Exam AI-900: Microsoft Azure AI Fundamentals
This exam is an opportunity for you to demonstrate knowledge of machine learning and AI concepts and related Microsoft Azure services. As a candidate for this exam, you should have familiarity with Exam AI-900’s self-paced or instructor-led learning material.
This exam is intended for you if you have both technical and non-technical backgrounds. Data science and software engineering experience are not required. However, you would benefit from having awareness of:
Cloud basics
Client-server applications
You can use Azure AI Fundamentals to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Skills measured
The English language version of this exam will be updated on November 2, 2023. Review the study guide linked in the preceding “Tip” box for details about the skills measured and upcoming changes.
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%)
Tips-
Review the AI-900 study guide to help you prepare for the exam
Demo the exam experience by visiting our exam sandbox
Exam AI-900: Microsoft Azure AI Fundamentals
This exam is an opportunity for you to demonstrate knowledge of machine learning and AI concepts and related Microsoft Azure services. As a candidate for this exam, you should have familiarity with Exam AI-900’s self-paced or instructor-led learning material.
This exam is intended for you if you have both technical and non-technical backgrounds. Data science and software engineering experience are not required. However, you would benefit from having awareness of:
Cloud basics
Client-server applications
You can use Azure AI Fundamentals to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Skills measured
The English language version of this exam will be updated on November 2, 2023. Review the study guide linked in the preceding “Tip” box for details about the skills measured and upcoming changes.
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%)
Tips-
Review the AI-900 study guide to help you prepare for the exam
Demo the exam experience by visiting our exam sandbox
Unlock Your Future as a Software Architect: Master UML and Design Software with Ease
Don't Just Code—Command! I'll Transform You from Developer to Architect with UML Expertise. Make Software Design Your Second Nature."
AI in UML: Discover the power of generative AI in automating and enhancing UML diagram creation.
Are you a software developer looking to escalate your career and transition into software architecture? Look no further. This course is designed to bridge that gap, transforming you from a skilled developer into a visionary software architect.
Coding is Just the Start: Soar to Architect Status with UML Mastery! Design, Communicate, and Lead Projects with Unmatched Clarity
Why This Course Is Essential:
As software development evolves, there's an increasing need for professionals who can see the big picture, create robust system designs, and lead teams effectively. Understanding Unified Modeling Language (UML) is crucial for anyone aspiring to become a software architect. UML serves as the common language that fosters clear communication, collaboration, and a shared understanding among team members and stakeholders.
Skyrocket Your Career from Coder to Architect: Master UML and Design Systems that Wow Stakeholders. Be the Architect Everyone Needs!
What You'll Learn:
Master UML: Grasp the essential UML diagrams and how they contribute to a project’s success.
Transitioning Skills: Practical steps to shift from a software developer to a software architect role.
Team Leadership: How to communicate effectively with stakeholders and lead a development team.
Design Principles: Master the art of designing robust and scalable software architectures.
Course Highlights:
Hands-on UML projects
Real-world case studies
A special 15-minute video on leveraging generative AI for UML diagramming
Interactive quizzes and assignments
Expert-led video lectures
Peer discussions and network opportunities
Who This Course Is For:
This course is ideal for software developers, junior architects, project managers, technical leads, software analysts, and anyone interested in progressing into software architecture roles.
Elevate Your Code to Architecture: Master UML and Become the Software Architect You're Meant to Be! Cut Through Complexity and Design Like a Pro.
Prerequisites:
Basic to intermediate programming skills
Familiarity with software development lifecycles
A willing mind and eagerness to learn
Course Outcomes:
Proficient understanding of UML
Understanding of how AI can streamline and innovate UML diagram generation
Ability to design complex software systems
Enhanced leadership and communication skills
Certificate of Completion
Enroll today to transition from coding tasks to leading architectural visions and designing software with ease!
Unlock Architect-Level Design Skills: I Fast-Track Developers into Master Architects with UML—Turn Complex Systems into Child's Play!
Quantifiable End Outcomes:
UML Proficiency: Ability to create and interpret at least 10 different types of UML diagrams accurately.
Design Skills: Demonstrated ability to design a medium-complexity software system, evidenced by a capstone project or a set of smaller projects throughout the course.
Communication Metrics: Gain the skill to effectively communicate complex system designs to both technical and non-technical stakeholders, evidenced by peer and instructor assessments.
Leadership Ability: Lead at least one team project or simulation during the course, applying best practices in workflow management and team communication.
Exam Scores: Achieve an average score of 85% or above on all course assessments, quizzes, and final exams focused on UML and software architecture principles.
Unlock Your Future as a Software Architect: Master UML and Design Software with Ease
Don't Just Code—Command! I'll Transform You from Developer to Architect with UML Expertise. Make Software Design Your Second Nature."
AI in UML: Discover the power of generative AI in automating and enhancing UML diagram creation.
