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AI Engineer

AI-102

START YOUR AI ODYSSEY

An AI engineer is a pivotal architect of cutting-edge technologies, specializing in the development, management, and deployment of sophisticated AI solutions. These professionals orchestrate the entire lifecycle of AI projects, spanning from conceptualization and design to implementation, integration, optimization, and ongoing maintenance. AI engineers collaborate closely with a multidisciplinary team, working alongside data scientists, software developers, infrastructure administrators, and domain experts to create comprehensive AI-driven solutions that transcend conventional boundaries.

As an AI engineer, you possess the prowess to craft AI-powered applications that exhibit remarkable capabilities, ranging from language translation and sentiment analysis to image recognition and predictive modeling. You harness the potential of machine learning algorithms and advanced neural networks to enable systems to learn, adapt, and evolve over time, while striving for enhanced accuracy, efficiency, and real-world impact. With proficiency in languages like Python and familiarity with REST-based APIs, you craft robust and secure solutions that revolutionize industries, enrich user experiences, and drive innovation to the forefront.

Embracing the path of becoming an AI engineer unveils a world of limitless possibilities. By mastering the intricacies of AI technologies, you acquire the prowess to shape the future of automation, intelligent decision-making, and problem-solving. The demand for AI engineers is soaring across industries, as organizations seek to harness the transformative potential of AI to gain competitive advantages, streamline processes, and innovate at an unprecedented scale. Your journey as an AI engineer equips you to contribute meaningfully to groundbreaking projects, spearhead technological advancements, and play a pivotal role in shaping a future where AI is seamlessly integrated into our daily lives, propelling you into an exciting realm of innovation and boundless career opportunities.

Overview

An AI engineer is a proficient architect of artificial intelligence solutions, adept at designing, developing, and deploying advanced AI systems that encompass machine learning, natural language processing, computer vision, and more. These professionals wield the expertise to create transformative applications, optimize algorithms, and integrate AI technologies into various domains, contributing to a future powered by intelligent automation and innovation.

AI is not only for engineers. It's for anyone who has an innovative idea and wants to turn it into a product.

Fei-Fei Li, co-director of Stanford University's Human-Centered AI Institute

Curriculum

Topics Covered

Prepare for AI engineering

As someone aspiring to become an Azure AI Engineer, it’s essential to grasp fundamental AI development concepts and principles, along with a comprehensive understanding of the capabilities offered by Azure services utilized in the creation of AI solutions.

  1. Introduction
  2. Define Artificial Intelligence
  3. Understand AI-related terms
  4. Understand considerations for AI Engineers
  5. Understand considerations for responsible AI
  6. Understand capabilities of Azure Machine Learning
  7. Understand capabilities of Azure AI Services
  8. Understand capabilities of the Azure Bot service
  9. Understand capabilities of Azure Cognitive Search

Provision and manage Azure Cognitive Services

Discover the potential of Azure AI Services in seamlessly integrating AI capabilities into your applications. Gain insights into the creation and utilization of these services to enhance your development skills.

  1. Provision an Azure AI Services resource
  2. Identify endpoints and keys
  3. Use a REST API
  4. Use an SDK
  5. Use Azure AI Services

Implementing robust security measures for Azure AI Services is essential to safeguard against potential data breaches and protect user privacy within the solution.

  1. Consider authentication
  2. Implement network security
  3. Manage Azure AI Services Security

Leveraging Azure AI Services empowers you to seamlessly integrate AI capabilities into your applications and services. Ensuring effective monitoring of Azure AI Services is crucial for tracking usage patterns, identifying emerging trends, and swiftly identifying and resolving any operational challenges that may arise.

  1. Monitor cost
  2. Create alerts
  3. View metrics
  4. Manage diagnostic logging
  5. Monitor Azure AI

Explore the incorporation of containers within Azure AI Services, facilitating the utilization of Azure APIs while offering versatile deployment options through Docker containers. This feature enhances adaptability in choosing deployment locations and hosting solutions for your services.

