AWS Certified AI Practitioner
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Understand AI Fundamentals
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Identify Business Opportunities
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Plan & Execute Projects
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Evaluate Impact & Ethics
60 Hours
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Beginner level
No Prior Knowledge Required
Flexible Learning
Available in Online, Offline, and
Hybrid Modes
60 Hours
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Program Overview
The AWS Certified AI Practitioner (AIF-C01) certification validates your foundational understanding of artificial intelligence (AI), machine learning (ML), and generative AI, especially in AWS contexts.
This program (or prep track) is ideal for IT professionals, data analysts, business leaders, or aspiring AI practitioners who want to leverage AWS AI/ML services and demonstrate competence in designing and implementing AI solutions.
This program (or prep track) is ideal for IT professionals, data analysts, business leaders, or aspiring AI practitioners who want to leverage AWS AI/ML services and demonstrate competence in designing and implementing AI solutions.
Key Features
Aligned with official AWS AI Practitioner exam objectives (AIF-C01)
Hands-on labs and real AWS AI/ML services (e.g. SageMaker, Comprehend, Rekognition)
Focus on generative AI & responsible AI practices
Instruction + exam prep sessions + practice questions
Flexible delivery (self-paced / instructor-led / hybrid)
Certificate of completion or official AWS certification
Emphasis on applying AI/ML in real business / AWS use cases
Skills Covered
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AI Fundamentals: Understanding the basics of generative AI and its applications
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Content Generation: Creating text, images, and videos using AI tools
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Automation: Streamlining content creation processes with AI
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Personalization: Tailoring content to specific audiences using AI insights
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Ethical Considerations: Understanding the ethical implications of using AI in content creation
Course Curriculum
Certification & AI Foundations
Module 1 • 10 hour to complete
Module 1 • 10 hour to complete
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Course Orientation & Exam Details
• AWS AI Practitioner Certification Roadmap
• Cloud, AI, ML, and DL: Key Concepts & Differences
• Neural Networks, Computer Vision, and NLP Basics
• Business Applications and When (Not) to Use AI
• Quiz: Core AI & ML Concepts
• AWS AI Practitioner Certification Roadmap
• Cloud, AI, ML, and DL: Key Concepts & Differences
• Neural Networks, Computer Vision, and NLP Basics
• Business Applications and When (Not) to Use AI
• Quiz: Core AI & ML Concepts
Machine Learning Fundamentals
Module 2 • 10 hour to complete
Module 2 • 10 hour to complete
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Data Types and ML Process Overview
• Learning Approaches: Supervised, Unsupervised, Semi-Supervised, Reinforcement
• Inference and Deployment Options
• Value-Adding AI Applications Across Industries
• Quiz: ML Foundations
• Learning Approaches: Supervised, Unsupervised, Semi-Supervised, Reinforcement
• Inference and Deployment Options
• Value-Adding AI Applications Across Industries
• Quiz: ML Foundations
AWS AI Managed Services
Module 3 • 10 hour to complete
Module 3 • 10 hour to complete
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Amazon Rekognition (Vision AI)
• Amazon Transcribe & Translate (Speech & Language)
• Amazon Comprehend & Amazon Lex (NLP & Conversational AI)
• Amazon Polly (Text-to-Speech)
• Business AI: Personalize, Kendra, Textract, Forecast, Fraud Detector
• Human-in-the-Loop: Mechanical Turk & Augmented AI (A2I)
• Quiz: AWS AI Managed Services
• Amazon Transcribe & Translate (Speech & Language)
• Amazon Comprehend & Amazon Lex (NLP & Conversational AI)
• Amazon Polly (Text-to-Speech)
• Business AI: Personalize, Kendra, Textract, Forecast, Fraud Detector
• Human-in-the-Loop: Mechanical Turk & Augmented AI (A2I)
• Quiz: AWS AI Managed Services
Amazon SageMaker & MLOps Essentials
Module 4 • 10 hour to complete
Module 4 • 10 hour to complete
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SageMaker Overview & Key Features
• ML Development Lifecycle (Data, Training, Deployment, Monitoring
• MLOps Fundamentals & Pipelines
• Built-in Algorithms & Model Sources
• Performance Metrics: Technical & Business Perspectives
• Quiz: SageMaker & ML Lifecycle
• ML Development Lifecycle (Data, Training, Deployment, Monitoring
• MLOps Fundamentals & Pipelines
• Built-in Algorithms & Model Sources
• Performance Metrics: Technical & Business Perspectives
• Quiz: SageMaker & ML Lifecycle
Generative AI Fundamentals
Module 5 • 10 hour to complete
Module 5 • 10 hour to complete
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Foundation Models (FMs) & Large Language Models (LLMs)
