Azure AI Fundamentals Certification (AI-900) - Full Course to PASS the Exam



Prepare for the Azure AI Fundamentals Certification (AI-900) and pass!

✏️ Course developed by Andrew Brown of ExamPro. Check out the ExamPro YouTube channel: https://www.youtube.com/ExamProChannel
🔗 ExamPro Cloud Obsessed Certification Training: https://www.exampro.co

⭐️ Course Contents ⭐️
☁️ Introduction
🎤 (00:00:00) Introduction
🎤 (00:09:19) Exam Guide Breakdown

☁️ ML Introduction
🎤 (00:13:58) Layers of Machine Learning
🎤 (00:15:06) Key Elements of AI
🎤 (00:16:04) DataSets
🎤 (00:17:44) Labeling
🎤 (00:18:50) Supervised and Unsupervised Reinforcement
🎤 (00:20:16) Neural Networks and Deep Learning
🎤 (00:22:32) GPU
🎤 (00:23:28) CUDA
🎤 (00:24:36) Simple ML Pipeline
🎤 (00:26:46) Forecast vs Prediction
🎤 (00:27:31) Metrics
🎤 (00:29:05) Juypter Notebooks
🎤 (00:30:20) Regression
🎤 (00:31:57) Classification
🎤 (00:32:51) Clustering
🎤 (00:33:36) Confusion Matrix

☁️ Common AI Workloads
🎤 (00:35:13) Anomaly Detection AI
🎤 (00:36:06) Computer Vision AI
🎤 (00:38:12) Natural Language Processing AI
🎤 (00:39:49) Conversational AI

☁️ Responsible AI
🎤 (00:41:23) Responsible AI
🎤 (00:42:16) Fairness
🎤 (00:43:15) Reliability and safety
🎤 (00:44:07) Privacy and security
🎤 (00:44:52) Inclusiveness
🎤 (00:45:31) Transparency
🎤 (00:46:07) Accountability
🎤 (00:46:52) Guidelines for Human AI Interaction
🎤 (00:47:11) Follow Along Guidelines for Human AI Interaction

☁️ Cognitive Services
🎤 (00:58:40) Azure Cognitive Services
🎤 (01:00:48) Cognitive API Key and Endpoint
🎤 (01:01:15) Knowledge Mining
🎤 (01:05:49) Face Service
🎤 (01:07:37) Speech and Translate Service
🎤 (01:09:11) Text Analytics
🎤 (01:12:09) OCR Computer Vision
🎤 (01:13:29) Form Recognizer
🎤 (01:15:55) Form Recognizer Custom Models
🎤 (01:16:41) Form Recognizer Prebuilt Models
🎤 (01:18:40) LUIS
🎤 (01:21:05) QnA Maker
🎤 (01:25:26) Azure Bot Service

☁️ ML Studio
🎤 (01:27:52) Azure Machine Learning Service
🎤 (01:29:17) Studio Overview
🎤 (01:30:46) Studio Compute
🎤 (01:31:55) Studio Data Labeling
🎤 (01:32:52) Data Stores
🎤 (01:33:41) Datasets
🎤 (01:34:51) Experiments
🎤 (01:35:23) Pipelines
🎤 (01:36:30) ML Designer
🎤 (01:37:14) Model Registry
🎤 (01:37:41) Endpoints
🎤 (01:38:57) Notebooks

☁️ AutoML
🎤 (01:39:48) Introduction to AutoML
🎤 (01:42:22) Data Guard Rails
🎤 (01:43:08) Automatic Featurization
🎤 (01:45:00) Model Selection
🎤 (01:46:04) Explanation
🎤 (01:46:58) Primary Metrics
🎤 (01:48:50) Validation Type

☁️ Custom Vision
🎤 (01:49:21) Introduction to Custom Vision
🎤 (01:50:05) Project Types and Domains
🎤 (01:53:01) Custom Vision Features

☁️ Follow Alongs
🎤 (01:55:39) Setup
🎤 (02:06:37) Computer Vision
🎤 (02:10:19) Custom Vision Classification
🎤 (02:16:57) Custom Vision Object Detection
🎤 (02:22:53) Face Service
🎤 (02:26:05) Form Recognizer
🎤 (02:29:36) OCR
🎤 (02:34:29) Text Analysis
🎤 (02:38:12) QnAMaker
🎤 (02:56:46) LUIS
🎤 (03:02:31) AutoML
🎤 (03:19:48) Designer
🎤 (03:30:06) MNIST
🎤 (03:49:45) Data Labeling
🎤 (03:54:13) Clean up

☁️ CheatSheet
🎤 (03:55:28) AI CheatSheet

🎉 Thanks to our Champion and Sponsor supporters:
👾 Wong Voon jinq
👾 hexploitation
👾 Katia Moran
👾 BlckPhantom
👾 Nick Raker
👾 Otis Morgan
👾 DeezMaster
👾 Treehouse

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26 thoughts on “Azure AI Fundamentals Certification (AI-900) – Full Course to PASS the Exam”
  1. Hi, Sorry but I guess at 22:38 GPU's full form pronounced wrongly as General Processing Unit, it should be like Graphics Processing Unit, correct me if I am missing anything.

  2. I tried the az 900 2 times , and I still haven't cleared it after 1 year of trying ( not concentrated)
    Also the azure fundamentals certifications do not expire.

  3. Thank you so much for this course, I passed the exam after going through this course, special thanks for the cheatsheet. Kudos!

  4. Misunderstanding in the confusion matrix (00:34:11):

    The division into 100 labeled items and 70 predictions is NOT related to the confusion matrix!

    The example SHOULD say:
    Our ground truth had 170 labeled items, of which

    100 are labeled NO (negative) and 70 are labeled YES (positive).

    Our model made 170 predictions, of which

    125(=75+50) are predicted to get the label NO (negative) and

    45(=25+20) are predicted to get the label YES (positive).

    The predictions are called TRUE if CORRECTLY classified, that is

    the 75 ground truth negative predicted as negative, are named True negatives and

    the 20 ground truth positive predicted as positive, are named True positives.

    The predictions are called FALSE if ERRONEOUSLY classified, that is

    the 25 ground truth negative predicted as positive, are named False positives and

    the 50 ground truth positive predicted as negative, are named False negatives.

    Check f.ex. https://en.wikipedia.org/wiki/Confusion_matrix

  5. Hello, Andrew. Trust me when I say that I passed the exam after only seeing your video and not studying at all… Thank you, Brother. 936/1000

  6. Hello, Andrew. Trust me when I say that I passed the exam after only seeing your video and not studying at all… Thank you, Brother. 936/1000

  7. Great video, I believe there is an error in the confusion matrix at 34:45 ? When predicting No and the actual outcome is No that should be a true negative

  8. Can I give the exam without doing AZ-900? Will it be a failure if I give the exam without having any experience or information of AZ-900?

  9. Just passed the exam 10 mins ago, please ensure you watch this and memorize key points and familiar yourself with the MS learning as most of the questions will come from there , good luck everyone

  10. There is a small error in the confusion matrix. If the Predicted and Actual are both NO, this is called a True Negative (the model predicted it correctly!).

    When the model predicted is NO, but the actual is YES, then it is a false negative (the model was wrong).

  11. Does anyone notice something with Confusion Matrix(33:36) …. !!!. I have a doubt, is it correct !!??

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