AI-900: Microsoft Azure AI Fundamentals in a Weekend
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I’m here to help you pass the AI-900 Azure AI Fundamentals certification exam!
Do you think learning Artificial Intelligence and Machine Learning is DIFFICULT? What if I can prove you WRONG?
Learn AI and ML Fundamentals in a WEEKEND!
Take your FIRST STEPS into the amazing world of Artificial Intelligence and Machine Learning using a HANDS-ON step by step approach.
BEGINNERS to cloud, Azure, AI and ML are WELCOME!
WHAT LEARNERS ARE SAYING
5 STARS – The course is amazing, just direct to the point
5 STARS – Good course to quickly clear the certification exam.
5 STARS – Another superb course from In28Minutes!
5 STARS – Right to the point and provided short notes were amazing.
6 Things YOU need to know about this AI–900 Course
#1: HANDS-ON – The best way to learn Azure AI Fundamentals is to get your hands dirty!
#2: Designed for ABSOLUTE BEGINNERS to Azure
#3: MULTI-CLOUD INSTRUCTOR – MORE THAN 100,000 Learners are learning AWS, Azure, and Google Cloud with us
#4: COMPLETE PREP for Azure Certification – AI-900 – Microsoft Azure AI Fundamentals
#5: FREE Downloadable PDF – Quickly Review for the exam
#6: FREE Practice Test – Test if you are ready for the exam
Artificial Intelligence (AI) will revolutionize how we do things in the next decade. Cloud is making AI easy! This course is a wonderful introduction to the world of Cloud and Artificial Intelligence. AI-900 Azure AI Fundamentals validates foundational knowledge of machine learning and artificial intelligence concepts and related Microsoft Azure services.
AI-900 Azure AI Fundamentals helps you demonstrate knowledge of:
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AI workloads and considerations
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Fundamental principles of machine learning on Azure
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Features of computer vision workloads on Azure
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Features of Natural Language Processing (NLP) workloads on Azure
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Features of conversational AI workloads on Azure.
Skills measured in AI-900 Azure AI Fundamentals
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Describe AI workloads and considerations
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Describe fundamental principles of machine learning on Azure
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Describe features of computer vision workloads on Azure
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Describe features of Natural Language Processing (NLP) workloads on Azure
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Describe features of conversational AI workloads on Azure
Are you ready to get started on the amazing journey to achieve Azure Certification – AI-900 – Microsoft Azure AI Fundamentals?
Do you want to join 750,000+ learners having Amazing Learning Experiences with in28Minutes?
Look No Further!
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3Step 01 - Introduction to Artificial Intelligence & Machine Learning
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4Course Update: Link to Demo
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5Step 02 - Exploring Machine Learning Examples
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6Step 03 - Exploring Machine Learning vs Traditional Programming
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7Step 04 - Machine Learning Fundamentals - Scenarios
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8Section Quiz
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9Step 05 - Exploring Different Types of AI Workloads
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10Step 01 - Exploring Pre Trained Models - Cognitive Services
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11Course update - Cognitive Services renamed to Azure AI Services
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12Course Update - Links to New Demos
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13Step 02 - Exploring Vision Related APIs
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14Step 03 - Exploring Vision - Some Terminology
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15Step 04 - Getting started with Computer Vision API
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16Creating Azure Account
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17Step 05 - Demo - Creating Cognitive Services Multi Service Account
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18Step 06 - Demo - Playing with Computer Vision API
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19Do you want to help us?
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20Step 07 - Understanding Computer Vision API - OCR Operations
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21Course Updates - Links to New Demos
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22Step 08 - Getting Started with Face API
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23Step 09 - Exploring Form Recognizer API
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24Step 10 - Cognitive Services - Vision - Scenarios
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25Step 11 - Getting Started - Cognitive Services - Natural Language Processing
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26Step 12 - Exploring Text Analytics API
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27Step 13 - Exploring Translator and Speech API
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28Step 14 - Getting Started with Conversational AI
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29Step 15 - Demo - Playing with QnA Maker - 1 - Getting Started
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30Step 16 - Demo - Playing with QnA Maker - 2 - Setting up Knowledge Base
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31Step 17 - Demo - Playing with Azure Bot Service
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32Step 18 - Exploring LUIS/ Language Understanding Intelligent Service
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33Step 19 - Cognitive Services - NLP - Scenarios
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34Step 20 - Understanding Decision Services/ Make smarter decisions
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35Step 21 - Cognitive Services - Decision Services and Others
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36Step 22 - Cognitive Services - A Quick Review
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37Section Quiz
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38Quick Review : Reviewing Basics Before Getting Started with Generative AI
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39Step 01 What is Generative AI?
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40Most Popular Generative AI Tool Today - ChatGPT
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41Step 02 Playing with ChatGPT - Getting Started
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42Step 03 Playing with ChatGPT - Coding, Learning and Design
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43Step 04 Playing with ChatGPT - Exploring Technology
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44How is Generative AI Different?
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45Step 05 Generative AI - Needs Huge Volumes of Data
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46Step 06 Generative AI - Uses Self Supervised Learning
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47Step 07 Key Step In Generative AI For Text - Predicting Next Word
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48Step 08 Understanding Deep Learning
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49Step 09 Understanding Loss Function
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50Step 10 Getting Started with Azure OpenAI API
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51Step 11 The AI Turmoil - My View Point
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52Course Downloads - Custom Vision - Images
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53Step 01 - Building ML Models - Custom Vision - 1
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54Step 02 - Building ML Models - Custom Vision - 2
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55Step 03 - Creating ML Models - Features and Labels
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56Step 04 - Creating ML Models - Choosing Technique
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57Step 05 - Machine Learning Fundamentals - Scenarios
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58Step 06 - Creating Machine Learning Models - Steps
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59Step 07 - Understanding Machine Learning Terminology
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60Step 08 - ML Stages and Terminology - Scenarios
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61Do you want to help us?
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62Step 09 - Getting Started with Azure Machine Learning
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63Step 10 - Demo - Automated Machine Learning - Dataset and Compute
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64Step 11 - Demo - Setting up Automated ML Training
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65Step 12 - Demo - Exploring Automated ML Training
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66Step 13 - Demo - Creating Azure Machine Learning Pipeline
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67Step 14 - Demo - Model Evaluation - Regression Models
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68Step 15 - Model Evaluation - Classification Models
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69Step 16 - ML Model Evaluation - Scenarios
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70Step 17 - Azure Machine Learning - Terminology
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71Step 18 - Building Custom ML Models in Azure - Scenarios
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72Section Quiz