Who is this for?
Students, business and technical professionals, and anyone who wants AI literacy on AWS. No coding required.
Syllabus
1. AI and ML Fundamentals (5 h)
- AI vs ML vs deep learning
- Supervised, unsupervised and reinforcement learning
- Data, features and model training
- Model evaluation metrics
- Hands-on: Explore SageMaker Canvas with a sample dataset
2. The ML Development Lifecycle (4 h)
- Data collection and preparation
- Training, tuning and deployment
- MLOps concepts
- Monitoring and drift
- Hands-on: Walk through a SageMaker pipeline
3. AWS AI Services (5 h)
- Vision: Rekognition, Textract
- Language: Comprehend, Translate, Transcribe, Polly, Lex
- Personalization and forecasting
- Choosing managed AI services
- Hands-on: Try Rekognition and Comprehend
4. Generative AI Fundamentals (5 h)
- Foundation models and LLMs
- Tokens, embeddings and context
- Amazon Bedrock and Amazon Q
- Prompt engineering basics
- Hands-on: Prompt experiments in the Bedrock playground
5. Applications of Foundation Models (4 h)
- Retrieval-Augmented Generation (RAG)
- Fine-tuning vs prompting
- Evaluating model output
- Agents overview
6. Responsible AI, Security and Governance (4 h)
- Bias, fairness, transparency and explainability
- Data privacy and security on AWS
- Compliance and governance
- Guardrails
7. Exam Preparation (3 h)
- Exam format and strategy
- Domain revision
- Mock test with review
- Hands-on: Mock test
After this course you will be able to
- Explain core AI, ML and deep-learning concepts
- Describe the ML lifecycle and common AWS AI/ML services
- Understand generative AI, foundation models and prompt engineering
- Apply responsible-AI, security and governance principles
- Choose the right AWS AI service for a business use case
Tools & topics
Amazon SageMakerAmazon BedrockAmazon QRekognitionComprehendTranscribePolly
Projects
- AI use-case recommendation report
- Prompt-engineering playbook
Assessment
Module quizzes and a full-length mock exam.
What is included
- Live instructor-led online sessions
- Hands-on labs and assignments
- Session recordings after each class
- Doubt-solving support
- Course completion certificate
- Small interactive batches
- Unpaid internship opportunities
- Session recordings after each class
- Small interactive batches
- Unpaid internship opportunities for practical exposure
Your trainer
Ameya Vaidya
Cloud Trainer: AWS, Azure & GCP
Ameya started in IT more than 16 years ago and has spent over a decade in the cloud. He holds six AWS and two Azure certifications, is an AWS Community Builder and a speaker, and has trained over 5,000 students. Ask him about security, networking or AI and expect real-world examples alongside the theory.
- 6 AWS and 2 Azure certifications
- 16+ years in IT, 10+ years in cloud
- Expertise in security, networking and AI
- Trained 5,000+ students
- AWS Community Builder and speaker
What our AWS AI Practitioner students say
FAQ
Can a beginner join AWS AI Practitioner?
Yes. There are no prerequisites. Basic cloud awareness helps (Cloud Practitioner recommended).
Will there be a free demo?
Yes. Book a free demo, attend the live session and decide after you have seen how we teach.
Do you guarantee a job after this course?
No. We do not make guaranteed-placement claims. We train you to be capable, help with resume and career guidance, and offer unpaid internship opportunities.
What is the fee and batch schedule?
Our counselor shares the current fee and batch details. Book a free demo or WhatsApp +91-9156091020.
Not sure which course is right for you?
Talk to our counselor. It is free, and we will tell you honestly whether a course fits your goals.