Azure OpenAI Boot Camp for Developers: Platform, Generative AI, Models, Prompt Engineering|System Source

Immerse yourself in the transformative world of AI with the Azure OpenAI Boot Camp for Developers. This intensive, two-day program, designed for developers new to Azure OpenAI and OpenAI, offers an exceptional opportunity to harness AI's capabilities using the leading-edge Azure platform. This program is structured to give you a strong foundational understanding of AI and its diverse applications, from language translation to prediction modeling.

Guided by our Microsoft Azure-certified AI expert instructor, you’ll gain modern hands-on skills using cutting-edge tools to implement innovative AI solutions at your workplace, resulting in smarter applications and improved operational efficiency. Throughout the course you’ll explore five main themes: OpenAI and Azure OpenAI platforms, Generative AI, Azure OpenAI's capabilities, exploration of AI models, and prompt engineering. You’ll gain core skills and gain hands-on practice with major AI models including GPT-4, GPT-3, DALL-E, Codex, and Embedding, learning how to apply them on the job or in your projects in a practical way. You'll also become adept at prompt engineering, a skill that is essential to the successful deployment and performance of AI tasks.

You'll engage with a wide array of subjects, from experimenting with Azure OpenAI's features to fine-tuning GPT models, implementing embeddings and indexing, and establishing content filters. In addition, you'll learn about Azure OpenAI's workload management, access procedures, and responsible AI practices. This ensures that all AI applications developed are not only high-performing and efficient but also ethically sound and compliant with regulations.

At the end of this immersive course, you will have gained a deep understanding of the distinctive features of both OpenAI and Azure OpenAI platforms, developed advanced skills in prompt engineering and fine-tuning AI models, and gained hands-on experience with the applications of embeddings and indexing. Moreover, you will have the practical knowledge to apply these skills to improve your organization's AI capabilities, opening the door to a new level of innovative solutions, and preparing you for the AI-focused world of tomorrow.


06/03/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led	(click to enroll)
07/22/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led	(click to enroll)
09/16/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led	(click to enroll)
10/28/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led	(click to enroll)
12/02/24 - TTV - Virtual-Instructor Led - Virtual-Instructor Led	(click to enroll)

This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you’ll:

Gain a solid comprehension of the OpenAI and Azure OpenAI platforms, their unique features, and their capabilities.
Develop an in-depth understanding of prominent AI models such as GPT-4, GPT-3, DALL-E, Codex, and Embedding, and their potential applications.
Learn to manipulate the output of AI models effectively using the principles of prompt engineering.
Gain the ability to fine-tune AI models efficiently, enhancing their performance for specific tasks.
Obtain practical knowledge in implementing embeddings and indexing, integral parts of machine learning tasks.
Understand Azure OpenAI's responsible AI practices, access policies, and security measures, fostering ethical and compliant AI applications within your organization.
Grasp the principles and best practices of creating a private Business GPT, a critical skill in leveraging AI technology for business-specific applications.
Develop proficiency in setting up and configuring content filters within Azure OpenAI Studio, enhancing the relevance and appropriateness of AI output.

If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals.

Viewing outline for:

Please note that this topics, agenda and labs are subject to change to cover the most recent technical trends or tools, and may adjust during live delivery based on audience skill level, interests and participation.

Day 1

Introduction and Overview

Introduction to OpenAI and Azure OpenAI
Core competencies and objectives of OpenAI and Azure OpenAI
Distinctive features of both platforms
Comparative evaluation of OpenAI and Azure OpenAI
Hands-on Lab: Comparison of OpenAI and Azure OpenAI
Discussion and debrief

Unfolding Generative AI

Definition of generative AI
Evolution and historical context of generative AI
Use-cases of generative AI in various industries
Overview of generative AI algorithms and frameworks
Hands-on Lab: Investigating real-world applications of generative AI
Review and analysis of findings

Deep Dive into Azure OpenAI

Detailed overview of Azure OpenAI
In-depth analysis of Azure OpenAI's architecture and infrastructure
Key features and benefits of Azure OpenAI
Overview of Azure OpenAI applications and success stories
Hands-on Lab: Exploring Azure OpenAI capabilities through practical exercises
Discussion on insights and challenges

AI Models Exploration

Introduction to GPT-4, GPT-3, DALL-E, Codex, and Embedding
Overview of model development and evolution
Comparison of features and use-cases of each model
Exploration of the potential future advancements and applications of these models
Activity: Practical demonstration of different model uses
Analysis and review

