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

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

What is the Azure AI Fundamentals Certification?

The Azure AI Fundamentals Certification is for those seeking a Machine Learning role such as AI Engineer or Data Scientist.

In the last decade companies have been collecting vast amount of data surrounding their service and product offerings.

The successful companies of the 2010s were data-driven companies who knew how to collect, transform, store and analyze their vast amount of data.

The successful companies of the 2020s will be ml-driven who how know how to leverage deep learning and create AI product and service offerings.

Overview of the Azure AI Fundamentals

The Azure AI Fundamentals covers the following:

• Azure Cognitive Services
• AI Concepts
• Knowledge Mining
• Responsible AI
• Basics of ML pipelines and MLOps
• Classical ML models
• AutoML and Azure ML Studio

How do you get the Azure AI Fundamentals certification?

You can get the certification by paying the exam fee and sitting for the exam at a test center partnered with Microsoft Azure.

Microsoft Azure is partnered with Pearson Vue and PSI Online who have a network of test centers around the world. They provide both in-person and online exams. If you have the opportunity, I recommend that you take the exam in-person.

Microsoft has a portal page on Pearsue Vue where you can register and book your exam.

That exam fee is $99 USD.

Can I simply watch the videos and pass the exam?

For a fundamental certification like the AI-900 you can pass by just watching the video content without exploring hands-on with the Azure services on your own

Azure has a much higher frequency of updates than other cloud service providers. Sometimes there are new updates every month to a certification however, the AI-900 is not hands-on focused, so study courses are less prone to becoming stale.

• The exam has 40 to 60 questions with a timeline of 60 minutes.
• The exam contains many different question types.
• A passing grade is around 70%.

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⭐️ 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

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