  1. Understand containers
  2. Use Azure AI services containers
  3. Use a container

Process and translate text with Azure Cognitive Services

Leverage the Language service to develop smart applications and solutions capable of extracting meaningful insights from textual content.

  1. Provision a Language resource
  2. Detect language
  3. Extract key phrases
  4. Analyze sentiment
  5. Extract entities
  6. Extract linked entities
  7. Analyze text

Utilize the Translator service to build intelligent applications and solutions with the ability to translate text seamlessly between different languages.

  1. Provision a Translator resource
  2. Understand language detection, translation, and transliteration
  3. Specify translation options
  4. Define custom translations
  5. Translate text with the Translator service

Process and Translate Speech with Azure Cognitive Speech Services

Leverage the capabilities of the Speech service to develop applications that are empowered with speech functionalities. This section concentrates on harnessing the speech-to-text and text-to-speech APIs, enabling you to craft applications that can perform speech recognition and synthesis tasks.

  1. Provision an Azure resource for speech
  2. Use the Speech to text API
  3. Use the Text to speech API
  4. Configure audio formats and voices
  5. Use Speech Synthesis Markup Language
  6. Create a speech-enabled app

Expanding upon speech recognition, speech translation involves recognizing and transcribing spoken input in a designated language, then providing translations of the transcription in one or multiple other languages.

  1. Provision an Azure resource for speech translation
  2. Translate speech to text
  3. Synthesize translations
  4. Translate speech

Create a Language Understanding solution with Azure Cognitive Services

The Language Understanding service empowers you to train a language model that applications can utilize to derive significance from natural language expressions.

  1. Understand resources for building a language understanding model
  2. Define intents, utterances, and entities
  3. Use patterns to differentiate similar utterances
  4. Use pre-built entity components
  5. Train, test, publish, and review a Language Understanding model
  6. Build a language understanding model

Once you’ve developed a Language Understanding app, you can make it available for use by publishing it and integrating it into client applications.

  1. Understand capabilities of the Language service
  2. Process predictions
  3. Use a container
  4. Create a Language Understanding app

Build a question answering solution

The Language service’s question answering feature simplifies the creation of applications where users can ask questions using natural language and receive relevant answers.

  1. Understand question answering
  2. Compare question answering to language understanding
  3. Create a knowledge base
  4. Implement multi-turn conversation
  5. Test and publish a knowledge base
  6. Use a knowledge base
  7. Improve question answering performance
  8. Create a question answering bot
  9. Create a question answering solution

Build custom text analytics solutions

Harness the power of the Language service in Azure Cognitive Services to process natural language for your applications. Explore the process of creating a personalized text classification project from scratch.

  1. Understand types of classification projects
  2. Understand how to build text classification projects
  3. Classify text

Develop a tailored entity recognition solution for extracting key elements from unstructured documents.

  1. Understand custom named entity recognition
  2. Label your data
  3. Train and evaluate your model
  4. Extract custom entities

Create conversational AI solutions

Acquire the skills to create a bot using the Microsoft Bot Framework SDK.

  1. Introduce principles of bot design
  2. Get started with the Bot Framework SDK
  3. Implement activity handlers and dialogs
  4. Deploy a bot
  5. Create a bot with the Bot Framework SDK

Utilize the Bot Framework Composer to effortlessly construct advanced conversational bots without the need for coding.

  1. Understand ways to build a bot
  2. Get started with the Bot Framework Composer
  3. Understand dialogs
  4. Understand adaptive flow
  5. Design the user experience
  6. Create a bot with the Bot Framework Composer

Create computer vision solutions with Azure Cognitive Services

Leverage the Computer Vision service to employ pre-trained models for analyzing images and extracting valuable insights and information.

  1. Provision a Computer Vision resource
  2. Analyze and image
  3. Generate a smart-cropped thumbnail
  4. Analyze images with Computer Vision

Azure Video Analyzer for Media offers a service for extracting valuable insights from videos, encompassing tasks like face identification, text recognition, object labeling, scene segmentation, and more.

