Description

This course will help you prepare for the AI-900 Exam: Microsoft Azure AI Fundamentals. We will cover the complete exam syllabus as updated in April 2021 with sample questions.

Prepare for the AI-900 Certification Exam by covering the complete exam syllabus as updated in April 2021 with sample questions with this course. We will be covering the following 5 domains in the course: Domain 1: We will cover the identification of features in common AI workloads and guiding principles for responsible AI. Domain 2: We will cover the identification of common machine learning variants, description of core machine learning concepts, identification of core risks in the creation of a machine learning solution, and description of capabilities of no-code machine learning with Azure machine learning. Domain 3: We will cover the identification of common types of computer vision solutions and the identification of Azure tools and services for computer vision tasks. Domain 4: We will cover the identification of features in common NLP workload scenarios and learn how to identify Azure tools and services for NLP workloads. Domain 5: We will cover the identification of common use cases for conversational AI and will be identifying Azure services for conversational AI. By the end of this course, you will be ready to appear for your AI-900 exam. All the resources for this course are available at https://github.com/PacktPublishing/AI-900-Microsoft-Azure-AI-Fundamentals-Video-Course-and-Ques.

What You Will Learn

Learn foundational knowledge of machine learning and artificial intelligence
Learn common ML and AI workloads and how to implement them on Azure
Cover principles of machine learning on Azure
Learn about computer vision workloads on Azure
Cover Natural Language Processing (NLP) workloads on Azure
Understand conversational AI workloads on Azure

Audience

This course is designed for those who are willing to give AI-900 Exam: Microsoft Azure AI Fundamentals and are interested in learning the basics of artificial intelligence or machine learning.

No prerequisite is required for this course. Candidates with both technical and non-technical backgrounds can benefit from this course.

Approach

In this course, we will prepare for the AI-900 exam by following the exam syllabus and covering all five domains one by one. The course also includes sample questions that will help you track your learning process.

Key Features

Cover 100% of the syllabus as updated in April 2021 * Prepare for AI-900 Microsoft Azure AI Fundamentals certification exam * Solve sample questions to track your learning progress

Github Repo

https://github.com/PacktPublishing/AI-900-Microsoft-Azure-AI-Fundamentals-Video-Course-and-Ques

About the Author

Eshant Garg

Eshant Garg has 16 years of extensive professional experience with expertise in database and business intelligence solutions, advanced analytics, design and solution architecture, reporting, and cloud computing technologies (Azure and AWS). He loves to explain complicated things in a simple and effective way. As a developer and architect, he has worked closely with customers, users, and colleagues to support business solutions across a variety of industries including healthcare, insurance, finance, and government ranging from small companies to Fortune 500 companies. Outside of the technical world, he loves yoga and meditation. He is a student of the ancient yogic text, the Bhagavad Gita, and loves to discuss and practice philosophical teachings.

Course Outline

1. Introduction

Welcome to the course! Let's take a quick introduction to the course.

1. Course Introduction

In this video, we will cover course introduction.

2. Azure Portal Introduction: For Beginners

In this section, we will cover a quick Azure portal introduction.

1. Create Azure Free Subscription

In this video, you will learn how to create Azure free subscription.

2. Azure Portal Overview

In this video, we will cover Azure portal overview.

3. Azure Sandbox - How to Use Azure Portal Absolutely Free

In this video, we will cover Azure Sandbox - how to use Azure Portal absolutely free.

3. AI Workloads and Considerations (15-20%)

In this section, we will cover domain 1 - AI workloads and considerations, which covers 15-20% of the exam.

1. Learning Objectives

In this video, we will understand the learning objectives of this domain.

2. What is Artificial Intelligence

In this video, we will cover what artificial intelligence is.

3. Prediction and Forecasting

In this video, we will cover prediction and forecasting.

4. Anomaly Detection Workloads

In this video, we will cover anomaly detection workloads.

5. Computer Vision Workloads

In this video, we will cover computer vision workloads.

6. Natural Language Processing

In this video, we will cover natural language processing.

7. Knowledge Mining Workloads

In this video, we will cover knowledge mining workloads.

8. Conversational AI Workloads

In this video, we will cover conversational AI workloads.

9. Introduction to Guiding Principles of Responsible AI

In this video, we will cover an introduction to guiding principles of responsible AI.

10. Guiding Principle - Fairness

In this video, we will cover a guiding principle - fairness.

11. Guiding Principle - Reliability and Safety

In this video, we will cover a guiding principle - reliability and safety.

12. Guiding Principle - Privacy and Security

In this video, we will cover a guiding principle - privacy and security.

