Level up your machine learning skills by learning how to build perceptrons: the foundations of neural networks.

Machine Learning/AI Engineers build end-to-end ML applications and power many of the apps we use every day. They work in Python, Git, & ML.

In this path, you'll learn to design and implement a new AI paradigm called Machine Teaching for Autonomous AI. Machine Teaching uses the knowledge of subject matter experts to teach AI. Machine Teaching integrates known control methods, for stable control, Machine Learning, for advance perception, and Deep Reinforcement Learning, for learning strategies and human-like decision making. The deployment in industrial processes without disruption and providing real business value is considered from its design. Machine Teaching for Autonomous AI stores expert operators' skill set, and it helps companies achieve new levels of optimization for competitiveness, profitability, and sustainability. The hands-on development of Autonomous solutions will be taught using the Microsoft Project Bonsai Platform, a low-code platform where Machine Teaching is used to the implementation, training, and validation of Bonsai brains.

Maintain the performance, cost, and reliability of your Azure AI Search solutions.

Make cutting-edge games! Mine a unique world using NavMesh artificial intelligence. Make a 3D pathfinding game with C#.

Learn how to use Azure AI Personalizer to empower your apps with smarter decision making through improved recommendations.

Developing Generative Adversarial Networks (GANs) using PyTorch

Build your own neural network from scratch in Python, focusing on fundamental concepts, architecture, and practical implementation techniques.

In this course, you will learn how to create and manage an orchestration process on IBM Robotic Process Automation control center.

This course is for developers familiar with developing RPA scripts with IBM RPA platform and who want to improve their knowledge by learning about manipulating emails.

Learn to craft effective prompts for ChatGPT, focusing on maximizing the model's performance and output quality.

Unlock the Power of Machine Learning Algorithms and Build Real-World Applications