Free Master Class on AWS Certified AI Practitioner (Technical Essentials)
Are you ready to take your first step into AI with AWS? Now is the time to prepare and stay ahead in this AI-driven era.

Course Description

AWS Certified Cloud Practitioner focuses on overall knowledge of AWS Cloud and gives a foundational-level overview of all AWS services. AWS Certified AI Practitioner covers the breadth of AI frameworks, concepts, and associated AWS technologies, with an emphasis on generative AI.

Schedule: 20 August (Wednesday) 2025 at 7 pm IST

To Register:

Fees: NILL

Course Outline.Agenda:

#1: Introduction to Cloud & AWS
Why Cloud? Real-world examples (Startups, Gaming, AI/ML)
Cloud Models: IaaS, PaaS, SaaS
AWS Global Infrastructure: Regions, Availability Zones, Edge Locations
Hands-on: Sign up for AWS Free Tier, Explore AWS Management Console, Explore AWS AI/ML Services

#2: AWS Overview
Introduction to Amazon Web Services (AWS)
Key AWS services and their use cases
Understanding the AWS global infrastructure

#3: Cost Awareness & Free Tier
AWS Free Tier Overview
Budget Controls & Cost Management Tools
Hands-on: Set a Billing Alarm to Avoid Overcharges

#4:Security & Identity Management, Compliances in AWS for AI/ML
AWS Shared Responsibility Model
IAM Basics: Users, Groups, Policies (IAM for AI services)
Multi-Factor Authentication (MFA) and Best Practices
Hands-on: Create Student IAM User with Limited and Full Access

#5: Core AWS Services: (Compute for AI)
Amazon EC2: Instance Types, AMIs, Security Groups, AWS Custom Chips: AWS Trainium, AWS Inferentia
AWS CPU/GPU Instances for AI/ML: P4/P5/G4/G5/Inf1/Inf2/Trn1/Trn2, M7i/C7i
Hands-on:Launch an EC2 (Windows/Linux) Instance, Connect via SSH

#6: AI/ML Fundamentals
What is Artificial Intelligence, Machine Learning and Deep Learning?
Types of ML: Supervised, Unsupervised, Reinforcement
Real-world applications: (Speach, Vision, NLP)

#7: Overview of the AWS/ML Stack
Three layers of the AWS AI/ML Stack
AI Services (Pre-trained), ML Services (SageMaker, Frameworks and Infrastructure)
Use cases per service type.

#8: AWS AI Services (Pre-trained services that abstract ML) Use cases and Capabilities
Computer Vision: Amazon Rekognition: Use cases: Object detection, face analysis, moderation
Natural Language: Amazon Comprehend & Translate: Use cases: Sentiment, key phrases, entity recognition
Conversational AI: Amazon Lex : Use cases: Chatbots, call centers Speech Services: Amazon Polly & Transcribe: Polly: Text-to-speech, Transcribe: Generative AI with Foundation Models: Amazon Bedrock: Build and deploy generative AI applications using leading foundation models (Claude, Llama, Mistral, Titan, etc.)

#9: Machine Learning on AWS (SageMaker) ML Services and Tools
What is SageMaker and where it fits
SageMaker Autopilot and JumpStart overview
Use cases: Build/train/deploy models without deep ML knowledge

A MasterClass Participation certificate will be issued for all attendees.

For clarifications email: hello@graphitenetworks.in