New Year Offer End Date: 30th April 2024
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Program

Digital Twin Agriculture: Mastering Multi-Source Data Fusion & Machine Learning

Learn How Ai Can Monitor Crops , Predict Yeild & Improve Farming

Skills you will gain:

About Program:

In this workshop, you will learn how AI is used to monitor crop health, predict yield, and improve farming decisions using real-world data

Aim: To equip participants with practical knowledge and hands-on skills in using AI, data analytics, and precision monitoring tools to optimize crop management, improve yield predictions, and support sustainable agricultural practices

Program Objectives:

  • To introduce participants to AI-driven tools and technologies for crop monitoring and management.

  • To enable accurate prediction of crop yields using data analytics and modeling techniques.

  • To teach methods for assessing and improving crop health through real-time monitoring.

  • To demonstrate how precision agriculture techniques can optimize resource use and sustainability.

  • To provide hands-on experience with practical datasets, sensors, and analytics platforms for informed decision-making in agriculture.

What you will learn?

📅 Day 1 — Monitoring Crop Health with AI & Remote Sensing

  • Overview of crop intelligence and precision agriculture
  • Introduction to remote sensing and IoT sensor data in agriculture
  • AI techniques for monitoring crop growth and detecting stress
  • Key data sources and standards for crop research (MDPI datasets, open-access repositories)

🛠️ Hands-on:

  • Using satellite imagery and NDVI indices to assess crop health with Python (NumPy, Pandas, Rasterio)

📅 Day 2 — Predicting Crop Yields Using Machine Learning

  • Data preprocessing and feature engineering for crop datasets
  • Supervised learning models for crop yield prediction (Random Forest, XGBoost, LSTM)
  • Integration of environmental and climate data into predictive models
  • Model evaluation metrics and best practices for agriculture datasets

🛠️ Hands-on:

  • Building a crop yield prediction model using historical MDPI crop datasets

📅 Day 3 — Improving Crop Productivity through Data-Driven Insights

  • Decision support systems for crop management
  • AI-driven irrigation, fertilization, and pest management strategies
  • Trend analysis and data visualization for agronomic decisions
  • Future of AI in agriculture and emerging trends

🛠️ Hands-on:

  • Visualizing crop recommendations and productivity optimization strategies using Python (Matplotlib, Seaborn, Plotly)

Mentor Profile

Fee Plan

INR 1999 /- OR USD 50

Get an e-Certificate of Participation!

2024Certfiacte

Intended For :

  • Agricultural researchers and scientists interested in AI applications in farming.

  • Agronomists and crop consultants looking to adopt precision agriculture techniques.

  • Data scientists and machine learning practitioners focusing on agriculture datasets.

  • Students and Ph.D. scholars in agriculture, biotechnology, environmental science, or data analytics.

  • Professionals in agri-tech startups and companies seeking to optimize crop productivity.

  • Policy makers and sustainability experts exploring data-driven approaches in agriculture.

Career Supporting Skills

Program Outcomes

  • Participants will be able to monitor crop health effectively using AI and sensor-based technologies.

  • Participants will gain the ability to predict crop yields accurately through data-driven models.

  • Participants will learn strategies to optimize resource usage and improve overall farm productivity.

  • Participants will acquire hands-on experience with agricultural datasets and analytics tools.

  • Participants will be prepared to implement precision agriculture practices for sustainable crop management.