13. Guiding Principle - Inclusiveness

In this video, we will cover a guiding principle - inclusiveness.

14. Guiding Principle - Transparency

In this video, we will cover a guiding principle - transparency.

15. Guiding Principle - Accountability

In this video, we will cover a guiding principle - accountability.

4. Fundamental Principles of Machine Learning on Azure (30- 35%)

In this section, we will cover domain 2 - fundamental principles of machine learning on Azure, which covers 30- 35% of the exam.

1. Learning Objectives

In this video, we will understand the learning objectives of this domain.

2. Introduction to Machine Learning

In this video, we will cover an introduction to machine learning.

3. Rule-Based Versus Machine Learning Based Learning

In this video, we will cover rule-based versus machine learning based learning.

4. Classification Versus Regression Versus Clustering Machine Learning Types

In this video, we will cover classification versus regression versus clustering machine learning types.

5. Feature Selection and Feature Engineering

In this video, we will cover feature selection and feature engineering.

6. Training Versus Validating Dataset

In this video, we will cover training versus validating dataset.

7. Machine Learning Algorithms

In this video, we will cover machine learning algorithms.

8. Demo Part1.1 ML Workspace

In this demo video, we will work on ML workspace.

9. Demo Part1.2 Regression Model

In this demo video, we will work on regression model.

10. Demo Part1.3 Delete Resources

In this demo video, we will work on deleting resources.

11. Demo 2.1 Classification Model

In this demo video, we will work on classification model.

12. Demo 3.1 Automated Machine Learning

In this demo video, we will work on automated machine learning.

13. Demo: Delete Compute

In this demo video, we will work on delete compute.

5. Describe Features of Computer Vision Workloads on Azure (15-20%)

In this section, we will cover domain 3 - describe features of computer vision workloads on Azure, which covers 15-20% of the exam.

1. Learning Objectives

In this video, we will understand the learning objectives of this domain.

2. Image Classification Versus Object Detection Versus Semantic Segmentation

In this video, we will cover image classification versus object detection versus semantic segmentation.

3. Optical Character Recognition (OCR)

In this video, we will cover Optical Character Recognition (OCR).

4. Face Detection Recognition and Analysis

In this video, we will cover face detection recognition and analysis.

5. What are Cognitive Services

In this video, we will cover cognitive services.

6. What are Computer Vision Services

In this video, we will cover computer vision services.

7. Demo: Computer Vision

In this demo video, we will work on computer vision.

8. Custom Vision Service

In this video, we will cover custom vision service.

9. Demo: Custom Vision Service

In this demo video, we will work on custom vision service.

10. Face Service

In this video, we will cover face service.

11. Form Recognizer Service

In this video, we will cover form recognizer service.

6. Natural Language Processing (NLP) Workloads on Azure (15-20%)

In this section, we will cover domain 4 - Natural Language Processing (NLP) workloads on Azure, which covers 15-20% of the exam.

1. Learning Objectives

In this video, we will understand the learning objectives of this domain.

2. What is Natural Language Processing

In this video, we will cover Natural Language Processing.

3. Key Phrase Extraction Versus Entity Recognition Versus Sentiment Analysis

In this video, we will cover key phrase extraction versus entity recognition versus sentiment analysis.

4. Language Modelling

In this video, we will cover language modelling.

5. Speech Recognition and Speech Synthesis

In this video, we will cover speech recognition and speech synthesis.

6. Translation

In this video, we will cover translation.

7. Introduction to Azure Tools and Services for NLP

In this video, we will cover an introduction to Azure tools and services for NLP.

8. Text Analytics Service

In this video, we will cover text analytics service.

9. Speech Service

In this video, we will cover speech service.

10. Translator Service

In this video, we will cover translator service.

11. Language Understanding Service (LUIS)

In this video, we will cover Language Understanding Service (LUIS).

7. Conversational AI Workloads on Azure (15-20%)

In this section, we will cover domain 5 - conversational AI workloads on Azure, which covers 15-20% of the exam.

1. Learning Objectives

In this video, we will understand the learning objectives of this domain.

2. Conversational AI Use Cases

In this video, we will cover conversational AI use cases.

3. QnA Maker and Bot Framework

In this video, we will cover QnA Maker and Bot framework.

4. Demo QnA Maker and Bot Framework

In this demo video, we will work on QnA Maker and Bot framework.

8. Practice Tests

In this section, we will understand the exam structure.

1. AI-900 Exam Tips

In this video, we will cover AI-900 Exam tips.

Course Images

AI-900: Microsoft Azure AI Fundamentals Video Course + Ques

By Packt

Booking options

Highlights

Description

Course Content

About The Provider

Tags

Reviews