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EnglishAI-100: Designing and Implementing an Azure AI Solution [AI-100T01-A] training including Exam Voucher
Learn to translate the vision from solution architects to build complete end-to-end solutions as an Azure AI engineer!
Training codeCGAAI100CESpoken LanguageEnglishLanguage MaterialsEnglishDayparts6Price€1.600,00excl. VAT No extra costs.Book AI-100: Designing and Implementing an Azure AI Solution [AI-100T01-A] training including Exam Voucher now
This course will mostly take place in a group setting. We use several learning methods to help you obtain the knowledge, give you helpful insights and get you inspired. Check the Spoken Language on the left for language info.
What is AI-100: Designing and Implementing an Azure AI Solution [AI-100T01-A] including Exam Voucher
Gain subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.
This course uses MOC (Microsoft Official Courseware) and will be given by an experienced MCT (Microsoft Certified Trainer).
See the below modules for more information:
Module 1: Introducing Azure Cognitive Services
The student will learn about the available Cognitive Services on Microsoft Azure and their role in architecting AI solutions.
Lessons- Overview of Azure Cognitive Services
- Creating a Cognitive Service on the Azure Portal
- Access and Test a Cognitive Service
Module 2: Creating Bots
The student will learn about the Microsoft Bot Framework and Bot Services.
Lessons- Introducing the Bot Service
- Creating a Basic Chat Bot
- Testing with the Bot Emulator
Module 3: Enhancing Bots with QnA Maker
The student will learn about the QnA Maker and how to integrate Bots and QnA Maker to build up a useful knowledge base for user interactions.
Lessons- Introducing QnA Maker
- Implement a Knowledge Base with QnA Maker
- Integrate QnA with a Bot
Module 4: Learn How to Create Language Understanding Functionality with LUIS
The student will learn about Language Understanding with Intents and Utterances (LUIS) and how to create intents and utterances to support a natural language processing solution.
Lessons- Introducing Language Understanding
- Create a new LUIS Service
- Build LUIS
Module 5: Enhancing Your Bots with LUIS
The student will learn about integrating LUIS with a Bot to better understand the users’ intentions when interacting with the Bot.
Lessons- Overview of language understanding for AI applications
- Integrate LUIS and Bot to create an AI-based solution
Module 6: Integrate Cognitive Services with Bots and Agents
The student will learn about integrating Bots and Agents with Azure Cognitive Services for advanced features such as sentiment analysis, image and text analysis, and OCR and object detection.
Lessons- Understand Cognitive Services for Bot Interactions
- Perform Sentiment Analysis for your Bot with Text Analytics
- Detect Language in a Bot with the Language Cognitive Services
- Integrate Computer Vision with Bots
Who should attend the AI-100: Designing and Implementing an Azure AI Solution [AI-100T01-A] including Exam Voucher
This course is aimed at Cloud Solution Architects, Azure artificial intelligence designers, and AI developers. You have experience working with data scientists, data engineers, IoT specialists, and software developers.
Also, you will receive a voucher to make the exam. Enlist today!Prerequisites
The participants should have prior knowledge of:
Professional experience with cloud technologies, and experience with software development.- Implementing solutions in C# or Python.
- Application development in the cloud.
- Understanding Azure storage technologies.
- If you are completely new to Azure AI services, please complete Microsoft Azure AI Fundamentals first.
Objectives
After completing this course, you will be able to:
Requirements analysis for AI solutions.- Recommending the appropriate tools and technologies.
- Designing and implementing AI solutions that meet scalability and performance requirements.
- Use of Microsoft Azure Cognitive Services, Azure Bot Service, Azure Cognitive Search, and data storage in Azure.
- Knowledge of the components that make up the Azure AI portfolio and the available data storage options.
- Knowledge of when a custom API should be developed to meet specific requirements.
- Analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.
Exam information
- Exam duration (minutes): 150-210
- % extra time for non-native speakers:
- Number of exam questions: 40-60
- Minimum correct questions:
- Exam style: Multiple choice
- Open book: No
A NEW VERSION OF THIS EXAM, AI-102, WILL BE AVAILABLE ON FEBRUARY 23, 2021. You will be able to take this exam until it retires on June 30, 2021. Note: Exams retire at 11:59 PM Central Standard Time.
Learn to translate the vision from solution architects to build complete end-to-end solutions as an Azure AI engineer!
