Coursera – Microsoft Generative AI Engineering Professional Certificate

Empower innovation using generative AI engineering. Build, fine-tune, and deploy generative AI models using Microsoft tools and platforms.

What you’ll learn
+ Grasp core generative AI models and their applications, including GANs, diffusion models, and LLMs, leveraging Azure AI Foundry.
+ Implement and fine-tune Large Language Models (LLMs) and build generative applications using Azure OpenAI Services.
+ Integrate multimodal and cross-modal AI components within applications using Azure AI Vision and other Azure AI Services.
+ Apply MLOps principles with Azure ML for lifecycle management and implement responsible AI practices.

Skills you’ll gain
• Data Ethics
• MLOps (Machine Learning Operations)
• Generative Model Architectures
• AI Workflows
• Azure DevOps Pipelines
• Responsible AI
• Prompt Engineering
• AI Enablement
• AI Orchestration
• PyTorch (Machine Learning Library)
• ChatGPT
• Multimodal Prompts
• Microsoft Azure
• Python Programming
• Artificial Intelligence and Machine Learning (AI/ML)
• Model Deployment
• AI Security
• Generative Adversarial Networks (GANs)
• Generative AI
• Azure DevOps

This certificate is designed for developers with a foundational understanding of Azure, aiming to deepen their expertise in AI-powered application development, specifically customizing generative AI models within the Microsoft ecosystem.

This specialization empowers you to build, fine-tune, and deploy generative AI models using Microsoft tools such as Azure AI Foundry, Azure Machine Learning, and Azure OpenAI Service. You’ll gain hands-on experience with models like GANs, transformer models, diffusion models, and LLMs, integrating them with Azure’s cloud infrastructure for scalable solutions.

By the end of this specialization, you will be able to

Understand core generative AI models and their applications.

Leverage Azure AI Foundry for developing scalable generative AI solutions.

Implement and fine-tune LLMs using Azure OpenAI services.

Integrate multimodal learning and cross-modal techniques in AI workflows.

Optimize AI models for performance, efficiency, and cost within Azure.

Explore MLOps practices for lifecycle management of AI models.

Address ethical considerations and implement responsible AI practices.

This program is ideal for developers looking to customize generative AI models and build AI-powered applications within the Microsoft ecosystem. While an understanding of Microsoft Azure and generative AI models is beneficial, the program is structured to provide a comprehensive learning experience, preparing you for the evolving demands of the AI industry.

Applied Learning Project

Learners will complete four hands-on projects and one final project that they can use for their personal portfolios. Each project can be completed independently of the others, as each set of skills is unique to each individual course. First, you’ll create a basic AI text generation app. Next, you’ll fine-tune a personalized simple generative model and document the process, including model choice and application. After, you’ll build a text generation and translation application utilizing Azure OpenAI’s GPT models. Then, you’ll develop an AI application that incorporates text-to-image generation using Azure AI Services. Finally, you’ll integrate an end-to-end MLOps pipeline leveraging Azure tools and previously built/tuned models, incorporating responsible AI practices to track and manage an AI model’s lifecycle. These projects provide concrete, real-world work samples to showcase your skills to potential employers.