Getting Started with Azure OpenAI Boot Camp for Technical Users (TTAI2333)

At Course Completion

This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you’ll learn how to:

· Understand the core concepts and tools of Azure AI services, and their significance in a business environment. This foundational knowledge will help you appreciate how AI can streamline operations and offer innovative solutions.

· Develop the ability to work with Azure Cognitive Services for tasks such as text analytics, speech recognition, and image analysis. These practical skills can enhance applications with rich, natural user experiences.

· Learn how to create, deploy, and monitor machine learning workflows in Azure. This hands-on understanding will allow you to harness the power of AI for predictive modelling and data analysis.

· Acquire the skills to build intelligent chatbots using Azure Bot Services and integrate them with natural language understanding. This ability can improve your organization's customer engagement and services.

· Gain proficiency in using Azure tools for data analysis, visualization, predictive modelling, and real-time analytics. These skills will empower you to draw valuable insights from big data and implement real-time decision-making processes.

· Familiarize yourself with the usage of Azure AI in various applications such as vision, language, speech and voice, and decision support. This knowledge will enable you to create diverse AI-powered solutions tailored to specific industry needs.

Audience Profile

This Intermediate level course is geared for experienced technical users new to AI and Azure. Roles would include but not be limited to software engineers, developers, data analysts, IT professionals, and system administrators who are looking to learn Azure and add AI capabilities to their skillset. Attendees will build on their experience while learning and developing new skills related to Azure AI, but they don’t need to have extensive prior knowledge of AI or Azure to attend.

Prerequisites

To ensure a smooth learning experience and maximize the benefits of attending this course, you should have the following prerequisite skills:

· A basic understanding of general IT concepts such as databases, servers, and networks would help attendees to grasp the concepts and functionalities of Azure AI services more effectively.

· Basic familiarity with any programming language can be beneficial when understanding the workflow of AI solutions, but you don’t need to be a programmer to attend.

· Knowledge of basic data analysis concepts such as data cleaning, data manipulation, and understanding of data types will be helpful, particularly in the sections related to machine learning and data analytics.

Outline

1. Introduction to Azure AI

· Overview of Azure AI services and offerings

· Understanding the benefits of Azure AI for businesses

· Exploring the Azure AI ecosystem and tools

· Lab

2. Azure Cognitive Services

· Introduction to Azure Cognitive Services and its key features

· Text analytics and natural language processing with Azure Cognitive Services

· Speech recognition and synthesis using Azure Cognitive Services

· Computer vision and image analysis with Azure Cognitive Services

· Lab

3. Azure Machine Learning

· Introduction to Azure Machine Learning and its components

· Creating and managing machine learning experiments in Azure

· Training and deploying machine learning models using Azure ML

· Monitoring and scaling machine learning workflows in Azure ML

· Lab

4. Azure Bot Services

· Building intelligent chatbots with Azure Bot Services

· Designing conversational experiences using Azure Bot Framework

· Integrating Azure Bot Services with natural language understanding

· Deploying and managing chatbots in Azure

· Lab

5. Azure Data Science and Analytics

· Exploratory data analysis and visualization with Azure tools

· Building predictive models using Azure Machine Learning Studio

· Implementing big data analytics with Azure HDInsight

· Real-time analytics and stream processing with Azure Stream Analytics

· Lab

6. Azure AI for Vision Applications

· Image recognition and classification using Azure Custom Vision

· Object detection and tracking with Azure Computer Vision

· Building custom vision models with Azure Machine Learning

· Implementing facial recognition and analysis with Azure Face API

· Lab

7. Azure AI for Language Applications

· Text classification and sentiment analysis using Azure Text Analytics

· Language translation and localization with Azure Translator

· Building language models with Azure Language Understanding

· Entity recognition and named entity recognition using Azure NLP services

· Lab

8. Azure AI for Speech and Voice Applications

· Speech-to-text transcription using Azure Speech Services

· Voice synthesis and customization with Azure Speech Services

· Implementing speech translation with Azure Speech Services

· Developing voice-enabled applications with Azure AI services

· Lab

9. Azure AI for Decision Support

· Implementing recommendation systems with Azure Personalizer

· Anomaly detection and predictive maintenance using Azure AI

· Forecasting and time series analysis with Azure Machine Learning

· Building decision support systems using Azure AI services

· Lab