Training codeCGAAI100CESpoken LanguageEnglishLanguage MaterialsEnglishDayparts6Price€1.600,00excl. VAT No extra costs.With an Incompany training you have several advantages:
- You choose the location
- You experience the training with your colleagues, so it is always in line with your practice
- The trainer can tailor explanations, examples and assignments to your organization
- In consultation exercises can be adapted to organization-specific questions
Request more information or a quote.What is AI-100: Designing and Implementing an Azure AI Solution [AI-100T01-A] including Exam Voucher
Gain subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.
This course uses MOC (Microsoft Official Courseware) and will be given by an experienced MCT (Microsoft Certified Trainer).
See the below modules for more information:
Module 1: Introducing Azure Cognitive Services
The student will learn about the available Cognitive Services on Microsoft Azure and their role in architecting AI solutions.
Lessons- Overview of Azure Cognitive Services
- Creating a Cognitive Service on the Azure Portal
- Access and Test a Cognitive Service
Module 2: Creating Bots
The student will learn about the Microsoft Bot Framework and Bot Services.
Lessons- Introducing the Bot Service
- Creating a Basic Chat Bot
- Testing with the Bot Emulator
Module 3: Enhancing Bots with QnA Maker
The student will learn about the QnA Maker and how to integrate Bots and QnA Maker to build up a useful knowledge base for user interactions.
Lessons- Introducing QnA Maker
- Implement a Knowledge Base with QnA Maker
- Integrate QnA with a Bot
Module 4: Learn How to Create Language Understanding Functionality with LUIS
The student will learn about Language Understanding with Intents and Utterances (LUIS) and how to create intents and utterances to support a natural language processing solution.
Lessons- Introducing Language Understanding
- Create a new LUIS Service
- Build LUIS
Module 5: Enhancing Your Bots with LUIS
The student will learn about integrating LUIS with a Bot to better understand the users’ intentions when interacting with the Bot.
Lessons- Overview of language understanding for AI applications
- Integrate LUIS and Bot to create an AI-based solution
Module 6: Integrate Cognitive Services with Bots and Agents
The student will learn about integrating Bots and Agents with Azure Cognitive Services for advanced features such as sentiment analysis, image and text analysis, and OCR and object detection.
Lessons- Understand Cognitive Services for Bot Interactions
- Perform Sentiment Analysis for your Bot with Text Analytics
- Detect Language in a Bot with the Language Cognitive Services
- Integrate Computer Vision with Bots
Who should attend the AI-100: Designing and Implementing an Azure AI Solution [AI-100T01-A] including Exam Voucher
This course is aimed at Cloud Solution Architects, Azure artificial intelligence designers, and AI developers. You have experience working with data scientists, data engineers, IoT specialists, and software developers.
Also, you will receive a voucher to make the exam. Enlist today!Prerequisites
The participants should have prior knowledge of:
Professional experience with cloud technologies, and experience with software development.- Implementing solutions in C# or Python.
- Application development in the cloud.
- Understanding Azure storage technologies.
- If you are completely new to Azure AI services, please complete Microsoft Azure AI Fundamentals first.
Objectives
After completing this course, you will be able to:
Requirements analysis for AI solutions.- Recommending the appropriate tools and technologies.
- Designing and implementing AI solutions that meet scalability and performance requirements.
- Use of Microsoft Azure Cognitive Services, Azure Bot Service, Azure Cognitive Search, and data storage in Azure.
- Knowledge of the components that make up the Azure AI portfolio and the available data storage options.
- Knowledge of when a custom API should be developed to meet specific requirements.
- Analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.
Exam information
- Exam duration (minutes): 150-210
- % extra time for non-native speakers:
- Number of exam questions: 40-60
- Minimum correct questions:
- Exam style: Multiple choice
- Open book: No
A NEW VERSION OF THIS EXAM, AI-102, WILL BE AVAILABLE ON FEBRUARY 23, 2021. You will be able to take this exam until it retires on June 30, 2021. Note: Exams retire at 11:59 PM Central Standard Time.
Related
Fields of ExpertiseCloude-CF competences with this course
At Capgemini Academy we believe in transparency and clarity in the training landscape. That is why, in the table below, we show you to which e-CF competence this training or certification contributes. For more information about how to use the e-Competence Framework read more here. If you want to know how you can apply the e-CF within your organization, read more on this page.
e-Competence Level 1 2 3 4 5 B.6.Systems Engineering A.5.Architecture Design C.5.Systems Management
