YoVDO

AWS Flash - AWS AI/ML Essentials (GCR Only)

Offered By: Amazon Web Services via AWS Skill Builder

Tags

Amazon Web Services (AWS) Courses Artificial Intelligence Courses Machine Learning Courses Prompt Engineering Courses Generative AI Courses Responsible AI Courses Foundation Models Courses AI Governance Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!

This course is aimed at technicians who need to take the AWS Certified AI Practitioner (AIF-C01) certification exam. Through studying this course, they understand the certification exam process and precautions. It helps students strengthen their understanding and mastery of the knowledge points within the scope of the certification exam. At the same time, with the help of analysis and explanation of sample questions, they can better understand and familiarize themselves with the difficulty factor and exam format of the certification exam.

  • Levels: Intermediate
  • Teaching method: Digital training, video, and question analysis
  • Durations: 4.25h


Course Objectives

In this course, you'll learn:

  • Introduction to certification exams and exam notes
  • Fundamentals of AI and ML, explain basic AI concepts and terminologies, identify practical use cases for AI, describe the ML development lifecycle
  • Fundamentals of Generative AI, explain the basic concepts of generative AI, understand the capabilities and limitations of generative AI for solving business problems, describe AWS infrastructure and technologies for building generative AI applications
  • Applications of Foundation Models, describe design considerations for applications that use foundation models, choose effective prompt engineering techniques, describe the training and fine-tuning process for foundation models, describe methods to evaluate foundation model performance
  • Guidelines for Responsible AI, explain the development of AI systems that are ethical and fair, recognize the importance of transparent and explainable models
  • Security, Compliance, and Governance for AI Solutions, Explain methods to secure AI systems, recognize governance and compliance regulations for AI systems
  • Assess gaps in your knowledge of exam topics and confirm your exam preparation


Target audience

This course is aimed at the following people:

  • Business analyst, IT support, marketing professional, product or project manager, line-of-business or IT manager, sales professional
  • The target candidate has up to 6 months of exposure to AI/ML technologies on AWS. Individuals who are familiar with, but do not necessarily build, solutions using AI/ML technologies on AWS
  • Preparing for the AWS Certified AI Practitioner (AIF-C01) certification exam


Requisites

We recommend that students take the following courses (or similar) before attending this course:

  • Gen AI Fundamental for Business Professionals
  • Generative AI for Executives


Course Outline

Module 1: Introduction to certification exams

Section 1: Introduction to AWS Certification

  • Categories of AWS Certifications

Section 2: Certification Exam Overview

  • Exam format
  • Exam length
  • Exam passing score
  • Exam notes


Module 2: Fundamentals of AI and ML

Section 1: Review of Key Knowledge Points

  • Explain basic AI concepts and terminologies
  • Identify practical use cases for AI
  • Describe the ML development lifecycle

Section 2: Explanation of sample questions


Module 3: Fundamentals of Generative AI

Section 1: Review of Key Knowledge Points

  • Explain the basic concepts of generative AI
  • Understand the capabilities and limitations of generative AI for solving business problems
  • Describe AWS infrastructure and technologies for building generative AI applications

Section 2: Explanation of sample questions


Module 4: Applications of Foundation Models

Section 1: Review of Key Knowledge Points

  • Describe design considerations for applications that use foundation models
  • Choose effective prompt engineering techniques
  • Describe the training and fine-tuning process for foundation models
  • Describe methods to evaluate foundation model performance

Section 2: Explanation of sample questions


Module 5: Guidelines for Responsible AI

Section 1: Review of Key Knowledge Points

  • Explain the development of AI systems that are ethical and fair
  • Recognize the importance of transparent and explainable models

Section 2: Explanation of sample questions


Module 6: Security, Compliance, and Governance for AI Solutions

Section 1: Review of Key Knowledge Points

  • Explain methods to secure AI systems
  • Recognize governance and compliance regulations for AI systems

Section 2: Explanation of sample questions


Module 7: Course Summary


Tags

Related Courses

AI Concepts and Strategy
Rutgers University via Coursera
Amazon Bedrock - Getting Started with Generative AI
Amazon Web Services via Coursera
Amazon Bedrock Getting Started (Japanese)
Amazon Web Services via AWS Skill Builder
Amazon SageMaker JumpStart Foundations
Amazon Web Services via AWS Skill Builder
Amazon SageMaker JumpStart Foundations (Japanese)
Amazon Web Services via AWS Skill Builder