  1. Understand Video Analyzer for Media capabilities
  2. Extract custom insights
  3. Use Video Analyzer widgets and APIs
  4. Analyze video

Image classification serves to identify the primary subject of an image. By utilizing the Custom Vision services, you have the ability to train a model that classifies images according to your customized categories.

  1. Provision Azure resources for custom vision
  2. Understand image classification
  3. Train an image classifier
  4. Classify images with custom vision

Object detection is employed to pinpoint and recognize items within images. The Custom Vision platform can be harnessed to train a model geared towards identifying distinct classes of objects within images.

  1. Understand object detection
  2. Train an object detector
  3. Consider options for labeling images
  4. Detect objects images wit custom vision

The capacity of applications to detect human faces, analyze facial attributes and emotions, and recognize individuals constitutes a fundamental capability of artificial intelligence.

  1. Identify options for face detection analysis and identification
  2. Understand considerations for face analysis
  3. Detect faces with the computer vision service
  4. Understand capabilities of the face service
  5. Compare and match detected faces
  6. Implement facial recognition
  7. Detect, analyze and identify faced

Extract text from images and documents

Azure’s Computer Vision service employs algorithms to analyze images and provide data. This module instructs you on utilizing the Read API for optical character recognition (OCR).

  1. Explore Computer Vision options for reading text
  2. Use the Read API
  3. Read text in images

Form Recognizer harnesses machine learning technology to accurately identify and extract key-value pairs and table data from form documents on a large scale. This module guides you through using the Azure Form Recognizer cognitive service.

  1. What is Form Recognizer?
  2. Get started with Form Recognizer
  3. Understand prebuilt models
  4. Train custom models
  5. Use Form Recognizer models
  6. Extract data from custom forms
  7. Use the Recognizer Studio

Implement knowledge mining with Azure Cognitive Search

Reveal concealed insights within your data using Azure Cognitive Search.

  1. Azure resources
  2. Search components
  3. Understand the indexing process
  4. Search an index
  5. Apply filtering and sorting
  6. Enhance the index
  7. Create a search solution

Harness the capabilities of artificial intelligence to enhance your data and uncover fresh insights.

  1. Create a custom skill
  2. Add a custom skill to a skillset
  3. Implement a custom skill

Store the outcomes generated by an Azure Cognitive Search enrichment pipeline for separate analysis or subsequent processing.

  1. Define projections
  2. Define a knowledge store
  3. Create a knowledge store

Leverage Azure Cognitive Service for language to harness the capabilities of Natural Language Processing (NLP) for automated text comprehension and analysis. Employ this capability to enrich and elevate your search solutions.

  1. Explore the available features of Azure Cognitive Service for Language
  2. Enrich a cognitive search index with custom classes and Language Studio
  3. Enrich a cognitive search index with custom classes

Explore the advanced functionalities of Azure Cognitive Search to enhance your current search solutions. Discover techniques to adjust document rankings, amplify specific terms, and enable multi-language search capabilities.

  1. Improve the ranking of a document with term boosting
  2. Improve the relevance of results by adding scoring profiles
  3. Improve an index with analyzers and tokenized terms
  4. Enhance an index to include multiple languages
  5. Improve search experience by ordering results by distance from a given reference point
  6. Implement enhancements to search results

Employ custom skills to augment datasets during enrichment pipeline traversal. Azure Machine Learning can create personalized regression or classification models for enhancing your search indexes.

  1. Understand how to use a custom Azure Machine Learning skillset
  2. Enrich a search index using an Azure Machine Learning model
  3. Enrich a search index using Azure Machine Learning model

Leverage Azure Data Factory to integrate data from both within and beyond the Azure platform into your search indexes.

  1. Index data from external data sources using Azure Data Factory
  2. Index any data using the Azure Cognitive Search push API
  3. Add to an index using the push API

Ensure the optimal performance, cost-efficiency, and reliability of your Azure Cognitive Search solutions.

