AWS Certified AI Practitioner (AIF-C01)- Full Course & Tests

By Architect @ AWS | 100% Exam Coverage | 30+ Demos | 150+ Section Quiz | 2 Full Practice Tests & Exam Revision Guide
What you'll learn

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Prepare confidently for the AWS Certified AI Practitioner (AIF-C01) certification exam.
Understand the fundamentals of AI, Machine learning, and Generative AI.
Understand Foundation models, Promp engineering, RAG, Model customization, Model evaluation and AI agents.
Learn and experience AWS Services used for AI, ML and Generative AI
Understand Responsible AI, AI Security, Compliance, and Governance considerations.
Requirements

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No prior AI or machine learning experience is required.
Description

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I believe thata strong technical foundation is the key to a successful career, and the foundation must be built right. This course primarily focuses on getting you AWS AI Practitioner certified but the concepts that you will learn will stay with you and guide you for the rest of your career. I have tried to strike right balance between what exam requires you to know and what's important for your career.
So try to get the most out of this course. All the best!
~Chetan
About this course
This course provides you everything to pass your AWS Certified AI Practitioner - Foundational Exam (AIF-C01)
This course contains 12hrs of detailed lectures including 30+ demonstrations and walkthroughs to make sure that you understand the concepts to its core. Also, this is a COMPLETE course which means I won't ask you to go through any other videos, white-papers or documentation.
No prior IT or Cloud or AI experience required.This course can be taken by absolute beginners including students.
Only thing required to complete this course and pass your exam is -Your sincere efforts and dedication.
Course topics
Domain 1 - Fundamentals of AI and Machine Learning
AI, ML, Deep Learning and Generative AI
How Machines learn?
Machine Learning Lifecycle - Business Problem -> ML Problem Framing -> Data Collection -> Data Preparation -> Model Training -> Model Evaluation -> Model Inference and Model Optimization
AWS AI Services - Rekognition, Polly, Transcribe, Translate, Textract, Comprehend, Personalize, Forecast, Kendra, Lex
Amazon SageMaker AI
Data Wrangler, Ground Truth & Feature Store, SageMaker Studio, Canvas & JumpStart
SageMaker Training Jobs
SageMaker Endpoints - Real-time, Batch Transform, Asynchronous, Serverless
SageMaker Clarify, SageMaker Model Monitor, Model Cards and Model Registry
SageMaker Pipelines, Mlflow and SageMaker Autopilot (MLOps)
Domain 2 - Fundamentals of Generative AI
Foundation Models (FMs) and Large Language Models (LLMs)
Transformer Architecture
Prompt Engineering
Vector Embedding and Retrieval Augmented Generation (RAG)
Domain 3 - Applications of Foundation Models
Amazon Bedrock
Foundation Model (FM) catalog in Bedrock
Bedrock Guardrails
Bedrock Monitoring and Logging
Bedrock Pricing (old and new)
Prompt Engineering and RAG in Amazon Bedrock
Prompt Engineering & components of a Prompt
Prompt Techniques - Zero shot, Few shots, Chain-of-thought, ReAct & Negative prompting
Model response optimization parameters - Temperature, Top-K, Top-P, Stop sequence
Prompt templates
Prompt attacks
Amazon Bedrock Knowledge Bases (RAG)
Amazon Bedrock Vector Databases - Amazon OpenSearch, Amazon Aurora, Amazon Neptune, S3 Vectors
Customizing Foundation Models
Transfer Learning, Model Fine-tuning & Model Continued-Pretraining
Amazon SageMaker Jumpstart
Model Distillation (Teacher -> Student models)
Small Language Models (SLMs) and Edge deployment
Foundation Model Evaluation
Business Metrics - User/Customer satisfaction, Avg response time, Conversion rate etc.
Technical Metrics - Accuracy, Robustness, Toxicity, Fairness, BLEU, ROUGE, BERTScore and more
FM Evaluation Methods - Automated Evaluation, LLM-as-Judge, Human-based review
BLEU Score, ROUGE & BERTScore
AI Agents
Why AI Agents?
Demo - Banking Assistant Chatbot vs AI Agent
AI Agent Frameworks - LangGraph, LangChain, CrewAI, Strands, AutoGen etc.
Amazon Bedrock Agent (Classic)
Amazon Bedrock AgentCore (New)
AgentCore components - Runtime, Harness, Gateway, Memory, Identity, Browser and more.
Agent Communication - MCP (Model Context Protocol) and A2A (Agent-to-Agent)
AWS Generative AI Application Services
Amazon Q - Amazon Q Developer, Q in Console, Q in Connect
Amazon Quick Suite (Formerly Amazon QuickSight + Amazon Q Business)
Amazon Quick Modules - Chat/Agents, Index, Research, Flows, Automate, Apps etc.
AWS DevOps Agent, AWS Security Agent, AWS Kiro Agent (Coding assistant)
AWS Party Rock
Domain 4 - Guidelines for Responsible AI
What is Responsible AI and why its important?
Responsible AI Features and Dimensions - Fairness, Explainability, Transparency and more
Common Risks and challenges of AI - Bias, Variance, Hallucination, Toxicity, Plagiarism, Nondeterminism & more
AI Model Interpretability vs Complexity Trade-offs
AWS Services and Tools for Responsible AI
AI Service Cards
Amazon Bedrock Guardrails
Amazon SageMaker Clarify
Amazon Augmented AI (A2I)
Responsible AI Best Practices
Domain 5 - Security, Compliance, and Governance for AI Solutions
AWS Services/Features for AI Security
Access and Permissions - AWS IAM
Network Security - AWS VPC, PrivateLink
Data Security - Amazon S3 Bucket Policy, Amazon KMS, Amazon Macie
AI Agent Security - AgentCore Identity, AgentCore Policy, AWS IAM
AWS Services/Features for AI Governance and Compliance
AWS Config
AWS CloudTrail
Amazon Inspector
AWS Trusted Advisor
AWS Artifact
AWS Audit Manager
AI Service Cards and SageMaker Model Cards
Additional Topics
Secure Data Engineering
AI response Grounding Techniques
AWS Generative AI Scoping Matrix
+ Section Quizzes (~150 questions)
Practice Tests
Full Practice Test 1 - Exam level (65 questions)
Full Practice Test 2 - Challenging level (65 questions)
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Full course slides
Exam Essentials guide
Exam Cheat Sheet
This course also comes with
Lifetime access to all future updates
A responsive instructor in the Q&A Section
Udemy Certificate of Completion Ready for
A 30-Day "No Questions Asked" Money Back Guarantee!
Who this course is for

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Anyone preparing for the AWS Certified AI Practitioner (AIF-C01) exam.
Students and Cloud Beginners looking to start their journey into AI and cloud technologies.
Business and Product Professionals who want to understand AI/GenAI concepts, capabilities, use cases, and risks.
AWS and Cloud Professionals who want to build foundational AI/ML and Generative AI knowledge.
Homepage

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