Dive into the fascinating world of Generative AI in this foundational course designed for beginners. Generative AI, a subset of artificial intelligence, focuses on systems that can produce content, from art and music to text and images.
As one of the most rapidly evolving domains in AI, understanding generative models is crucial for anyone looking to stay at the forefront of technological advancements.
With this course you will learn how to insert Generative AI on your everyday work a personal life, you will be able to identify tasks the can be accomplished with this technology, saving your precious time to more important and demanding ones.
You will also learn the best pratices and techniques to get the best results from your generations and come to know a list of the more famous and used AI tools avaliable today like ChatGPT, Bard, Runway ML, Pika Labs and much more.
In a structured and comprehensive manner. The course is divided into several modules, each focusing on a specific type of data generated with Generative AI and their possibilities with it.
Don't get behind and starting learning today this new theme that will be each day the passes more present in our lifes.
Dive into the fascinating world of Generative AI in this foundational course designed for beginners. Generative AI, a subset of artificial intelligence, focuses on systems that can produce content, from art and music to text and images.
As one of the most rapidly evolving domains in AI, understanding generative models is crucial for anyone looking to stay at the forefront of technological advancements.
With this course you will learn how to insert Generative AI on your everyday work a personal life, you will be able to identify tasks the can be accomplished with this technology, saving your precious time to more important and demanding ones.
You will also learn the best pratices and techniques to get the best results from your generations and come to know a list of the more famous and used AI tools avaliable today like ChatGPT, Bard, Runway ML, Pika Labs and much more.
In a structured and comprehensive manner. The course is divided into several modules, each focusing on a specific type of data generated with Generative AI and their possibilities with it.
Don't get behind and starting learning today this new theme that will be each day the passes more present in our lifes.
Course Overview
This course is expertly designed to equip you with the skills and confidence needed to excel in the Salesforce AI Associate certification exam. It provides a series of practice tests meticulously crafted to mirror the format, content, and level of difficulty you can expect in the actual exam. By enrolling in this course, you'll assess your proficiency, identify areas for improvement, and ultimately be well-prepared for success.
About the Salesforce Certified AI Associate Exam
Read on for details about the Salesforce Certified AI Associate exam.
Content: 40 multiple-choice questions
Time allotted to complete the exam: 70 minutes
Passing score: 65%
Registration fee: USD 75 plus applicable taxes as required per local law
Retake fee: Free
Delivery options: Proctored exam delivered onsite at a testing center or in an online proctored environment.
References: No hard-copy or online materials may be referenced during the exam.
Prerequisite: None
Exam Outline
The Salesforce Certified AI Associate exam measures a candidate’s knowledge and skills related to the following objectives.
AI Fundamentals: 17%
Explain the basic principles and applications of AI within Salesforce.
Differentiate between the types of AI and their capabilities.
AI Capabilities in CRM: 8%
Identify CRM AI capabilities.
Describe the benefits of AI as they apply to CRM.
Ethical Considerations of AI: 39%
Describe the ethical challenges of AI (e.g., human bias in machine learning, lack of transparency, etc.).
Apply Salesforce's Trusted AI Principles to given scenarios.
Data for AI: 36%
Describe the importance of data quality.
Describe the elements/components of data quality.
I keep this course up to date with the most recent Salesforce releases and offer a 30-day, no-questions-asked money-back guarantee!
Course Overview
This course is expertly designed to equip you with the skills and confidence needed to excel in the Salesforce AI Associate certification exam. It provides a series of practice tests meticulously crafted to mirror the format, content, and level of difficulty you can expect in the actual exam. By enrolling in this course, you'll assess your proficiency, identify areas for improvement, and ultimately be well-prepared for success.
About the Salesforce Certified AI Associate Exam
Read on for details about the Salesforce Certified AI Associate exam.
Content: 40 multiple-choice questions
Time allotted to complete the exam: 70 minutes
Passing score: 65%
Registration fee: USD 75 plus applicable taxes as required per local law
Retake fee: Free
Delivery options: Proctored exam delivered onsite at a testing center or in an online proctored environment.
References: No hard-copy or online materials may be referenced during the exam.
Prerequisite: None
Exam Outline
The Salesforce Certified AI Associate exam measures a candidate’s knowledge and skills related to the following objectives.
AI Fundamentals: 17%
Explain the basic principles and applications of AI within Salesforce.
Differentiate between the types of AI and their capabilities.
AI Capabilities in CRM: 8%
Identify CRM AI capabilities.
Describe the benefits of AI as they apply to CRM.
Ethical Considerations of AI: 39%
Describe the ethical challenges of AI (e.g., human bias in machine learning, lack of transparency, etc.).
Apply Salesforce's Trusted AI Principles to given scenarios.
Data for AI: 36%
Describe the importance of data quality.
Describe the elements/components of data quality.
I keep this course up to date with the most recent Salesforce releases and offer a 30-day, no-questions-asked money-back guarantee!
This course goes through all of the skills required for the Microsoft Applied Skills: Build an Azure AI Vision solution.
