- Visualizing Trends in Crop and Weather Data
Day 3
Machine Learning Fundamentals
- Supervised & Unsupervised Learning
- Regression and Classification Models
- Model Training and Testing
- Case Study: Crop Yield Prediction
Day 4
Predictive Analytics Applications
- Time Series Forecasting (Rainfall / Market Price)
- Decision Trees and Random Forest
- Evaluating Model Accuracy
- Mini Project: “Data to Decision”
Day 5
Deployment, Visualization, and Presentation
- Model Deployment Basics
- Dashboards using Streamlit & Power BI
- Project Presentations and Peer Evaluation
- Evaluation and Reflection
Eligibility Criteria
- Students must be enrolled in a recognized institute or university.
- Eligible for BTech & BE students from all branches.
- Must possess a valid student ID card.
- Basic understanding of computer fundamentals is desirable.
- Open for I, II, III & IV Year Engineering students.
Download the detailed brochure for complete program information:
Speakers
Industry experts and academic leaders
Central and National Institutes
Dr. P. Krishna Reddy
Professor, Center for Data Engineering
International Institute of Information Technology, Gachibowli, Hyderabad
Dr. Monalisa Patra
Associate Head, ML Research Center / iHub-Data
International Institute of Information Technology, Gachibowli, Hyderabad
Dr. Pranitha Sanda
Researcher
CR Rao Advanced Institute of Mathematics, Statistics and Computer Science, University of Hyderabad Campus, Gachibowli
Dr. A. Amara Jyothi
Researcher
University of Hyderabad, Gachibowli, Hyderabad, Telangana
Universities and Private Engineering Institutions
Sri. B. Vikas
Associate Director – Academic Planning & Strategy, Deputy Director (I/C) – CETLI
Sreenidhi University, Yamnampet, Hyderabad
Dr. Md. Ali Hussain
Dean – Research & Development
Sreenidhi Institute of Science & Technology, Hyderabad, Telangana
Dr. M. Kumara Swamy
Professor & Head, CSE (AI & ML)
Sreenidhi University, Yamnampet, Hyderabad, Telangana
Dr. G. Padmaja
Professor & Head, Department of CSE
Sreenidhi University, Yamnampet, Hyderabad, Telangana
Dr. K. Ravikanth
Professor, Department of CSE
Aurora University, Hyderabad
Dr. G. Kiran Kumar
Professor
Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad
Dr. Ram Anirudh
Assistant Professor, Department of CSE
Sreenidhi University, Yamnampet, Hyderabad, Telangana
Sri. Silpa Padmanabhuni
Assistant Professor, Department of CSE
PSCMR College of Engineering & Technology, Vijayawada, Andhra Pradesh
Industry and Professional Experts
Dr. Gundala Nagaraju
Vice-President, Technology Alumni Association (IIT Kharagpur – Hyderabad Chapter)
Hyderabad, Telangana
Dr. Srinivasa Rao Perla
Director – Technical Training
Cyient Limited, Hyderabad, Telangana, India
Organizing Committee
Shri. Abhijit Rao Katikaneni
President
Dr. P. Narasimha Reddy
Pro-Chancellor
Dr. T. Chandrashekar
Registrar
Dr. M. Karthikeyan
Dean, School of Engineering