AI Adoption Workshop for Technical Users (AI-AITU)
This Instructor Led Workshop will provide technical teams an overview of AI and will by the workshops end have everyone creating AI solutions.
Course Information
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Certification:
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Check out our full list of training locations and learning formats. Please note that the location you choose may be an Established HD-ILT location with a virtual live instructor.
Train face-to-face with the live instructor.
Access to on-demand training content anytime, anywhere.
Attend the live class from the comfort of your home or office.
Interact with a live, remote instructor from a specialized, HD-equipped classroom near you. An SLI sales rep will confirm location availability prior to registration confirmation.
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Prerequisites:
Target Audience:
Course Objectives:
Course Outline:
Day 1: Introduction to AI and Azure AI Fundamentals
- Welcome and Workshop Overview
- Introduction to the workshop objectives and agenda
- Importance of AI in modern technology
- Overview of Microsoft Azure AI services
- Understanding AI Workloads and Considerations
- Definition and types of AI workloads
- Ethical considerations and responsible AI
- Use cases and industry applications
- Fundamental Principles of Machine Learning on Azure
- Introduction to machine learning concepts
- Azure Machine Learning services
- Hands-on lab: Creating a simple machine learning model
- Computer Vision Workloads on Azure
- Overview of computer vision and its applications
- Azure Computer Vision services
- Hands-on lab: Building a computer vision solution
Day 2: Deep Dive into AI Workloads
- Natural Language Processing (NLP) Workloads on Azure
- Introduction to NLP and its use cases
- Azure Cognitive Services for language
- Hands-on lab: Implementing an NLP solution
- Conversational AI Workloads on Azure
- Basics of conversational AI and chatbots
- Azure Bot Services and Language Understanding (LUIS)
- Hands-on lab: Creating a chatbot
- AI Solution Design Principles
- Overview of AI solution design principles
- Planning and scoping AI projects
- Case studies and best practices
Day 3: Building and Integrating AI Solutions
- Building AI-Infused Applications
- Integrating AI services into applications
- Using REST-based APIs for AI solutions
- Hands-on lab: Developing an AI-infused application
- Azure AI Search and Knowledge Mining
- Introduction to Azure AI Search
- Implementing knowledge mining solutions
- Hands-on lab: Creating a knowledge mining solution
- Generative AI and Azure OpenAI
- Overview of generative AI and its applications
- Using Azure OpenAI for generative AI solutions
- Hands-on lab: Building a generative AI application
Day 4: Deploying, Managing, and Scaling AI Solutions
- Deploying AI Solutions
- Best practices for deploying AI models
- Monitoring and maintaining AI solutions
- Hands-on lab: Deploying an AI solution on Azure
- Scaling AI Solutions
- Strategies for scaling AI projects
- Performance optimization and cost management
- Case studies of scalable AI solutions
- Workshop Wrap-Up and Next Steps
- Summary of key learnings
- Q&A session
- Resources for further learning
- Planning next steps for AI adoption in your organization