This can also help with Microsoft AI-102 "Designing and Implementing a Microsoft Azure AI Solution" exam, with "Implement computer vision solutions".
In this 2½ hour course we’ll cover the skills that you need for the Microsoft Applied Skills credential for Azure AI Vision.
The tasks that you need to perform to get this skill are:
Create a computer vision resource and analyze images. We’ll create a computer vision resource in a free Azure subscription, and use it to analyze images. We’ll create captions and dense captions, looking at the results in text and in JSON format, before looking at other features.
Create, train, evaluate and consume a custom image analysis model. After that, we’ll create a custom image analysis model. We will train it to recognise three different types of products, and then test it so that it can identify them in new photos.
Programming in C#. Finally, we’ll find out how to analyse images in code. We’ll use Visual Studio and customise code to connect to both the computer vision and the custom image resources, and use them to analyse images and return the analysis.
We’ll go through several practical examples, so you can see how you can analyse your own images.
By the end of the course, you'll be much more confident about using building an Azure AI Vision solution and perhaps even take the official Microsoft assessment. That would look great on your CV or resume.
This course goes through all of the skills required for the Microsoft Applied Skills: Build an Azure AI Vision solution.
This can also help with Microsoft AI-102 "Designing and Implementing a Microsoft Azure AI Solution" exam, with "Implement computer vision solutions".
In this 2½ hour course we’ll cover the skills that you need for the Microsoft Applied Skills credential for Azure AI Vision.
The tasks that you need to perform to get this skill are:
Create a computer vision resource and analyze images. We’ll create a computer vision resource in a free Azure subscription, and use it to analyze images. We’ll create captions and dense captions, looking at the results in text and in JSON format, before looking at other features.
Create, train, evaluate and consume a custom image analysis model. After that, we’ll create a custom image analysis model. We will train it to recognise three different types of products, and then test it so that it can identify them in new photos.
Programming in C#. Finally, we’ll find out how to analyse images in code. We’ll use Visual Studio and customise code to connect to both the computer vision and the custom image resources, and use them to analyse images and return the analysis.
We’ll go through several practical examples, so you can see how you can analyse your own images.
By the end of the course, you'll be much more confident about using building an Azure AI Vision solution and perhaps even take the official Microsoft assessment. That would look great on your CV or resume.
Welcome to our comprehensive practice exams course designed to equip you with the winning advantage on your path to achieving Microsoft Azure AI Fundamentals - AI-900 certification!
Our meticulously crafted course mirrors the real exam experience, offering questions that align with the tone and style of the actual test. Each question is accompanied by detailed explanations, diagrams, and reference links, ensuring a deep understanding of all domains covered in the AI-900 exam.
Rest assured, our expertly curated content draws extensively from Microsoft documentation, providing you with a thorough grasp of AI and machine learning concepts essential for the exam.
Our aim is to be your ultimate resource for success. We want you to confidently cross the finish line, fully prepared to conquer the AI-900 exam.
Key Features of our Course:
Thorough Coverage: Our question bank spans all four categories of the AI-900 certification exam, ensuring proficiency in AI workloads, machine learning principles, computer vision, and Natural Language Processing (NLP) workloads on Azure.
Exam Simulation: Our practice tests closely replicate the real exam format with 35-50 questions, including various question types such as single select, multiple select, Yes/No, Drag and Drop, Select from Drop-down, and True/False.
Flexibility and Support: Retake exams as needed, and our mobile-compatible course allows convenient learning on the go. Dedicated instructors are available for support and answering queries.
Money-Back Guarantee: Confident in our course's quality, we offer a 30-day money-back guarantee for your satisfaction.
Enroll now to embark on a fulfilling journey toward AI-900 certification. Prepare with confidence, excel in the exam, and delve into the exciting realm of AI and machine learning on Microsoft Azure. Happy learning and best of luck for your Microsoft Azure AI Fundamentals - AI-900 exam!
Practice Test Content Areas:
AI Workloads and Considerations (15-20%)
Fundamental Principles of Machine Learning (30-35%)
Introduction to Azure AI Services (20-25%)
Introduction to Computer Vision (15-20%)
Introduction to Natural Language Processing (15-20%)
Welcome to our comprehensive practice exams course designed to equip you with the winning advantage on your path to achieving Microsoft Azure AI Fundamentals - AI-900 certification!
Our meticulously crafted course mirrors the real exam experience, offering questions that align with the tone and style of the actual test. Each question is accompanied by detailed explanations, diagrams, and reference links, ensuring a deep understanding of all domains covered in the AI-900 exam.
Rest assured, our expertly curated content draws extensively from Microsoft documentation, providing you with a thorough grasp of AI and machine learning concepts essential for the exam.
Our aim is to be your ultimate resource for success. We want you to confidently cross the finish line, fully prepared to conquer the AI-900 exam.
Key Features of our Course:
Thorough Coverage: Our question bank spans all four categories of the AI-900 certification exam, ensuring proficiency in AI workloads, machine learning principles, computer vision, and Natural Language Processing (NLP) workloads on Azure.
