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Explore the powerful fusion of Artificial Intelligence, Machine Learning, and Wildlife Conservation through this advanced hands-on program. Learn modern techniques like camera trap analysis, satellite remote sensing, species identification, bioacoustics, habitat mapping, and predictive ecological modeling using tools such as Python, R, and Google Earth Engine. This course opens exciting opportunities in Conservation AI, Ecological Data Science, GIS & Remote Sensing, biodiversity research, and environmental sustainability, helping participants build future-ready skills for solving real-world conservation challenges. Foundation Level: Foundations & Processing (Beginner) This level focuses on data acquisition, setting up cloud environments, and deploying foundational machine learning tools for ecological data. Lecture 1: Foundations of AI, ML & Hybrid Ecological Models (Theory) Lecture 2: Data Engineering & Cloud Platforms (Hands-On 1) Lecture 3: Earth Observation & Passive Acoustic Monitoring (Theory) Lecture 4: Computer Vision I – Automated Image Tagging (Hands-On 2) Lecture 5: Predictive Modeling I – Species Distribution Modeling (Hands-On 3) Advanced Level: Complex Analytics & Integration (Advanced) This level dives into advanced computer vision, spatial machine learning, and integrating AI outputs with rigorous Bayesian frameworks. Lecture 6: Computer Vision II – Identification & Behavior (Hands-On 4) Lecture 7: Cloud-Based Machine Learning in GEE (Hands-On 5) Lecture 8: Predictive Modeling II – Population Estimation (Hands-On 6) Lecture 9: Movement Ecology & Threat Detection (Hands-On 7) Lecture 10: Scaling Conservation AI & Final Presentations (Theory/Interactive)
You can also join this program via the mobile app. Go to the app