Ready to take your AI and machine learning skills to the next level? This comprehensive learning path equips you with the knowledge and tools to thrive in the field. Learn how to harness data, build and optimize models, and manage AI operations. Explore deep learning, reinforcement learning, and GANs. Gain the expertise to create impactful AI solutions and drive innovation. Start your journey to becoming an AI expert today.

Gain hands-on training with generative models.
Refine your skills in deep learning and neural networks.
Explore the developing fields of MLOps and responsible AI.
Monitor ML operations for continuous improvement.

Syllabus

Courses under this program:
Course 1: Applied Machine Learning: Ensemble Learning (2022)
-Explore how to make powerful, accurate predictions with ensemble learners, one of the most common classes of machine learning algorithms.

Course 2: Deep Learning: Model Optimization and Tuning
-Learn about various optimization and tuning options available for deep learning models and use them to improve models.

Course 3: Reinforcement Learning Foundations
-Learn the basics of reinforcement learning (RL), including the terminology, the kinds of problems you can solve with RL, and the different methods for solving those problems.

Course 4: Introduction to Attention-Based Neural Networks
-Learn what attention-based models are, how they work, and what they can do for recurrent neural networks.

Course 5: Training Neural Networks in Python
-Take a deep dive into the inner workings of neural networks by learning how to create one from scratch in Python.

Course 6: Introduction to Generative Adversarial Networks (GANs)
-Gain a better understanding of Generative Adversarial Networks (GANs), how they are created, how they train, and how they are able to create new media.

Course 7: AI Workshop: Hands-on with GANs Using Dense Neural Networks
-Learn how to build and train generative adversarial networks (GANs) using dense neural networks in this interactive, workshop-style coding course.

Course 8: AI Workshop: Hands-on with GANs with Deep Convolutional Networks
-Learn how to build and train deep convolutional generative adversarial networks (GANs) in this interactive, workshop-style coding course.

Course 9: Exploring AIOps
-Discover how the exciting new world of AIOps is changing everyday IT workflows and practices around the world.

Course 10: MLOps Essentials: Model Development and Integration
-Get started with MLOps Concepts for Model Development and Integration, to organize machine learning (ML) development and deliver scalable and reliable ML products.

Course 11: MLOps Essentials: Model Deployment and Monitoring
-Learn how to deploy and monitor machine learning models to deliver scalable, reliable ML products and services.

Course 12: MLOps Essentials: Monitoring Model Drift and Bias
-Learn about the growing field of MLOps and the modeling techniques used to monitor model drift and bias.

Course 13: UX for AI: Design Practices for AI Developers
-Discover new approaches to building better UX for AI applications using the Microsoft Copilot stack.

Course 14: Foundations of Responsible AI
-Learn about the practices needed to perform fairness testing and implement responsible AI systems.

Course 15: Responsible AI: Principles and Practical Applications
-Learn how AI is being used today and how to ensure its responsible usage into the future.

Course 16: Introduction to AI Governance
-Explore core concepts and practical strategies to effectively implement and manage AI governance.