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AWS AI & Gen AI Engineer Certification Training

4.7/5
Google Reviews
4.7/5
ScholarHat Reviews
Watch Course Preview
Course Preview
12 Sessions
Live Classes
54 Videos
Video Course
33 Notes
Quick Notes
20 Labs
Hands-on Labs
2 Project(s)
Learn to implement
7 Tests
Skill Tests
24 Guides
Interview Q&A

AWS AI Engineer Certification Training Overview

AWS AI Engineer Certification is a prestigious credential for developers, data specialists, and solution architects aspiring to design and deploy intelligent, cloud-based solutions using Amazon Web Services (AWS). As enterprises increasingly adopt AI and Generative AI to enhance automation, customer engagement, and decision-making, the demand for skilled AWS AI Engineers continues to grow.

ScholarHat’s AWS AI Engineer Course empowers you with the knowledge and hands-on skills to design, train, and deploy AI and GenAI solutions at scale. Learn to build real-world AI applications using Amazon Bedrock, Amazon SageMaker, Amazon Comprehend, Amazon Rekognition, Amazon Lex, and other cutting-edge AWS AI services. Whether you're preparing for the AWS Certified Generative AI Engineer – Professional exam or looking to strengthen your AI engineering expertise, this course offers structured lessons, expert mentorship, and practical labs to help you succeed.

AWS AI Engineer Course Objectives

After completing this course, participants will be able to:

Master AWS AI and Generative AI concepts aligned with the AWS Certified Generative AI Engineer – Professional exam
Design and deploy machine learning and generative AI solutions using Amazon SageMaker and Bedrock
Use Amazon Comprehend for natural language processing, sentiment analysis, and text classification
Build and deploy conversational AI chatbots using Amazon Lex integrated with enterprise systems
Leverage Amazon Rekognition for computer vision applications such as image and video analysis
Integrate foundation models (FMs) and LLMs using Amazon Bedrock with agents, RAG, and prompt engineering
Secure and govern AI applications using AWS Identity and Access Management (IAM) and Responsible AI principles
Automate AI workflows with Amazon Step Functions and integrate with AWS Lambda for serverless AI pipelines
Monitor, debug, and optimize deployed AI workloads using Amazon CloudWatch and SageMaker Model Monitor
Prepare for the AWS Generative AI Certification with hands-on labs, mock tests, and real-world projects

Training Outcomes

  • 1. Design and deploy intelligent, scalable AI and GenAI solutions on AWS Cloud
  • 2. Gain hands-on expertise with AWS AI tools like Bedrock, SageMaker, Comprehend, Rekognition, and Lex
  • 3. Confidently prepare for the AWS Certified Generative AI Engineer – Professional exam
  • 4. Develop and deploy enterprise-ready AI applications with responsible AI practices
  • 5. Advance your career as an AWS AI Engineer and become an expert in cloud-based AI development

Why Become an AWS AI Engineer in 2026?

1.) High Demand:  Over 85% of enterprises now leverage AI on the cloud, and AWS leads with 35% market share in AI and machine learning workloads — powering solutions across finance, healthcare, e-commerce, and manufacturing. (Gartner, 2024)

2.) Attractive Compensation:  AWS AI Engineers command some of the highest salaries in the cloud domain:

  • US: $120,000 – $170,000 per year.
  • India: ₹18,00,000 – ₹35,00,000 annually.

3.) Career Growth Opportunities:  With the AWS AI Engineer Certification and the new Generative AI Engineer – Professional track, professionals can pursue top-tier roles like AI Engineer, Machine Learning Engineer, Data Scientist, and AI Solutions Architect at leading companies such as Amazon, Netflix, NVIDIA, and Deloitte.

4.) Work on Cutting-Edge Technologies:  AWS AI Engineers work with state-of-the-art tools like Amazon Bedrock, Amazon SageMaker, Amazon Comprehend, Amazon Rekognition, and Amazon Lex to build intelligent applications and Generative AI systems across diverse industries.

5.) Job Stability and Growth:  The global AI market is expected to exceed $407B by 2027, with AWS AI-related roles growing at a 38% year-over-year rate. This ensures strong career stability and accelerated professional growth in the AWS AI ecosystem.


