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Aron Mesterbasic
Candidates for this course build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Your course package is designed to provide maximum learning and convenience. This is included in the price of your course:
Your expert instructor will get you ready for the following exam and certification, which are included in your course package and covered by the Certification guarantee.
Candidates for this exam should be proficient in C#, Python, or JavaScript and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
Using our engaging learning methodology including a variety of tools, we’ll cover the entire curriculum.
Plan and Manage an Azure Cognitive Services Solution
- select the appropriate Cognitive Services resource
- select the appropriate cognitive service for a vision solution
- select the appropriate cognitive service for a language analysis solution
- select the appropriate cognitive Service for a decision support solution
- select the appropriate cognitive service for a speech solution
Plan and configure security for a Cognitive Services solution
- manage Cognitive Services account keys
- manage authentication for a resource
- secure Cognitive Services by using Azure Virtual Network
- plan for a solution that meets responsible AI principles
Create a Cognitive Services resource
- create a Cognitive Services resource
- configure diagnostic logging for a Cognitive Services resource
- manage Cognitive Services costs
- monitor a cognitive service
- implement a privacy policy in Cognitive Services
Plan and implement Cognitive Services containers
- identify when to deploy to a container
- containerize Cognitive Services (including Computer Vision API, Face API, Text Analytics, Speech, Form Recognizer)
Implement Computer Vision Solutions (20-25%)
Analyze images by using the Computer Vision API
- retrieve image descriptions and tags by using the Computer Vision API
- identify landmarks and celebrities by using the Computer Vision API
- detect brands in images by using the Computer Vision API
- moderate content in images by using the Computer Vision API
- generate thumbnails by using the Computer Vision API
Extract text from images
- extract text from images by using the OCR API
- extract text from images or PDFs by using the Read API
- convert handwritten text by using Ink Recognizer
- extract information from forms or receipts by using the pre-built receipt model in Form
Recognizer
- build and optimize a custom model for Form Recognizer
Extract facial information from images
- detect faces in an image by using the Face API
- recognize faces in an image by using the Face API
- configure persons and person groups
- analyze facial attributes by using the Face API
- match similar faces by using the Face API
Implement image classification by using the Custom Vision service
- label images by using the Computer Vision Portal
- train a custom image classification model in the Custom Vision Portal
- train a custom image classification model by using the SDK
- manage model iterations
- evaluate classification model metrics
- publish a trained iteration of a model
- export a model in an appropriate format for a specific target
- consume a classification model from a client application
- deploy image classification custom models to containers
Implement an object detection solution by using the Custom Vision service
- label images with bounding boxes by using the Computer Vision Portal
- train a custom object detection model by using the Custom Vision Portal
- train a custom object detection model by using the SDK
- manage model iterations
- evaluate object detection model metrics
- publish a trained iteration of a model
- consume an object detection model from a client application
- deploy custom object detection models to containers
Analyze video by using Video Indexer
- process a video
- extract insights from a video
- moderate content in a video
- customize the Brands model used by Video Indexer
- customize the Language model used by Video Indexer by using the Custom Speech service
- customize the Person model used by Video Indexer
- extract insights from a live stream of video data
Implement Natural Language Processing Solutions (20-25%)
Analyze text by using the Text Analytics service
- retrieve and process key phrases
- retrieve and process entity information (people, places, urls, etc.)
- retrieve and process sentiment
- detect the language used in text
Manage speech by using the Speech service
- implement text-to-speech
- customize text-to-speech
- implement speech-to-text
- improve speech-to-text accuracy
Translate language
- translate text by using the Translator service
- translate speech-to-speech by using the Speech service
- translate speech-to-text by using the Speech service
Build an initial language model by using Language Understanding Service (LUIS)
- create intents and entities based on a schema, and then add utterances
- create complex hierarchical entities, use this instead of roles
- train and deploy a model
Iterate on and optimize a language model by using LUIS
- implement phrase lists
- implement a model as a feature (i.e. prebuilt entities)
- manage punctuation and diacritics
- implement active learning
- monitor and correct data imbalances
- implement patterns
Manage a LUIS model
- manage collaborators
- manage versioning
- publish a model through the portal or in a container
- export a LUIS package
- deploy a LUIS package to a container
- integrate Bot Framework (LUDown) to run outside of the LUIS portal
Implement Knowledge Mining Solutions (15-20%)
Implement a Cognitive Search solution
- create data sources
- define an index
- create and run an indexer
- query an index
- configure an index to support autocomplete and autosuggest
- boost results based on relevance
- implement synonyms
Implement an enrichment pipeline
- attach a Cognitive Services account to a skillset
- select and include built-in skills for documents
- implement custom skills and include them in a skillset
Implement a knowledge store
- define file projections
- define object projections
- define table projections
- query projections
Manage a Cognitive Search solution
- provision Cognitive Search
- configure security for Cognitive Search
- configure scalability for Cognitive Search
Manage indexing
- manage re-indexing
- rebuild indexes
- schedule indexing
- monitor indexing
- implement incremental indexing
- manage concurrency
- push data to an index
- troubleshoot indexing for a pipeline
Implement Conversational AI Solutions (15-20%)
Create a knowledge base by using QnA Maker
- create a QnA Maker service
- create a knowledge base
- import a knowledge base
- train and test a knowledge base
- publish a knowledge base
- create a multi-turn conversation
- add alternate phrasing
- add chit-chat to a knowledge base
- export a knowledge base
- add active learning to a knowledge base
- manage collaborators
Design and implement conversation flow
- design conversation logic for a bot
- create and evaluate *.chat file conversations by using the Bot Framework Emulator
- add language generation for a response
- design and implement adaptive cards
Create a bot by using the Bot Framework SDK
- implement dialogs
- maintain state
- implement logging for a bot conversation
- implement a prompt for user input
- add and review bot telemetry
- implement a bot-to-human handoff
- troubleshoot a conversational bot
- add a custom middleware for processing user messages
- manage identity and authentication
- implement channel-specific logic
- publish a bot
Create a bot by using the Bot Framework Composer
- implement dialogs
- maintain state
- implement logging for a bot conversation
- implement prompts for user input
- troubleshoot a conversational bot
- test a bot by using the Bot Framework Emulator
- publish a bot
Integrate Cognitive Services into a bot
- integrate a QnA Maker service
- integrate a LUIS service
- integrate a Speech service
- integrate Dispatch for multiple language models
- manage keys in app settings file
The Virtual Classroom is an online room, where you will join your instructor and fellow classmates in real time. Everything happens live and you can interact freely, discuss, ask questions, and watch your instructor present on a whiteboard, discuss the courseware and slides, work with labs, and review.
Yes, you can sit exams from all the major Vendors like Microsoft, Cisco etc from the comfort of your home or office.
With Readynez you do any course form the comfort of your home or office. Readynez provides support and best practices for your at-home classroom and you can enjoy learning with minimal impact on your day-to-day life. Plus you'll save the cost and the environmental burden of travelling.
Well, learning is limitless, when you are motivated, but you need the right path to achieve what you want. Readynez consultants have many years of experience customizing learner paths and we can design one for you too. We are always available with help and guidance, and you can reach us on the chat or write us at info@readynez.com.