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.
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Gain hands-on training with generative models.
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Refine your skills in deep learning and neural networks.
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Explore the developing fields of MLOps and responsible AI.
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Monitor ML operations for continuous improvement.
Courses
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1
Applied Machine Learning: Ensemble Learning1h 28mApplied Machine Learning: Ensemble Learning
By: Matt Harrison
Learn to use ensemble techniques like bagging, boosting, and stacking to improve your machine learning models.
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2
Deep Learning: Model Optimization and Tuning (2022)54mDeep Learning: Model Optimization and Tuning (2022)
By: Kumaran Ponnambalam
Learn about various optimization and tuning options available for deep learning models and use them to improve models.
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3
Reinforcement Learning Foundations44mReinforcement Learning Foundations
By: Khaulat Abdulhakeem
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.
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4
Introduction to Attention-Based Neural Networks2h 11mIntroduction to Attention-Based Neural Networks
By: Janani Ravi
Learn what attention-based models are, how they work, and what they can do for recurrent neural networks.
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5
Training Neural Networks in Python2h 7mTraining Neural Networks in Python
By: Eduardo Corpeño
Take a deep dive into the inner workings of neural networks by learning how to create one from scratch in Python.
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6
Introduction to Generative Adversarial Networks (GANs)1h 1mIntroduction to Generative Adversarial Networks (GANs)
By: Gwendolyn Stripling
Gain a practical understanding of Generative Adversarial Networks (GANs) and unlock the exciting possibilities of these powerful generative modeling technologies.
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7
AI Workshop: Hands-on with GANs Using Dense Neural Networks (2023)1h 24mAI Workshop: Hands-on with GANs Using Dense Neural Networks (2023)
By: Janani Ravi
Learn how to build and train generative adversarial networks (GANs) using dense neural networks in this interactive, workshop-style coding course.
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8
AI Workshop: Hands-on with GANs with Deep Convolutional Networks1h 36mAI Workshop: Hands-on with GANs with Deep Convolutional Networks
By: Janani Ravi
Learn how to build and train deep convolutional generative adversarial networks (GANs) in this interactive, workshop-style coding course.
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9
Exploring AIOps18mExploring AIOps
By: Morten Rand-Hendriksen
Discover how the exciting new world of AIOps is changing everyday IT workflows and practices around the world.
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10
MLOps Essentials: Model Development and Integration1h 36mMLOps Essentials: Model Development and Integration
By: Kumaran Ponnambalam
Get started with MLOps Concepts for Model Development and Integration, to organize machine learning (ML) development and deliver scalable and reliable ML products.
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11
MLOps Essentials: Model Deployment and Monitoring1h 24mMLOps Essentials: Model Deployment and Monitoring
By: Kumaran Ponnambalam
Learn how to deploy and monitor machine learning models to deliver scalable, reliable ML products and services.
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12
MLOps Essentials: Monitoring Model Drift and Bias1h 5mMLOps Essentials: Monitoring Model Drift and Bias
By: Kumaran Ponnambalam
Learn about the growing field of MLOps and the modeling techniques used to monitor model drift and bias.
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13
UX for AI: Design Practices for AI Developers59mUX for AI: Design Practices for AI Developers
By: John Maeda
Discover new approaches to building better UX for AI applications using the Microsoft Copilot stack.
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14
Foundations of Responsible AI1h 8mFoundations of Responsible AI
By: Vilas Dhar
Explore a practical framework for implementing AI practices in a way that bridges the gap between high-level AI ethics principles and day-to-day technical decisions.
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15
Responsible AI: Principles and Practical Applications1h 6mResponsible AI: Principles and Practical Applications
By: Jill Finlayson
Learn how AI is being used today and how to ensure its responsible usage into the future.
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16
Introduction to AI Governance59mIntroduction to AI Governance
By: Vidhi Chugh
Explore core concepts and practical strategies to effectively implement and manage AI governance.
Instructors
Matt Harrison
Kumaran Ponnambalam
AI / ML Leader & Author
Khaulat Abdulhakeem
Career Strategy for Multipotentialites • Join an upcoming Masterclass ↓
Janani Ravi
Co-Founder at Loonycorn
Eduardo Corpeño
Electrical & Computer Engineer, Creator of the world-renowned Brainfuino platform.
Gwendolyn Stripling
Generative AI | Agentic AI | AI Security | Tech Speaker | Author |
Morten Rand-Hendriksen
Principal Instructor @ LinkedIn | AI Demythifier | Tech Educator | System Critic | TEDx Speaker | Neurodivergent System Thinker | Dad
John Maeda
AI @ MSFT / Laws of Simplicity + How To Speak Machine / LinkedIn Top US Influencer
Vilas Dhar
President, Patrick J. McGovern Foundation ($1.5B) | Global Authority on AI, Governance & Social Impact | Board Director | Shaping Leadership in the Digital Age
Jill Finlayson
Brandie Nonnecke
Senior Director of Policy, Americans for Responsible Innovation
Tsu-Jae Liu
President, National Academy of Engineering
Vidhi Chugh
Agentic AI Business Leader | Microsoft MVP | AI Educator | Author | World’s Top 200 Innovators | AI Patent holder | Chief AI Officer