No.1

Cloud AI Platform Worldwide

~6.2M

Websites and Apps use AWS Cloud

250+

AI & ML Services on AWS

~35 LPA

AWS AI Engineer Salary

~3.2M

AI Career Opportunities in AWS Cloud

~48.5%

Growth in Global Gen AI Market

AWS AI Engineer Career Scope

AWS AI Engineer
AI Engineer
AWS AI Architect
AI Architect
AI Lead
₹12 LPA
Avg package
35%
Avg hike
3,200+
Transitions
78%
Demand
Annual Salaries (₹)
₹15 LPA
Avg package
38%
Avg hike
3,200+
Transitions
75%
Demand
Annual Salaries (₹)
₹20 LPA
Avg package
40%
Avg hike
3,200+
Transitions
72%
Demand
Annual Salaries (₹)
₹24 LPA
Avg package
45%
Avg hike
3,200+
Transitions
75%
Demand
Annual Salaries (₹)
₹42 LPA
Avg package
80%
Avg hike
6,000+
Transitions
99%
Demand
Annual Salaries (₹)

Tools and Technologies Covered

Sage Maker
Bedrock
Rekognition
Open Search
Personalize
Textract
Polly
Comprehend
Kendra
Open Search
Kendra
LLMs
LLama Model
Claude
ChatGPT

AWS AI Engineer Certification Training Key Features

6 Weeks of Intensive Live Training

Interactive sessions with real-time problem solving

Learn from AWS Experts

Training by globally recognized experts

Build AWS AI based Projects

Hands-on project for your portfolio

Hands-On Labs

Practice real scenarios with guided, interactive labs

Interview Q&A

Frequently asked interview questions with clear answers

Quick Notes

Concise revision notes for fast and effective learning

Book a FREE Career Growth Session

Course Curriculum

Python For AI Development

Python Foundations

  1. Introduction to Python
  2. Variables and Data Types
  3. Operators
  4. Conditional Statements and Loops
  5. Functions & Classes
  6. Dictionaries and Sets
  7. Modules and File Handling

Python Libraries

  1. Pandas
  2. Numpy
  3. Matplotlib
  4. Pydantic
  5. Uv Package Manager
  6. FastAPI
  7. Building REST APIs
  8. Database Operations
AI Foundations with AWS

AI Foundations

  1. Introduction to Artificial Intelligence
  2. Understanding Machine Learning
  3. Types of Machine Learning
  4. Introduction to Deep Learning
  5. Machine Learning vs Deep Learning
  6. Introduction to Generative AI
  7. Introduction to Large Language Models (LLMs)
  8. AWS AI and ML Services Overview
  9. AWS AI Workloads & Use Cases
  10. Responsible AI Principles
  11. AI Practitioner & Generative AI Certification Overview

Working with AWS AI Services

  1. Setting up AWS AI Services
  2. AWS AI Service Deployment Options
  3. Consuming AWS AI Services via Console, SDK, and API
  4. Using AWS SDK (Boto3) for AI Operations
  5. Securing AWS AI Services with IAM
  6. Managing AI Costs and Budgets
AWS Cognitive and Vision AI Services

Computer Vision with AWS

  1. Introduction to Amazon Rekognition
  2. Image and Video Analysis with Rekognition
  3. Face Detection, Comparison, and Analysis
  4. Object and Scene Detection
  5. Optical Character Recognition (OCR) with Textract
  6. Custom Vision Models using Amazon Lookout for Vision

Natural Language Processing with AWS

  1. Amazon Comprehend Overview
  2. Sentiment Analysis and Key Phrase Extraction
  3. Named Entity Recognition (NER)
  4. Language Detection and Translation with Amazon Translate
  5. Building Q&A Systems with Amazon Lex and Comprehend
  6. Custom Classification and Entity Recognition

Document Intelligence with AWS

  1. Extract Structured Data with Amazon Textract
  2. Automating Document Processing Workflows
  3. Integrating Textract with Comprehend for Intelligent Extraction
  4. Building End-to-End Document AI Pipelines
Amazon Bedrock and Kendra

Amazon Bedrock (Generative AI)

  1. Introduction to Amazon Bedrock
  2. Overview of Foundation Models (Claude, Titan, Llama, Mistral)
  3. Fine-Tuning and Prompt Engineering in Bedrock
  4. Implementing Retrieval-Augmented Generation (RAG)
  5. Image Generation with Stability AI (via Bedrock)
  6. Prompt Design and Optimization Principles
  7. Deploying Bedrock Models in Applications

Intelligent Search with Amazon Kendra

  1. Introduction to Amazon Kendra
  2. Architecture and Core Components
  3. Data Sources, Crawlers, and Indexing
  4. Implementing Semantic and FAQ Search
  5. Integrating Kendra with Bedrock for RAG
  6. Building AI-Powered Search Applications
ChatGPT, Amazon Q, and GitHub Copilot

Working with ChatGPT and Amazon Q

  1. Understanding OpenAI and ChatGPT
  2. Overview of Amazon Q (AWS GenAI Assistant)
  3. Building AI Agents using Amazon Q Developer Tools
  4. Code Generation and Debugging using ChatGPT and Q
  5. Generating Documentation and Code Explainability
  6. Multi-Language Translation and Code Refactoring

