Microsoft

Microsoft Generative AI Engineering Professional Certificate

Microsoft

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.

 Microsoft

Instructor: Microsoft

7,597 already enrolled

Included with Coursera Plus

Earn a career credential that demonstrates your expertise

from 17 reviews of courses in this program

Intermediate level

Recommended experience

3 months to complete
at 8 hours a week
Flexible schedule
Learn at your own pace
Earn a career credential that demonstrates your expertise

from 17 reviews of courses in this program

Intermediate level

Recommended experience

3 months to complete
at 8 hours a week
Flexible schedule
Learn at your own pace

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.

Details to know

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Taught in English
Recently updated!

January 2026

91% of learners achieved a positive career outcome

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Advance your career with in-demand skills

  • Receive professional-level training from Microsoft
  • Demonstrate your technical proficiency
  • Earn an employer-recognized certificate from Microsoft

Professional Certificate - 5 course series

Getting started with generative AI in Azure

Getting started with generative AI in Azure

Course 1, 17 hours

What you'll learn

Skills you'll gain

Category: Generative AI
Category: Microsoft Azure
Category: Application Design
Category: Prompt Engineering
Category: Fine-tuning
Category: Machine Learning
Category: Responsible AI
Category: Large Language Modeling
Category: LLM Application
Category: Software Documentation
Category: Data Ethics
Category: Application Development
Category: Artificial Intelligence
Category: AI Security
Category: Generative Model Architectures
Category: AI Integrations
Category: Deep Learning
Category: AI literacy
Category: Back-End Web Development
Category: Artificial Intelligence and Machine Learning (AI/ML)
Core generative models and techniques

Core generative models and techniques

Course 2, 21 hours

What you'll learn

Skills you'll gain

Category: Generative Model Architectures
Category: Prototyping
Category: Model Evaluation
Category: Generative Adversarial Networks (GANs)
Category: Time Series Analysis and Forecasting
Category: MLOps (Machine Learning Operations)
Category: Model Training
Category: Generative AI
Category: Forecasting
Category: Tensorflow
Category: Image Analysis
Category: Deep Learning
Category: Microsoft Azure
Category: Model Deployment
Category: PyTorch (Machine Learning Library)
Working with large language models using Azure

Working with large language models using Azure

Course 3, 21 hours

What you'll learn

  • Apply prompt engineering techniques to improve Large Language Model responses

  • Build Retrieval-Augmented Generation (RAG) pipelines using Azure services

  • Fine-tune and customize LLMs for domain-specific AI applications 

  • Develop and deploy generative AI applications using Azure AI Foundry

Skills you'll gain

Category: Application Performance Management
Category: Semantic Web
Category: Fine-tuning
Category: Cloud Deployment
Category: AI Workflows
Category: ChatGPT
Category: Generative Model Architectures
Multimodal and cross-modal AI integrations

Multimodal and cross-modal AI integrations

Course 4, 20 hours

What you'll learn

Skills you'll gain

Category: AI Integrations
Category: AI Orchestration
Category: Prompt Engineering
Category: Microsoft Azure
Category: Generative AI
Category: Computer Vision
Category: AI Workflows
Category: Artificial Intelligence
Category: Prompt Patterns
Category: Model Optimization
Category: Image Analysis
Category: Multimodal Prompts
Category: OpenAI API
MLOps and responsible AI practices

MLOps and responsible AI practices

Course 5, 22 hours

What you'll learn

Skills you'll gain

Category: MLOps (Machine Learning Operations)
Category: Responsible AI
Category: CI/CD
Category: Version Control
Category: Azure DevOps
Category: Git (Version Control System)
Category: Microsoft Azure
Category: Azure DevOps Pipelines
Category: Automation
Category: Model Evaluation
Category: Model Training
Category: AI Workflows
Category: Continuous Integration
Category: Application Performance Management
Category: Model Deployment
Category: Generative AI
Category: Data Ethics
Category: Continuous Monitoring

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Instructor

 Microsoft
326 Courses2,555,560 learners

Offered by

Microsoft

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