We really hope you'll agree, this training is way more than the average course on Udemy!
Have access to the following:
Training from an instructor of over 20 years who has trained thousands of people and also a Microsoft Certified Trainer
Lecture that explains the concepts in an easy to learn method for someone that is just starting out with this material
Instructor led hands on and simulations to practice that can be followed even if you have little to no experience
TOPICS COVERED INCLUDING HANDS ON LECTURE AND PRACTICE TUTORIALS:
Introduction
Welcome to the course
IMPORTANT Using Assignments in the course
Creating a free Azure Account
Order of concepts covered in the course
Introduction to artificial intelligence terminology
Identify features of common AI workloads
Understanding features of anomaly detection workloads
Example of univariate anomaly detection
Example of multivariate anomaly detection
What is computer vision workloads?
Conceptual usage of natural language processing workloads
Visualizing knowledge mining principals
Identify guiding principles for responsible AI
Introduction to responsible AI
Fairness and Inclusiveness in an AI solution
Reliability and safety in an AI solution
Privacy and security in an AI solution
Transparency in an AI solution
Accountability in an AI solution
Identify common machine learning types
Create an Azure Machine Learning workspace for machine learning scenarios
What is regression machine learning?
Building a pipeline with regression machine learning for cleaning a dataset
Implement a regression machine learning scenario
Evaluating the results of regression machine learning scenarios
What is classification machine learning?
Implement a classification machine learning scenario in Azure
Understanding labels on a confusion matrix
Clustering machine learning example
Describe core machine learning concepts
Understanding features and labels in a dataset for machine learning
How training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Using Automated machine learning
Understanding Azure Machine Learning Designer
Cleaning up our existing Azure resources
Identify common types of computer vision solutions
What are the Azure computer vision solutions?
Creating an Azure computer vision resource
Image classification and object detection solutions in vision studio
Optical character recognition solutions in vision studio
Facial detection and facial analysis solutions in vision studio
Spatial analysis solutions in vision studio
Identify Azure tools and services for computer vision tasks
Using the POSTMAN tool for interacting with Azure AI Services
Implementing the capabilities of the Computer Vision service
Implementing the capabilities of the Custom Vision service
Implementing the capabilities of the Face service
Implementing the capabilities of the Form Recognizer service
Identify features of common NLP Workload Scenarios
What are the Azure AI Language features?
Creating a language service resource in Azure
Trying out key phrase extraction
Trying out key entity recognition
Trying out key sentiment analysis
Trying out key language modeling
Trying out key speech recognition and synthesis
Trying out key translation
Identify Azure tools and services for NLP workloads
Exploring the capabilities of the Language service
Exploring the capabilities of the Speech service
Exploring the capabilities of the Translator service
Configuring Azure AI language to support questions and answers support
Identify considerations for conversational AI solutions on Azure
Understanding the features and uses for bots
Capabilities of Power Virtual Agents and the Azure Bot service
Remove existing resource
Identify features and capabilities of generative AI & the Azure Open AI Service
Features of generative Open AI models
Common scenarios for generative Open AI
Responsible Open AI considerations for generative AI