Course Description
AI-102 Designing and Applying AI-infused An Azure AI Solution is designed for software developers who want to create Applications that make use of Azure Cognitive Services, Azure Cognitive Search, and the Microsoft Bot Framework. The programming language for the training will be C# or Python.
Prerequisites
Before attending this course, students must have the following:
- Understanding of Microsoft Azure and ability to navigate the Azure portal
- Knowledge of either C# or Python
- Familiarity with JSON and REST programming semantics
- To gain C# or Python skills, complete the free Take a learning path that introduces you to Python or C# before enrolling in the course.
If you are new to artificial intelligence and want an overview of AI capabilities on Azure, consider completing the Azure AI Fundamentals certification before taking this one.
Target Audience
Software engineers are responsible for developing, managing, and deploying AI solutions based on Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python. They have an understanding of using REST-based APIs to build computer vision, language analysis, interpretation mining, intelligent search, and conversational AI solutions on Azure.
Content Outline
After completing this module, participants will be able to:
- Define artificial intelligence
- Understand AI-related terms
- Understand considerations for AI Engineers
- Understand reviews for responsible AI
- Understand the capabilities of Azure Machine Learning
- Understand the capabilities of Azure Cognitive Services
- Understand the powers of the Azure Bot Service
- Understand the capabilities of Azure Cognitive Search
- Provision of Cognitive Services resources in an Azure subscription.
- Identify endpoints, keys, and locations required to finish a Cognitive Services resource.
- Use a REST API to consume a cognitive service.
- Use an SDK to consume a mental service.
- Consider authentication for Cognitive Services
- Manage network security for Cognitive Services
- Monitor Cognitive Services costs
- Create alerts
- View metrics
- Manage diagnostic logging
- Create Containers for Reuse
- Deploy to a Container
- Secure a Container
- Consume Cognitive Services from a Container
- Detect language
- Extract key phrases
- Analyze sentiment
- Extract entities
- Extract linked entities
- Provision a Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
- Provision an Azure resource for the Speech service
- Use the Speech-to-Text API to apply speech recognition
- Use the Text-to-Speech API to apply speech synthesis
- Configure audio format and voices
- Use Speech Synthesis Markup Language (SSML)
- Translate speech with the speech service
- Generate text translation from speech.
- Synthesize spoken translations.
- Provision Azure resources for Language Understanding
- Define intents, utterances, and entities
- Use patterns to differentiate similar utterances
- Use prebuilt entity components
- Develop, test, publish, and evaluate a language comprehension model.
- Understand the capabilities of a Language Understanding app
- Process predictions from a Language Understanding app
- Deploy a language-understanding app in a container
- Understand question answering
- Compare question answering to language understanding
- Create an understanding base
- Apply multi-turn conversation
- Test and publish an understanding base
- Consume an understanding base
- Apply active learning
- Create a question-answering bot
- Understand the principles of bot design
- To create a bot, use the Bot Framework SDK.
- Deploy a bot to Azure
- Understand dialogs
- Plan conversational flow
- Design the user experience
- Make a bot with the Bot Framework Composer
- Provision a Computer Vision resource
- Analyze an image
- Generate a smart-cropped thumbnail
- Describe Video Analyzer for Media Capabilities
- Extract custom insights
- Use Video Analyzer for Media widgets and APIs
- Classify images
- Understand image classification
- Train an image classifier
- Provision Azure resources for Custom Vision
- Understand object detection
- Train an object detector
- Consider options for labeling images
- Identify options for face detection, analysis, and identification
- Understand considerations for face analysis
- Detect faces with the Computer Vision service
- Understand the capabilities of the Face service
- Compare and match detected faces
- Apply facial recognition
- Utilize the Read API to extract text from images.
- utilizing the REST API and SDKs to access the Computer Vision service
- Make an application that can read printed and handwritten text
- Identify how Form Recognizer's layout service, prebuilt models, and customer service can automate processes
- Use Form Recognizer's Optical Character Recognition (OCR) capabilities with SDKs, REST API, and Form Recognizer Studio
- Develop and test custom models
- Create an Azure Cognitive Search Solution
- Develop a search application
- Apply a custom skill for Azure Cognitive Search
- Integrate a custom skill into an Azure Cognitive Search skillset
- Create an understanding store from an Azure Cognitive Search pipeline
- View data in projections in an understanding store
FAQs
AI-102 Software developers who want to create AI-enhanced applications using Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework should refer to Designing and Applying an Azure AI Solution. Python or C# will be used as the programming language for the course.
Service that is fully managed and aids in securing remote access to your virtual machines. Firewall for web applications. A web application firewall (WAF) service that is cloud-native and offers a strong defense for web applications. Avatar Firewall Utilize cloud-native network security to safeguard your Azure Virtual Network resources.
Utilize Azure Machine Learning and Azure Databricks to quickly and easily create, train, and deploy your machine learning models. Utilize cutting-edge programs like Visual Studio Code and Jupyter, as well as frameworks like PyTorch on Azure, TensorFlow, and Scikit-Learn.
The migration Assistant tool helps the user to examine your IIS installation. It allows the user to recognize which site can be migrated to the Cloud. In general, it features components that are either not migrated or unsupported on the Azure platform
A: ASP.Net, PHP, and WCF are web applications that can be deployed with SQL Azure.
To attend the training session, you should have operational Desktops or Laptops with the required specification and a good internet connection to access the labs.
We would always recommend you attend the live session to practice & clarify the doubts instantly and get more value from your investment. However, if, due to some contingency, you have to skip the class, Radiant Techlearning will help you with the recorded session of that particular day. However, those recorded sessions are not meant only for personal consumption and NOT for distribution or any commercial use.
Radiant Techlearning has a data center containing a Virtual Training environment for participant hand-on-practice.
Participants can easily access these labs over Cloud with the help of a remote desktop connection.
Radiant virtual labs allow you to learn from anywhere and in any time zone.
The learners will be enthralled as we engage them the real-world and industry Oriented projects during the training program. These projects will improve your skills and understanding, and you will gain a better experience. These real-time projects will help you greatly in future tasks and assignments.