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LEARN AI Dashboard

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Welcome to LEARN AI! 💡

Empowering Agricultural Professionals with AI/ML Skills

This volunteer training, led by Delstarford Isaiah, provides completely free resources for students and innovators passionate about integrating **Artificial Intelligence, Machine Learning, and Deep Learning** into Agriculture.

🚀 Join Daily Google Meet Session

📅 Course Structure & Weekly Plan

Weekly Study Focus (Example Week)

Day Focus Area
MON Folder Structure and Organisation
TUE Basics of AI and the Subsets of AI
WED Algorithms and Pretrained Model
THUR Application in Agriculture
FRI Code Writing of the AI Models Creation / Exercise

This curriculum blends practical skills with domain-specific applications, ideal for professionals like you working at the intersection of AI, agriculture, and innovation.

Module Summary (Complexity Rating):

  • ⭐ **Module 1 (Weeks 1–4):** AI Fundamentals & Agricultural Challenges.
  • ⭐⭐ **Module 2 (Weeks 5–10):** Core ML Techniques (Data Handling, Supervised/Unsupervised Learning).
  • ⭐⭐⭐ **Module 3 (Weeks 11–15):** Computer Vision (CNNs for Disease Detection, Image Analysis).
  • ⭐⭐ **Module 4 (Weeks 16–18):** NLP for Agri-Intelligence (Text Mining, Chatbots).
  • ⭐⭐⭐ **Module 5 (Weeks 19–21):** Robotics & IoT Integration (Sensors, Autonomous Farming).
  • ⭐⭐⭐⭐ **Module 6 (Weeks 22–24):** Advanced AI Techniques & Capstone Project.

Download Full Resources

View the PDF document and download it below:

📥 Download Full Syllabus & Timetable (PDF)

🎥 Curated Video Resources (40+ Lessons)

Your dedicated playlist for foundational and advanced AI/ML topics in agriculture.

About Delstarford Isaiah (Instructor)

1. Introduction to Artificial Intelligence

2. What is Machine Learning?

3. Understanding Deep Learning

4. Python for Data Science

5. Introduction to Neural Networks

6. Supervised vs Unsupervised Learning

7. Regression and Classification Explained

8. Data Preprocessing with Pandas

9. Feature Engineering and Scaling

10. Model Evaluation and Accuracy

11. Introduction to TensorFlow

12. Introduction to PyTorch

13. Building Your First Neural Network in PyTorch

14. CNNs Explained Visually

15. RNNs and LSTMs Made Simple

16. Transfer Learning Concepts

17. AI in Agriculture: Overview

18. Using ML for Crop Disease Detection

19. Precision Farming with AI

20. The Future of AI & Deep Learning

21. AI in Livestock Monitoring

22. AI for Climate Prediction

23. IoT and Smart Agriculture

24. Drones in Agriculture

25. AI for Soil Health Monitoring

26. Deep Learning for Weed Detection

27. Computer Vision for Agriculture

28. AI for Irrigation Management

29. Data Collection Techniques for Agri-ML

30. AI-Based Yield Prediction

31. Satellite Imaging and AI for Farms

32. Deep Reinforcement Learning Basics

33. Object Detection with YOLO

34. AI Chatbots for Agriculture

35. Building AI APIs with Flask

36. Deploying AI Models

37. Edge AI for Smart Farms

38. AI for Greenhouse Automation

39. Robotics in Agriculture

40. Building Your AI Career in Agriculture

About the Instructor: Delstarford Isaiah

A passionate innovator dedicated to empowering students at the intersection of AI and Agriculture.

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