
I’ve designed this course to give you everything you need to prepare and pass confidently the AWS Certified AI Practitioner (AIF-C01) exam — No need to look beyond this course.
The course includes in-depth video lectures, section-wise Exam Essentials revision lectures, section quizzes, and 2 full-length practice tests to help you assess your readiness.
And when you’re ready for your final revision, you’ll have an Exam Essentials Guide containing the key concepts, important points, and exam-focused takeaways covered throughout the course. Use it for a quick and focused revision before your exam.
So, No endless whitepapers. No searching through countless videos. No jumping between different resources. Everything you need for your AI Practitioner exam preparation is brought together in one complete course.
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)
Downloads:
Download Full course slides
Download Exam Essentials guide
Download 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 Download
A 30-Day "No Questions Asked" Money Back Guarantee!