- Description
- Curriculum
- Reviews
Artificial Intelligence and machine learning in particular are solving a significant number of business and social problems and giving computers a new way to handle and process vast amounts of data.
In this course, you’ll learn about AI and machine learning concepts regarding regression, classification, and clustering algorithms. You’ll explore how to manage datasets and work with labeled versus unlabeled data.
You’ll learn how supervised and unsupervised machine learning can be used, as well as how to build and use AIs safely, transparently, and fairly. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
Azure AI Fundamentals online training prepares you for the exam and this exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure. So, taking this online training will give you an advantage over others.
Candidates with both technical and non-technical backgrounds can proceed on with this online training and gain knowledge of AI and ML basics.
Below are the concepts that you will learn in this course
- describe datasets and how to manipulate data for those datasets
- differentiate between labeled and unlabeled data and describe why some AI models require labeled data
- describe how features are selected and used from datasets in AI algorithms
- describe regression algorithms and how they are used to make predictions
- describe classification algorithms and how they are used to classify objects or relations
- describe clustering algorithms and how they can be used to determine groupings in data
- describe how supervised machine learning models use labeled data, are simpler to build, and have more accurate results
- describe how unsupervised machine learning models use unlabeled data, which makes them more complex but more flexible than supervised machine learning
- describe how to responsibly use AI by making sure it is reliable and safe
- describe how transparency should be used with AI algorithms in a responsible way
- describe how privacy and security must be factored into responsibly creating and using AI solutions
- describe how the use of inclusiveness in AI algorithms can benefit everyone
- describe how fairness in AI algorithms results in responsible AI
- describe how governance and organizational policies provide accountability for AI responsibility
Target Audience
- Azure Developers.
- Data scientists
- IT professional
- Students
Prerequisites
There are no prerequisites for this courseware. Anyone with an interest in pursuing AI and ML can pursue this online training.
Why Should I choose Lara Online Training?
- We provide Very in-depth course material with Real Time Scenarios for each topic with its Solutions for, Microsoft Azure AI Fundamental: AI-900 Online Training
- Â At Lara, we provide case studies in real-time applications with a professional explanation.
- Â We do Schedule the sessions based upon your comfort by our Highly Qualified Trainers and Real-time Experts.
- Â Class recordings are available immediately after the session for future reference.
- Â We do Normal Track, Fast Track, and Weekend Batches for Microsoft Azure AI Fundamental: AI-900 Online Training
- Â We assist you with cost Effective and Flexible Payment Schemes.
- Â At Lara, we provide Placement Assistance.
-  We provide Assessment and Mock Interviews
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Analyze images with the Computer Vision service -
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Classify images with the Custom Vision service
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15
Detect objects in images with the Custom Vision service
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16
Detect and analyze faces with the Face service
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Read text with the Computer Vision service
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18
Analyze receipts with the Form Recognizer service
