Curated learning path for AI for Agriculture. Build practical skills through expert-selected courses.
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Varies by topic; basics usually sufficient
Some programming experience helpful
Follow these courses in order to complete the learning path. Click on any course to enroll.
This course covers the application of AI and computer vision in agriculture. It includes modules on emerging technologies in agriculture, crop-related applications like disease and nutrient deficiency detection, weather prediction, and livestock monitoring. The course provides over 50 hours of content, including code and datasets, and is beginner-friendly.
This course reviews the mechanisms behind anthropogenic climate change and its impact on global temperatures and weather patterns. It includes two case studies: one using time series analysis for wind power forecasting and another using computer vision for biodiversity monitoring, demonstrating how AI techniques can help mitigate and adapt to climate change.
This introductory course explores the role of AI in transforming farming practices, including precision agriculture and sustainable crop management. Key topics include AI for precision agriculture, crop and soil management, and agricultural robotics and automation. No prior experience is required.
Precision Agriculture with AI and Machine Learning
Are you ready to master Deep Learning skills?Deep Learning is a technology using which we can solve highly computational problems such as Image Processing, Image Classification, Image Segmentation, Image tagging, sound classification, video analysis, etc.Deep Learning is becoming a buzzword these days, and If you want to learn Deep Learning then It is very important for you that you should have a proper plan regarding that.Before Learning Deep Learning you must have learned Machine Learning and must possess good knowledge of the Python programming language.If you want to build super-powerful applications in Deep Learning. Then, you are at the right place.This course will provide you with in-depth knowledge on a very hot topic i.e., Deep Learning.The purpose of this course is to provide you with knowledge of key aspects of Deep Learning without any intimidating mathematics and in a practical, easy, and fun way. The course provides students with practical hands-on experience using real-world datasets.This course will cover the following topics:-1. Deep Learning (DL).2. Artificial Neural Network (ANNs).3. Convolutional Neural Network (CNNs).4. Recurrent Neural Network. (RCN)5. Learn to Implement the LSTMs.This course will take you through the basics to an advanced level in all the mentioned four topics.After taking this course, you will be confident enough to work independently on any projects on these topics.There are lots and lots of exercises for you to practice In this Deep Learning Course and also a 5 Bonus Deep Learning Project "Stock Market Prediction", "Fruits Identification System", "Face Expression Recognizer", "Detecting Pneumonia from Chest X-rays", and "Optimizing Crop Production".In this Optimizing Crop Production, you will learn about Precision Farming using Data Science T
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Curated learning path for AI for Agriculture. Build practical skills through expert-selected courses.
You'll work through Understand core concepts and foundations; Build your first projects with guided tutorials; Gain confidence with hands-on exercises; Master fundamental concepts and terminology; Apply theoretical knowledge to practical projects; Build portfolio-worthy projects demonstrating your skills.
About 32 hours of study across 5 courses — and you can go at your own pace.
It's pitched at beginner level — a solid starting point if you're new to the topic.
5 curated courses, sequenced from foundational to advanced.
Around $40 total if you buy every course — but many include free audit options.
Enroll in this path to track your progress and stay motivated.