GitHub Copilot

  1. What is GitHub Copilot?
  2. Setting up GitHub Copilot with VS Code
  3. Using Copilot for Code Generation and Optimization
  4. Debugging and Testing with Copilot
  5. Copilot X and Integration with ChatGPT and AWS Tools

Overview of Python
Python Overview
Preview 0h 02m 42s
Python Advantages and Disadvantages
Preview 0h 03m 51s
Python an Interpreted Language
0h 02m 15s
Python History
0h 03m 24s
Downloading and Installing Python
0h 04m 15s
Python First Program
Preview 0h 03m 53s
Variables and Data Types
Variables
0h 06m 03s
Data Types
0h 07m 04s
String and String Methods
0h 06m 07s
String Formatting
0h 03m 09s
Escapse Sequences
0h 03m 32s
Python Operators
0h 07m 28s
Reading from Keyboard
0h 04m 36s

Conditional Constructs
Conditional Statements
0h 01m 37s
If Statement
0h 03m 47s
If else statement
0h 02m 33s
If-Elif-Else-Statement
0h 03m 43s
Nested Conditions
0h 03m 42s
Match-Case Conditions
0h 02m 59s
Looping Constructs
Loops in Python
0h 00m 44s
For Loop
0h 05m 50s
While Loop
0h 04m 23s
Jump Statements
0h 00m 53s
Break Statement
0h 02m 00s
Continue Statement
0h 03m 22s
Return Statement
0h 02m 28s

Working with Functions
Python Functions - Session Agenda
0h 00m 36s
Functions Introduction
0h 01m 20s
Defining and Calling Functions
0h 02m 57s
Function Arguments
0h 04m 50s
Lambda Functions
0h 04m 28s
Recursion Function
0h 04m 34s
Built-In Functions
0h 04m 10s
Anonymous-Functions
0h 02m 41s
Global, Local and NonLocal
0h 03m 55s

Object Oriented Programming
Object-Oriented-Programming-Module-Introduction
Preview 0h 01m 00s
OOPS Introduction
0h 01m 45s
Classes and Objects
0h 03m 56s
Inheritance
0h 05m 52s
Polymorphism
0h 04m 22s
Encapsulation
0h 04m 42s
Abstraction
0h 04m 41s
Access Modifiers
0h 05m 21s
Constructor
0h 05m 11s

File Handling
File Handling Session Agenda
0h 00m 38s
Python File Handling Introduction
0h 01m 59s
How-python-talk-to-files
0h 05m 01s
Text vs. Binary Files
0h 04m 45s
Python-Directory
0h 05m 49s
Exception Handling Agenda
0h 01m 00s
Python Exceptions
0h 02m 56s
Python Exception Handling
0h 03m 29s
Exception Handling Hands-On
0h 04m 11s
User Defined Exception
0h 05m 30s
1. Introduction to AWS AI
0:03:00
2. Introduction to Python
0:06:30
3. Variables & Data Types in Python
0:05:00
4. AWS AI Services
0:03:30
5. Responsible AI Principles on AWS
0:04:00
6. Operators in Python
0:04:00
7. Conditional Statements in Python
0:03:00
8. Working with ChatGPT
0:03:00
9. Code Generation & Documentation
0:04:00
10. Loops in Python
0:02:30
11. Jump Statements in Python
0:03:30
12. Debugging and Optimization via AI Tools
0:04:00
13. Copilot for Automated Test Generation
0:03:30
14. Functions in Python
0:06:00
15. Lambda Functions in Python
0:04:00
16. Introduction to Amazon Rekognition
0:05:00
17. Image & Video Intelligence with Amazon Rekognition
0:06:00
18. Recursion in Python
0:05:30
19. Modules and Packages in Python
0:04:00
20. Introduction to Amazon Comprehend
0:04:00
21. Advanced Text Analysis, NLP & Multilingual CLU with AWS AI Services
0:10:00
22. Object-Oriented Programming (OOP) with Python
0:07:00
23. File Handling in Python
0:04:00
24. Introduction to Amazon Textract
0:06:30
25. Advanced Document Intelligence with Amazon Textract
0:06:00
26. Errors & Exception Handling in Python
0:09:30
27. Introduction to Amazon Bedrock
0:07:00
28. RAG and Titan Image Generation on AWS Bedrock
0:10:00
29. Introduction to Amazon Kendra
0:08:00
30. Introduction to Amazon Kendra
0:08:00
31. Introduction to Amazon Kendra
0:08:00
32. Introduction to Amazon Kendra
0:08:00
33. Introduction to Amazon Kendra
0:08:00
1. Your First Text Generation: Amazon Bedrock
00:30:00
2. Prime Number Generator
00:30:00
3. Sentiment Analysis with Amazon Comprehend
00:30:00
4. Image Recognition with Amazon Rekognition
00:30:00
5. Temperature Converter Module
00:30:00
6. CSV Reader and Filter
00:30:00
7. Speech-to-Text with Amazon Transcribe
00:30:00
8. Building a Chatbot with Amazon Lex V2
00:30:00
9. Document Intelligence with Amazon Textract
00:30:00
10. Library Book Management System
00:30:00
11. Custom Calculator with Error Handling
00:30:00
12. Advanced Prompt Engineering with Bedrock
00:30:00
13. AI Image Generation with Amazon Nova Canvas
00:30:00
14. Email Validator
00:30:00
15. Data Cleaner with map, filter, and lambda
00:30:00
16. Build Your Own RAG Chatbot with Bedrock
00:30:00
17. Multimodal Vision with Claude 3 Haiku
00:30:00
18. Parallel File Download Simulation
00:30:00
19. Simple Weather API Fetcher
00:30:00
20. Logging Decorator
00:30:00
Project#1: AWS AI Chatbot with Amazon Bedrock