Are you a software developer looking to escalate your career and transition into software architecture? Look no further. This course is designed to bridge that gap, transforming you from a skilled developer into a visionary software architect.
Coding is Just the Start: Soar to Architect Status with UML Mastery! Design, Communicate, and Lead Projects with Unmatched Clarity
Why This Course Is Essential:
As software development evolves, there's an increasing need for professionals who can see the big picture, create robust system designs, and lead teams effectively. Understanding Unified Modeling Language (UML) is crucial for anyone aspiring to become a software architect. UML serves as the common language that fosters clear communication, collaboration, and a shared understanding among team members and stakeholders.
Skyrocket Your Career from Coder to Architect: Master UML and Design Systems that Wow Stakeholders. Be the Architect Everyone Needs!
What You'll Learn:
Master UML: Grasp the essential UML diagrams and how they contribute to a project’s success.
Transitioning Skills: Practical steps to shift from a software developer to a software architect role.
Team Leadership: How to communicate effectively with stakeholders and lead a development team.
Design Principles: Master the art of designing robust and scalable software architectures.
Course Highlights:
Hands-on UML projects
Real-world case studies
A special 15-minute video on leveraging generative AI for UML diagramming
Interactive quizzes and assignments
Expert-led video lectures
Peer discussions and network opportunities
Who This Course Is For:
This course is ideal for software developers, junior architects, project managers, technical leads, software analysts, and anyone interested in progressing into software architecture roles.
Elevate Your Code to Architecture: Master UML and Become the Software Architect You're Meant to Be! Cut Through Complexity and Design Like a Pro.
Prerequisites:
Basic to intermediate programming skills
Familiarity with software development lifecycles
A willing mind and eagerness to learn
Course Outcomes:
Proficient understanding of UML
Understanding of how AI can streamline and innovate UML diagram generation
Ability to design complex software systems
Enhanced leadership and communication skills
Certificate of Completion
Enroll today to transition from coding tasks to leading architectural visions and designing software with ease!
Unlock Architect-Level Design Skills: I Fast-Track Developers into Master Architects with UML—Turn Complex Systems into Child's Play!
Quantifiable End Outcomes:
UML Proficiency: Ability to create and interpret at least 10 different types of UML diagrams accurately.
Design Skills: Demonstrated ability to design a medium-complexity software system, evidenced by a capstone project or a set of smaller projects throughout the course.
Communication Metrics: Gain the skill to effectively communicate complex system designs to both technical and non-technical stakeholders, evidenced by peer and instructor assessments.
Leadership Ability: Lead at least one team project or simulation during the course, applying best practices in workflow management and team communication.
Exam Scores: Achieve an average score of 85% or above on all course assessments, quizzes, and final exams focused on UML and software architecture principles.
Welcome to the ultimate practice exams course designed to give you the winning edge in your journey to becoming Microsoft Azure AI Fundamentals - AI-900 certified!
Are you ready to pass the Microsoft Azure AI Fundamentals (AI-900) certification exam? Find out by testing yourself with this new offering on Udemy. Each of the 6 full practice tests in this set provides an entire exam’s worth of questions, enabling you to confirm your mastery of the topics and providing you with the confidence you’ll need to take your Microsoft Azure AI Fundamentals (AI-900) Certification exam.
The tests in this set are timed, so you’ll know when you’re taking more time than the official test allows, and at the end of the test, you’ll receive a personal breakdown of the questions you answered correctly and incorrectly to improve your knowledge and make you more prepared to pass the actual Microsoft exam.
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
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it is not a prerequisite for any of them.
You may be eligible for ACE college credit if you pass this certification exam. See ACE college credit for certification exams for details.
Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; and features of Natural Language Processing (NLP) workloads on Azure.
Welcome to the ultimate practice exams course designed to give you the winning edge in your journey to becoming Microsoft Azure AI Fundamentals - AI-900 certified!
Are you ready to pass the Microsoft Azure AI Fundamentals (AI-900) certification exam? Find out by testing yourself with this new offering on Udemy. Each of the 6 full practice tests in this set provides an entire exam’s worth of questions, enabling you to confirm your mastery of the topics and providing you with the confidence you’ll need to take your Microsoft Azure AI Fundamentals (AI-900) Certification exam.
The tests in this set are timed, so you’ll know when you’re taking more time than the official test allows, and at the end of the test, you’ll receive a personal breakdown of the questions you answered correctly and incorrectly to improve your knowledge and make you more prepared to pass the actual Microsoft exam.
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
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it is not a prerequisite for any of them.
You may be eligible for ACE college credit if you pass this certification exam. See ACE college credit for certification exams for details.
Prove that you can describe the following: AI workloads and considerations; fundamental principles of machine learning on Azure; features of computer vision workloads on Azure; and features of Natural Language Processing (NLP) workloads on Azure.