The Art of Prompt Engineering: The Basics

Introduction to the concept of prompt engineering
Understanding the core principles of prompt engineering
Importance and role of prompt engineering in AI model performance
Analysis of common challenges and solutions in prompt engineering
Hands-on Lab: Basic of prompt engineering tasks
Discuss and review findings and strategies

Day 2

Mastering Prompt Engineering: Advanced Topics

Deep dive into advanced topics like space efficiency, few-shot learning, and non-chat scenarios
Exploration of key strategies like clear instructions, prime the output, and clear syntax
Review of real-world examples of advanced prompt engineering
Analysis of common mistakes and pitfalls in advanced prompt engineering
Hands-on Lab: Advanced prompt engineering activities
Review outcomes and insights

Azure OpenAI Workloads and Access

Overview of different Azure OpenAI workloads
Analysis of workload performance and scalability
Procedures for accessing the Azure OpenAI Service
Review of Azure OpenAI Service's reliability and maintenance
Hands-on Lab: Accessing and using Azure OpenAI
Discuss challenges and solutions

Fine-Tuning Mastery: GPT Model

Introduction to the concept of fine-tuning a GPT model
Understanding the mathematical principles behind fine-tuning
Steps and tips for efficient fine-tuning
Analysis of common challenges in fine-tuning and potential solutions
Hands-on Lab: Exercise to fine-tune a GPT model
Review outcomes and insights

Essentials of Embeddings and Indexing

Understanding embeddings and indexing
Introduction to the mathematical theories behind embeddings and indexing
Importance and real-world applications of embeddings and indexing
Discussion on the challenges and potential advancements in embeddings and indexing
Hands-on Lab: Practical activity on implementing embeddings and indexing
Discuss the application and challenges

Content Filtering Made Simple

Introduction to content filtering in Azure OpenAI Studio
Understanding the mathematical models behind content filtering
Key best practices for effective content filtering
Discussion on ethical and legal considerations in content filtering
Hands-on Lab: Set up and configure content filters
Discuss and review outcomes

Building a Private Business GPT

Concepts of LangChain and Llama Index
Introduction to the principles and best practices in GPT business application
Guidelines for creating a private business GPT
Discussion on the challenges and future of business GPTs
Hands-on Lab: Create a private business GPT
Discuss and review project

Ensuring Security and Effective Monitoring

Introduction to Azure Tooling for security
Overview of the principles of secure AI deployment
Best practices for monitoring Azure OpenAI applications
Discuss future challenges and advancements in AI security and monitoring
Hands-on Lab: Practical activities on security setup and monitoring
Discuss outcomes and insights

Azure OpenAI Responsible AI Practices and Limited Access Policies

Overview of Azure OpenAI's responsible AI practices
Understanding the ethical considerations in AI application
Understanding Azure OpenAI's limited access policies
Discussion on the legal framework and potential challenges in AI access policies
Hands-on Lab: Implementing responsible AI practices
Discuss outcomes, analysis and insights

Capstone Project

FINAL LAB: Comprehensive project that integrates learning from all modules
Final project review and feedback session

Wrap-up, Q&A

To ensure a smooth learning experience and maximize the benefits of attending this course, you should have the following prerequisite skills:

A basic understanding of artificial intelligence and its applications would help to quickly grasp the course content.
A working knowledge of Python basics helpful but not required. Lab code will be supplied so you can simply run it for labs that require it.
Basic Understanding of Data Structures
Prior exposure to any cloud services platform (such as Azure, AWS, or Google Cloud) would be beneficial.

This Intermediate level course is geared for experienced technical professionals eager to deepen their understanding of AI and apply it in their work. Roles that would particularly benefit from attending include data scientists, machine learning engineers, AI researchers, and IT managers involved in AI strategy and deployment. This course is also well-suited for advanced tech enthusiasts who wish to get a comprehensive, hands-on introduction to the applications of OpenAI and Azure OpenAI technologies.

Next Steps / Follow-on Courses: We offer a wide variety of follow-on courses and learning paths for Generative AI, AI for Business, GPT, Applied AI, Azure OpenAI, Google BARD, AI for developers, testers, data analytics, machine learning, deep learning, programming, intelligent automation and many other related topics. Please see our catalog for the current AI & Machine Learning Courses, Learning Journeys & Skills Roadmaps, list courses and programs.

Azure OpenAI Boot Camp for Developers: Platform, Generative AI, Models, Prompt Engineering

Course Overview

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Outline

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