  1. Manage security of an Azure Cognitive Search solution
  2. Optimize performance of an Azure Cognitive Search solution
  3. Manage costs of an Azure Cognitive Search solution
  4. Improve reliability of an Azure Cognitive Search solution
  5. Debug search issues using Azure portal

Develop Generative AI solutions with Azure OpenAI Service

This module equips engineers with the necessary skills to initiate the construction of an Azure OpenAI Service solution.

  1. Access Azure OpenAI Service
  2. Use Azure OpenAI Studio
  3. Explore types of generative AI models
  4. Deploy generative AI models
  5. Use prompts to get completions from models
  6. Test models in Azure OpenAI Studio’s playgrounds
  7. Get started with Azure OpenAI Service

This module imparts engineers with the abilities to initiate the development of applications that seamlessly integrate with the Azure OpenAI Service.

  1. Integrate Azure OpenAI into your app
  2. Use Azure OpenAI REST API
  3. Use Azure OpenAI SDK
  4. Integrate Azure OpenAI into your app

In the realm of Azure OpenAI, prompt engineering refers to the practice of formulating prompts tailored for natural language processing models. This approach enhances response accuracy and pertinence, thereby optimizing the overall performance of the model.

  1. Understand prompt engineering
  2. Write more effective prompts
  3. Provide context to improve accuracy
  4. Utilize prompt engineering in your application

In this module, engineers will learn how to harness the capabilities of the Azure OpenAI Service to create and enhance code generation.

  1. Construct code from natural language
  2. Complete code and assist the development process
  3. Fix bugs and improve your code
  4. Generate and improve code with Azure OpenAI Service

Within the Azure OpenAI service, the DALL-E model is available, enabling the generation of unique images using prompts in natural language.

  1. What is DALL-E?
  2. Explore DALL-E in Azure OpenAI Studio
  3. Use the Azure REST API to consume DALL-E models
  4. Generate images with a DALL-E model

Leveraging Azure OpenAI with your data empowers developers to utilize AI chat models that can incorporate specific data sources to provide well-grounded responses.

  1. Understand how to use your own data
  2. Add your own data source
  3. Chat with your model using your own data
  4. Use your own data with Azure OpenAI Service

Generative AI unlocks incredible creative possibilities, but its implementation must prioritize responsibility to mitigate potential risks associated with generating harmful content.

  1. Plan a responsible generative AI solution
  2. Identify potential harms
  3. Measure potential harms
  4. Mitigate potential harms
  5. Operate a responsible generative AI solution
  6. Explore content filters in Azure OpenAI Service

Course Duration

4 Days

Choose the training options that match your preferences from the list below.

Remote Training

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Elevate your skills with hands-on onsite training led by industry experts. Enroll now for excellence!

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AI Engineering - unleashed

  • Tackle complex problems using AI techniques and innovative solutions.
  • Ensure ethical AI practices by addressing bias and transparency.
  • Shape the future by contributing to AI research and technology evolution.

Unveil the possibilities ahead

  • You will get a comprehensive set of materials and resources designed to provide a well-rounded learning experience.
  • Receive course manuals or syllabus, lecture slides, practical exercises, assessments such as quizzes or exams.
  • Access our online learning platform or virtual classrooms, and interact with instructors and other students.

MS Teams Developer

Maximizing Collaboration, Communication, and Productivity for Seamless Team Development.

Azure

Mastering Azure Unleashes Limitless Cloud Possibilities for Innovation and Growth with Cloud Technology.

AI Developer

Ignite Curiosity, Transform Industries, Shape the Future by Unlocking the Potential of Artificial Intelligence.

Onsite Training

Customized in-person training at the workplace, or in-class training, convenient and cost-effective.

Remote Training

Learning via Teams remotely online, offers online video conferencing for convenient and flexible access.

Hybrid Training

Combining on-site and remote training, we provide a comprehensive training experience.