Mock Tests : Oracle Cloud Infrastructure 2023 AI Foundations Associate 1Z0-1122-23
The Oracle Cloud Infrastructure AI Foundations Associate certification is designed for individuals who intend to demonstrate fundamental knowledge of Artificial Intelligence, Machine Learning, and related services provided by Oracle Cloud Infrastructure (OCI). This certification does not mandate candidates to have data science and software engineering experience, yet familiarity with OCI basics is beneficial. This credential serves as a foundation for other OCI role-based certifications like OCI Data Science Professional or OCI Digital Assistant Professional, even though it is not a prerequisite for any of them.
This is a mock exam bundle of 3 mock exams and have the similar approach in line with actual exam
Question type : Multiple choice or Multi select.
Number of Questions: 15 question (1 test) | 30 Question (2 tests) : Total 75 questions
Duration : 30 minutes (short test) | 60 minutes(full test).
Passing score : 60%
The topics of coverage in the test are
AI Concepts and Workloads
Understand the fundamental AI concepts and workloads
Machine Learning and Deep Learning
Explain the key concepts and terminologies of Machine Learning
Explain the key concepts and terminologies of Deep Learning
Identify common Machine Learning types
Generative AI and Large Language Models
Understand the fundamentals of Generative AI
Explain Large Language Model concepts
Explain the role of prompt engineering and fine-tuning in Generative AI
OCI AI Infrastructure and Services
Describe OCI AI Infrastructure
Describe OCI AI Services
Wish you good luck for certification & career ahead !
Mock Tests : Oracle Cloud Infrastructure 2023 AI Foundations Associate 1Z0-1122-23
The Oracle Cloud Infrastructure AI Foundations Associate certification is designed for individuals who intend to demonstrate fundamental knowledge of Artificial Intelligence, Machine Learning, and related services provided by Oracle Cloud Infrastructure (OCI). This certification does not mandate candidates to have data science and software engineering experience, yet familiarity with OCI basics is beneficial. This credential serves as a foundation for other OCI role-based certifications like OCI Data Science Professional or OCI Digital Assistant Professional, even though it is not a prerequisite for any of them.
This is a mock exam bundle of 3 mock exams and have the similar approach in line with actual exam
Question type : Multiple choice or Multi select.
Number of Questions: 15 question (1 test) | 30 Question (2 tests) : Total 75 questions
Duration : 30 minutes (short test) | 60 minutes(full test).
Passing score : 60%
The topics of coverage in the test are
AI Concepts and Workloads
Understand the fundamental AI concepts and workloads
Machine Learning and Deep Learning
Explain the key concepts and terminologies of Machine Learning
Explain the key concepts and terminologies of Deep Learning
Identify common Machine Learning types
Generative AI and Large Language Models
Understand the fundamentals of Generative AI
Explain Large Language Model concepts
Explain the role of prompt engineering and fine-tuning in Generative AI
OCI AI Infrastructure and Services
Describe OCI AI Infrastructure
Describe OCI AI Services
Wish you good luck for certification & career ahead !
Thank you for your interest in this course!
Salesforce is on the cutting edge of Artificial Intelligence and has a new associate certification for you to show your knowledge! Artificial Intelligence, especially in business, can be daunting. We cover AI for CRM to get you caught up on all you need to know!
In this course, we cover all of the necessities to pass the Salesforce AI associate Certification, with absolutely no fluff! Easily and quickly getting you Salesforce Certified.
You can be confident in taking the Salesforce AI Associate Certification after learning these concepts, learning the key terms, and working through practice questions.
Easily get certified through this streamlined course with the following resources:
Complete video lectures covering all exam topics.
Demoed solutions and practice questions after every section.
Comprehensive glossary of all terms you need to know with links to learn more.
A full practice exam formatted like the actual exam with explanations and documentation links.
Notes on the 52 trailhead modules that make up this Trailmix.
Learn how to leverage AI with Salesforce and increase your productivity.
We are excited to see you pass the Salesforce AI Associate Certification and celebrate both your Salesforce and AI wins!
Thank you for your interest in this course!
Salesforce is on the cutting edge of Artificial Intelligence and has a new associate certification for you to show your knowledge! Artificial Intelligence, especially in business, can be daunting. We cover AI for CRM to get you caught up on all you need to know!
In this course, we cover all of the necessities to pass the Salesforce AI associate Certification, with absolutely no fluff! Easily and quickly getting you Salesforce Certified.
You can be confident in taking the Salesforce AI Associate Certification after learning these concepts, learning the key terms, and working through practice questions.
Easily get certified through this streamlined course with the following resources:
Complete video lectures covering all exam topics.
Demoed solutions and practice questions after every section.
Comprehensive glossary of all terms you need to know with links to learn more.
A full practice exam formatted like the actual exam with explanations and documentation links.
Notes on the 52 trailhead modules that make up this Trailmix.
Learn how to leverage AI with Salesforce and increase your productivity.
We are excited to see you pass the Salesforce AI Associate Certification and celebrate both your Salesforce and AI wins!