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Python ProgrammingAI-102: Designing and Implementing a Microsoft Azure AI Solution
Learn new skills and discover the power of Microsoft Azure with step-by-step guidance.
Demand for Cloud Skills
Learn core Azure services and cloud concepts for career success. Start from the basics and progress to cloud expertise.
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Understanding Azure allows you to leverage technology to stay ahead of competitors and adapt to market changes.
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Build a solid foundation in cloud computing with Azure and lead in an increasingly digital business landscape.
- Instructor-led
- Official Courseware
- Flexible Schedule
- Guaranteed To Run
Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure AI Services, Azure AI Search, and Azure OpenAI.
The course will use C# or Python as the programming language. Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They should familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure.
- Course : Designing and Implementing an Azure AI Solution
- Level : Intermediate
- Type : Instructor led Live online or Classroom
- Length : 4 days
- Labs : Included
- Practice Test : Included
- AI engineers and developers working on AI solutions
- Data scientists and ML engineers
- Cloud solution architects designing AI powered applications
- IT professionals
- Anyone preparing for the Microsoft Certified Azure AI Engineer Associate certification
- Basic knowledge of Microsoft Azure services
- Experience with programming languages like Python or C#
- Developing AI Solutions with Azure Cognitive Services
- Implementing Natural Language Processing
- Building text analytics, language understanding
- Creating Conversational AI Solutions Developing chatbots
- Building Computer Vision Solutions Image classification
- Facial recognition, and optical character recognition
- Working with Azure Machine Learning
- Implementing Responsible AI Practices
- Security considerations in AI solutions
Instructor-led Virtual online live Training.
- Weekend Classes
- Evening Classes
- Weekdays Classes
Course Outline
Module 1: Plan and prepare to develop AI solutions on Azure
- Fundamental AI Concepts
- Fundamentals of machine learning
- Fundamentals of Azure AI services
- Azure AI services
- Azure AI Foundry
- Developer tools and SDKs
- Responsible AI
Module 2: Create and consume Azure AI services
- Provision an Azure AI services resource
- Identify endpoints and keys
- Use a REST API
- Use an SDK
Module 3: Secure Azure AI services
- Consider authentication
- Implement network security
Module 4: Monitor Azure AI services
- Monitor cost
- Create alerts
- View metrics
- Manage diagnostic logging
Module 5: Deploy Azure AI services in containers
- Understand containers
- Use Azure AI services containers
Module 6: Use AI responsibly with Azure AI Content Safety
- What is Content Safety
- How does Azure AI Content Safety work?
- When to use Azure AI Content Safety
Module 7: Analyze images
- Provision an Azure AI Vision resource
- Analyze an image
- Generate a smart-cropped thumbnail and remove background
Module 8: Image classification with custom Azure AI Vision models
- Understand custom model types
- Create a custom project
- Label and train a custom model
Module 9: Classify images
- Provision Azure resources for Azure AI Custom Vision
- Understand image classification
- Train an image classifier
Module 10: Detect objects in images
- Understand object detection
- Train an object detector
- Consider options for labeling images
Module 11: Detect, analyze, and recognize faces
- Identify options for face detection analysis and identification
- Understand considerations for face analysis
- Detect faces with the Azure AI Vision service
- Understand capabilities of the face service
- Compare and match detected faces
- Implement facial recognition
Module 12: Read Text in images and documents with the Azure AI Vision Service
- Explore Azure AI Vision options for reading text
- Use the Read API
Module 13: Analyze video
- Understand Azure Video Indexer capabilities
- Extract custom insights
- Use Video Analyzer widgets and APIs
Module 14: Analyze text with Azure AI Language
- Provision an Azure AI Language resource
- Detect language
- Extract key phrases
- Analyze sentiment
- Extract entities
- Extract linked entities
Module 15: Create question answering solutions with Azure AI Language
- Understand question answering
- Compare question answering to Azure AI Language understanding
- Create a knowledge base
- Implement multi-turn conversation
- Test and publish a knowledge base
- Use a knowledge base
- Improve question answering performance
Module 16: Build a conversational language understanding model
- Understand prebuilt capabilities of the Azure AI Language service
- Understand resources for building a conversational language understanding model
- Define intents, utterances, and entities
- Use patterns to differentiate similar utterances
- Use pre-built entity components
- Train, test, publish, and review a conversational language understanding model
Module 17: Create a custom text classification solution
- Understand types of classification projects
- Understand how to build text classification projects
Module 18: Custom named entity recognition
- Understand custom named entity recognition