• Tokens, Embeddings, Vectors Explained
• Multimodal & Diffusion Models
• Foundation Model Lifecycle
• Business Value Assessment & Limitations of Generative AI
• Quiz: Generative AI Basics
• Tokens, Embeddings, Vectors Explained
• Multimodal & Diffusion Models
• Foundation Model Lifecycle
• Business Value Assessment & Limitations of Generative AI
• Quiz: Generative AI Basics
AWS GenAI Toolkit
Module 6 • 10 hour to complete
Module 6 • 10 hour to complete
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Amazon Bedrock Overview & Service Menus
• Using Bedrock Playgrounds for Models
•Bedrock Guardrails, Safeguards & Inference Controls
•PartyRock for Prototyping GenAI Apps
•SageMaker JumpStart for Hugging Face & Open-Source Models
•Amazon Q (Business & Developer) for Enterprise AI
•Cost Considerations for AI/ML Workloads
•Quiz: AWS GenAI Services
• Using Bedrock Playgrounds for Models
•Bedrock Guardrails, Safeguards & Inference Controls
•PartyRock for Prototyping GenAI Apps
•SageMaker JumpStart for Hugging Face & Open-Source Models
•Amazon Q (Business & Developer) for Enterprise AI
•Cost Considerations for AI/ML Workloads
•Quiz: AWS GenAI Services
Applied Generative AI & RAG
Module 7 • 10 hour to complete
Module 7 • 10 hour to complete
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Foundation Model Selection Criteria
• Inference Parameters (Temperature, Top-K, Top-P, Input/Output Length)
•Retrieval-Augmented Generation (RAG) Concepts & Use Cases
•Amazon Bedrock Knowledge Bases & Vector Databases
•Agents in Bedrock for Multi-Step Tasks
•Quiz: Advanced GenAI Applications
• Inference Parameters (Temperature, Top-K, Top-P, Input/Output Length)
•Retrieval-Augmented Generation (RAG) Concepts & Use Cases
•Amazon Bedrock Knowledge Bases & Vector Databases
•Agents in Bedrock for Multi-Step Tasks
•Quiz: Advanced GenAI Applications
Prompt Engineering & AI Risks
Module 8 • 10 hour to complete
Module 8 • 10 hour to complete
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Introduction to Prompt Engineering
• Techniques for Quality, Specificity & Context Control
•Common AI Vulnerabilities: Injection, Poisoning, Jailbreaking
•Mitigation Strategies for Secure AI Use
•Quiz: Prompt Engineering & AI Risks
• Techniques for Quality, Specificity & Context Control
•Common AI Vulnerabilities: Injection, Poisoning, Jailbreaking
•Mitigation Strategies for Secure AI Use
•Quiz: Prompt Engineering & AI Risks
Fine-Tuning & Customization
Module 9 • 10 hour to complete
Module 9 • 10 hour to complete
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Fine-Tuning Methods for Foundation Models
• Data Preparation for Fine-Tuning
•Cost & Implementation Considerations
•Practical Applications of Customized Models
•Quiz: Fine-Tuning & Model Adaptation
• Data Preparation for Fine-Tuning
•Cost & Implementation Considerations
•Practical Applications of Customized Models
•Quiz: Fine-Tuning & Model Adaptation
Exam Readiness & Career Pathways
Module 10 • 10 hour to complete
Module 10 • 10 hour to complete
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Practice Questions & Mock Exam Review
• Exam Guide & Domain Alignment
•Study Resources & Success Strategies
•AWS Certification Paths After AI Practitioner
•Career Roles: AI Practitioner, ML Engineer, GenAI Specialist
• Exam Guide & Domain Alignment
•Study Resources & Success Strategies
•AWS Certification Paths After AI Practitioner
•Career Roles: AI Practitioner, ML Engineer, GenAI Specialist
Tools & Technologies
Completion Certificate
Job Role
- AI / ML Engineer
- AI / ML Solutions Architect
- AI / ML Developer
- Business / Data Analyst
- AI / ML Consultant
- Prompt Engineer
- AI / ML Support Engineer
Training Option
OFFLINE
₹7777
- 24/7 support
- 24/7 support
- 24/7 support
ONLINE
₹5555
- 24/7 support
- 24/7 support
- 24/7 support
HYBRID
₹6666
- 24/7 support
- 24/7 support
- 24/7 support
Why Join this Program
Earn a job
Receive complete job assistance tailored to your career goals. Get expert placement guidance to confidently step into the industry.
Leverage knowledge from industry experts
Learn directly from seasoned Trainers and Gain real-world insights that go beyond textbooks.
Industry-relevant Tools & Practical Learning
Get hands-on experience with the latest tools used by top companies. Hands-on learning through 200+ exercises and 10+ projects with seamless access to integrated labs.
Structured, industry-vetted curriculum
A curriculum shaped by experts to meet evolving industry demands. Structured learning ensures you're career-ready from day one.
Integrated with Gen AI Modules
The curriculum includes cutting-edge Generative AI modules designed to align with emerging tech trends.
Interview preparation & Placement assistance
Sharpen your interview skills with practical training and expert guidance. Receive complete placement support to connect with top recruiters.
FAQ
Basic Python is enough; we cover everything from scratch.
No — this course teaches ML fundamentals too.
Absolutely — this is designed for career transition.
You’ll need to put in extra effort, but many succeed.
Yes — the curriculum includes real-world LLM integration.
Yes — including techniques used by AI professionals.