Generative AI OpenAI
for Tech Managers using Azure
Syllabus
What You Would Be Able to Achieve at the End of This Training
● Understand the core concepts and capabilities of Generative AI
● Apply Generative AI solutions using Azure OpenAI in your organization
● Integrate and manage AI tools within your existing tech infrastructure
● Drive innovation and enhance productivity through AI-enabled solutions
● Develop strategic plans for AI adoption and scaling within your team
Course Audience
- TechManagers
- Project Managers
- IT Leaders
- Technical Team Leads
Duration
- 3 Days (8 hours per day)
Prerequisite
- Basic understanding of cloud computing, preferably Microsoft Azure
- Familiarity with AI and machine learning concepts
Course Outline Day 1: Understanding Generative AI and Azure OpenAI
- IntroductiontoGenerativeAI
- Overview of AI and Machine
- Learning Deep Learning Key Models
- Descriptive Models
- Generative Models
- Generative AI & its capabilities
- Specifics and scope of Generative AI
- Current trends and applications in the industry
- Generative AI Models – Text & Image
- Introduction to Large Language Models
- What are Large Language Models?
- How to choose right Large Language Models
- How LLM Works?
- LLMs vs Foundation Models vs Fine Tuned Models
- LLM Application and Use Cases
- How to customize LLMs as per the Requirement?
- OpenAIServicesOverview
- Introduction to Azure and its AI capabilities
- Detailed exploration of Azure OpenAI services
- Azure OpenAI Studio for Prompts
- Various Azure OpenAI Models
- How to integrate Azure OpenAI within Projects?
Day 2: Prompt Engineering and RAGs implementation
- PromptEngineering
- What is a Prompt?
- What does Prompt Structure look like?
- Introduction to Prompt Engineering
- What are the key elements of Prompts?
- Introduction to ChatGPT
- Key Tips & Techniques for Prompt Designs
- Azure Open AI Studio UI for Prompt Engineering
- WorkingwithRAGsonAzureOpenAI
- What is a RAG?
- Key Benefits of RAGs
- RAG vs Fine Tuning
- How to implement RAGs on Azure OpenAI?
- GenerativeAIProductDevelopment
- Building AI First Products
- Role of Generative AI in Project Management
- Generative AI Project Life Cycle
- Generative AI Vendor Landscape
- How to Evaluate Generative AI Projects?
Day 3: Managing and Scaling AI Solutions
- ManagingAIProjects
- Strategies for effective project management with Generative AI
- Understanding various Roles & Responsibilities
- Project Scoping and Requirement Gathering
- Effective Communication & Collaboration
- Monitoring and evaluating AI project performance
- Scaling and Future-proofing AI within the Organization
- Scaling AI solutions across the business
- Preparing for future AI trends and technologies
- Introduction to AIOps in Azure
- Security and Ethics in AI Implementation
- AI Risks and How to Mitigate them?
- Ensuring data privacy and security when using AI
- Ethical considerations and maintaining AI fairness
- Responsible AI Landscape
- Understanding Biases
- Generative AI Models Evaluation Metrics