- Label your data
- Train and evaluate your model
Module 19: Translate text with Azure AI Translator service
- Provision an Azure AI Translator resource
- Specify translation options
- Define custom translations
Module 20: Create speech-enabled apps with Azure AI services
- Provision an Azure resource for speech
- Use the Azure AI Speech to Text API
- Use the text to speech API
- Configure audio format and voices
- Use Speech Synthesis Markup Language
Module 21: Translate speech with the Azure AI Speech service
- Provision an Azure resource for speech translation
- Translate speech to text
- Synthesize translations
Module 22: Create an Azure AI Search solution
- Manage capacity
- Understand search components
- Understand the indexing process
- Search an index
- Apply filtering and sorting
- Enhance the index
Module 23: Create a custom skill for Azure AI Search
- Define the custom skill schema
- Add a custom skill
- Custom text classification skill
- Machine learning custom skill
Module 24: Create a knowledge store with Azure AI Search
- Define projections
- Define a knowledge store
Module 25: Implement advanced search features in Azure AI Search
- Improve the ranking of a document with term boosting
- Improve the relevance of results by adding scoring profiles
- Improve an index with analyzers and tokenized terms
- Enhance an index to include multiple languages
- Improve search experience by ordering results by distance from a given reference point
Module 26: Search data outside the Azure platform in Azure AI Search using Azure Data Factory
- Index data from external data sources using Azure Data Factory
- Index any data using the Azure AI Search push API
Module 27: Maintain an Azure AI Search solution
- Manage security of an Azure AI Search solution
- Optimize performance of an Azure AI Search solution
- Manage costs of an Azure AI Search solution
- Improve reliability of an Azure AI Search solution
- Monitor an Azure AI Search solution
- Debug search issues using the Azure portal
Module 28: Perform search reranking with semantic ranking in Azure AI Search
- What is semantic ranking?
- Set up semantic ranking
Module 29: Perform vector search and retrieval in Azure AI Search
- What is vector search?
- Prepare your search
- Understand embedding
Module 30: Plan an Azure AI Document Intelligence solution
- Understand AI Document Intelligence
- Plan Azure AI Document Intelligence resources
- Choose a model type
Module 31: Use prebuilt Document intelligence models
- Understand prebuilt models
- Use the General Document, Read, and Layout models
- Use financial, ID, and tax models
Module 32: Extract data from forms with Azure Document intelligence
- What is Azure Document Intelligence?
- Get started with Azure Document Intelligence
- Train custom models
- Use Azure Document Intelligence models
- Use the Azure Document Intelligence Studio
Module 33: Create a composed Document intelligence model
- Understand composed models
- Assemble composed models
Module 34: Get started with Azure OpenAI Service
- Access Azure OpenAI Service
- Use Azure AI Studio
- Explore types of generative AI models
- Deploy generative AI models
- Use prompts to get completions from models
- Test models in Azure AI Studio's playground
Module 35: Build natural language solutions with Azure OpenAI Service
- Integrate Azure OpenAI into your app
- Use Azure OpenAI REST API
- Use Azure OpenAI SDK
Module 36: Apply prompt engineering with Azure OpenAI Service
- Understand prompt engineering
- Write more effective prompts
- Provide context to improve accuracy
Module 37: Develop applications with Azure OpenAI Service
- Access Azure OpenAI Service
- Integrate OpenAI into an app
- OpenAI prompt engineering
- Provide context with prompt engineering
- Construct code from natural language
Module 38: Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service
- Understand Retrieval Augmented Generation (RAG) with Azure OpenAI Service
- Add your own data source
- Chat with your model using your own data
Module 39: Generate images with Azure OpenAI Service
- What is DALL-E?
- Explore DALL-E in Azure AI Studio
- Use the Azure OpenAI REST API to consume DALL-E models
Hands-on Labs
- Lab : Get Started with Cognitive Services
- Lab : Manage Cognitive Services Security
- Lab : Monitor Cognitive Services
- Lab : Use a Cognitive Services Container
- Lab : Analyze Text
- Lab : Translate Text
- Lab : Recognize and Synthesize Speech
- Lab : Translate Speech
- Lab : Create a Language Understanding App
- Lab : Create a Language Understanding Client Application
- Lab : Use the Speech and Language Understanding Services
- Lab : Create a QnA Solution
- Lab : Create a Bot with the Bot Framework SDK
- Lab : Create a Bot with Bot Framework Composer
- Lab : Analyze Images with Computer Vision
- Lab : Analyze Video
- Lab : Classify Images with Custom Vision
- Lab : Detect Objects in Images with Custom Vision
- Lab : Detect, Analyze, and Recognize Faces
- Lab : Read Text in Images
- Lab : Extract Data from Forms
- Lab : Create an Azure Cognitive Search solution
- Lab : Create a Custom Skill for Azure Cognitive Search
- Lab : Create a Knowledge Store with Azure Cognitive Search
Best Value offer
- Official Courseware
- Instructor-led live online / Classroom
- Flexible Schedule
- Course Completion Certification
US$ 1950
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