What You Need to Know Before
You Start

Starts 3 July 2025 14:06

Ends 3 July 2025

00 Days
00 Hours
00 Minutes
00 Seconds
course image

No-Code AI for Agriculture Professionals

Learn AI implementation in Agriculture using No-Code AI Platform without writing even a single line of code.
via Udemy

4123 Courses


3 hours 29 minutes

Optional upgrade avallable

Not Specified

Progress at your own speed

Paid Course

Optional upgrade avallable

Overview

Embark on a transformative learning journey with "No-Code AI for Agriculture Professionals," a comprehensive course designed to empower participants with the knowledge and practical skills needed to embrace the future of agriculture infused with artificial intelligence. This course goes beyond traditional coding, introducing a revolutionary no-code approach to seamlessly integrate AI into agricultural practices.

Syllabus

  • Introduction to AI in Agriculture
  • Overview of AI applications in agriculture
    Benefits of no-code AI for agriculture professionals
  • Understanding No-Code AI Tools
  • Introduction to popular no-code AI platforms
    Key features and capabilities of no-code tools
  • Data Management and Preparation
  • Basics of agricultural data
    Data collection techniques in agriculture
    Data preparation and preprocessing using no-code tools
  • Implementing AI for Crop Management
  • Monitoring crop health with AI
    Predicting yields and optimizing resources
    Pest and disease detection using no-code AI
  • AI in Livestock Management
  • Monitoring animal health and behavior
    Optimizing feeding and breeding practices
  • Precision Agriculture with No-Code AI
  • Real-time data analytics for precision farming
    Use of drones and sensors with AI
  • Machine Learning Techniques without Coding
  • Basics of machine learning algorithms applicable in agriculture
    Building and deploying models using no-code platforms
  • Case Studies and Industry Examples
  • Successful implementation of AI in agriculture
    Lessons learned from industry leaders
  • Ethical and Sustainable AI Practices
  • Understanding the ethical implications of AI in agriculture
    Sustainability considerations for AI-driven solutions
  • Practical Workshop
  • Hands-on projects using no-code AI platforms
    Developing personalized AI strategies for participants' specific needs
  • Final Assessment and Course Wrap-up
  • Project presentations and feedback
    Summary and future directions in AI for agriculture

Taught by

Dr Manoj Manuja


Subjects

Programming