Exam Simulation: Our practice tests closely replicate the real exam format with 35-50 questions, including various question types such as single select, multiple select, Yes/No, Drag and Drop, Select from Drop-down, and True/False.
Flexibility and Support: Retake exams as needed, and our mobile-compatible course allows convenient learning on the go. Dedicated instructors are available for support and answering queries.
Money-Back Guarantee: Confident in our course's quality, we offer a 30-day money-back guarantee for your satisfaction.
Enroll now to embark on a fulfilling journey toward AI-900 certification. Prepare with confidence, excel in the exam, and delve into the exciting realm of AI and machine learning on Microsoft Azure. Happy learning and best of luck for your Microsoft Azure AI Fundamentals - AI-900 exam!
Practice Test Content Areas:
AI Workloads and Considerations (15-20%)
Fundamental Principles of Machine Learning (30-35%)
Introduction to Azure AI Services (20-25%)
Introduction to Computer Vision (15-20%)
Introduction to Natural Language Processing (15-20%)
AI-900: Microsoft Azure AI Fundamentals is a comprehensive course designed to provide individuals with a solid foundation in the field of artificial intelligence (AI) and its applications in the Microsoft Azure platform. This course is ideal for beginners who are interested in understanding the fundamental concepts of AI and how it can be leveraged to solve real-world problems.
This Practice Exam covers a wide range of topics, including the basics of AI, machine learning, and deep learning. Participants will learn about the different types of AI workloads and how they can be implemented using Azure AI services. They will also gain insights into the ethical considerations and responsible AI practices that need to be taken into account when developing AI solutions.
Through a combination of lectures, hands-on labs, and practical exercises, participants will acquire the necessary skills to design and implement AI solutions using Azure AI services. They will learn how to use Azure Cognitive Services to build intelligent applications that can understand, analyze, and interpret human language, images, and videos. Additionally, participants will gain knowledge on how to train and deploy machine learning models using Azure Machine Learning service.
Overall, the AI-900: Microsoft Azure AI Fundamentals course provides a comprehensive introduction to AI and its applications in the Microsoft Azure platform. By the end of the course, participants will have a solid understanding of the fundamental concepts of AI and the practical skills to develop AI solutions using Azure AI services. Whether you are a developer, data scientist, or IT professional, this course will equip you with the knowledge and skills needed to leverage the power of AI in your projects and drive innovation in your organization.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Microsoft Azure AI Fundamentals provides a robust and comprehensive platform for businesses and developers to leverage artificial intelligence capabilities. With services like Azure Machine Learning, Azure Cognitive Services, Azure Bot Services, and Azure Search, businesses can accelerate innovation, automate processes, and gain valuable insights. By embracing Microsoft Azure AI Fundamentals, organizations can stay ahead of the competition and unlock the full potential of AI technologies.
AI-900: Microsoft Azure AI Fundamentals is a comprehensive course designed to provide individuals with a solid foundation in the field of artificial intelligence (AI) and its applications in the Microsoft Azure platform. This course is ideal for beginners who are interested in understanding the fundamental concepts of AI and how it can be leveraged to solve real-world problems.
This Practice Exam covers a wide range of topics, including the basics of AI, machine learning, and deep learning. Participants will learn about the different types of AI workloads and how they can be implemented using Azure AI services. They will also gain insights into the ethical considerations and responsible AI practices that need to be taken into account when developing AI solutions.
Through a combination of lectures, hands-on labs, and practical exercises, participants will acquire the necessary skills to design and implement AI solutions using Azure AI services. They will learn how to use Azure Cognitive Services to build intelligent applications that can understand, analyze, and interpret human language, images, and videos. Additionally, participants will gain knowledge on how to train and deploy machine learning models using Azure Machine Learning service.
Overall, the AI-900: Microsoft Azure AI Fundamentals course provides a comprehensive introduction to AI and its applications in the Microsoft Azure platform. By the end of the course, participants will have a solid understanding of the fundamental concepts of AI and the practical skills to develop AI solutions using Azure AI services. Whether you are a developer, data scientist, or IT professional, this course will equip you with the knowledge and skills needed to leverage the power of AI in your projects and drive innovation in your organization.
AI-900 : Microsoft Azure AI Fundamentals Exam details :
Exam Name: Microsoft Certified - Azure AI Fundamentals
Exam Code: AI-900
Exam Price: $99 (USD)
Number of Questions: Maximum of 40-60 questions,
Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,
Length of Test: 60 Minutes. The exam is available in English and Japanese languages.
Passing Score: 700 / 1000
Languages : English, Japanese, Korean, and Simplified Chinese
Schedule Exam : Pearson VUE
AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:
Skill Measurement Exam Topics:-
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
##) Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
##) Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
##) Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
##) Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Microsoft Azure AI Fundamentals provides a robust and comprehensive platform for businesses and developers to leverage artificial intelligence capabilities. With services like Azure Machine Learning, Azure Cognitive Services, Azure Bot Services, and Azure Search, businesses can accelerate innovation, automate processes, and gain valuable insights. By embracing Microsoft Azure AI Fundamentals, organizations can stay ahead of the competition and unlock the full potential of AI technologies.