Building Intelligent Chatbots

  1. Introduction to Amazon Bedrock and Foundation Models
  2. Natural Language Capabilities of Claude, Titan, and Llama Models
  3. Understanding User Prompts and Generating Accurate Responses
  4. Designing Human-like Conversational Flows using Bedrock APIs
  5. Prompt Engineering for Contextual and Domain-Specific Responses
  6. Fine-Tuning Foundation Models for Industry Use Cases

Enterprise-Ready Integration

  1. Integrating with Amazon Kendra for Retrieval-Augmented Generation (RAG)
  2. Accessing Company Documents, Databases & Knowledge Bases
  3. Delivering Context-Aware and Accurate Answers
  4. Customizing Chatbots for HR and Employee Support
  5. AI Assistants for Customer Service using Amazon Lex
  6. Internal Knowledge Management with Generative AI
Project#2: Intelligent Resume Matcher using AWS AI

AI-Powered Resume Matching

  1. Introduction to Resume Matcher with Amazon Bedrock & Kendra
  2. Converting Resumes into Numerical Embeddings using Titan Embeddings Model
  3. Processing Job Descriptions for Contextual Understanding
  4. Measuring Semantic Similarity between Candidates and Job Roles
  5. Ranking Candidates using Vector Search (Amazon Kendra + Bedrock RAG)
  6. Ensuring Fair, Explainable, and Accurate Talent Evaluation

Recruitment Efficiency & Impact

  1. Automating Candidate Shortlisting with AI
  2. Saving Recruiters Time in Initial Screening
  3. Reducing Human Bias in Hiring Decisions
  4. Identifying High-Potential Candidates Faster
  5. Improving Hiring Quality and Efficiency with AI
  6. Building AI-Driven Recruitment Tools using AWS AI Services
1. AI Foundations with AWS
15 Questions
2. Productivity with ChatGPT & Copilot
15 Questions
3. AWS Computer Vision with Recognition
15 Questions
4. NLP & Text Intelligence using Amazon Comprehend
15 Questions
5. Document Intelligence using Amazon Textract
15 Questions
6. Gen AI Platform with Amazon Bedrock
15 Questions
7. AI Search with Amazon Kendra
15 Questions

Q&A Guides

Introduction to Python
0:20:00
Variables & Data Types
0:15:00
Operators in Python
0:18:00
Conditional Statements & Loops in Python
0:20:00
Python Functions & Classes
0:17:00
Dictionaries & Sets in Python
0:19:00
Python Modules & Files
0:16:00

Core Python Libraries for Data Science
0:20:00
Data Validation and API Tools
0:15:00
FastAPI & Cloud API Development
0:18:00

Introduction to AI
0:20:00
Core AWS AI Tools and Services
0:19:00
AWS AI Service Integration and Optimization
0:17:00

ChatGPT in Testing and Automation
0:15:00
AI for Code & Testing
0:18:00

Introduction to Amazon Rekognition
0:20:00
Image & Video Analytics Using Rekognition
0:16:00

Enterprise NLP Fundamentals
0:19:00
Core Concepts of Amazon Comprehend
0:17:00
Text & Language Insights with Amazon Comprehend
0:16:00

Amazon Textract Fundamentals
0:20:00
Textract Document Analysis & Extraction
0:18:00

Amazon Bedrock Essentials
0:15:00
Kendra Search Service
0:17:00

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5-Day Money-Back Guarantee: Our training programs are empowering thousands with expert knowledge - they will you too. If you're disappointed for whatever reason, you'll get your 100% refund. We won't make you beg or invoke any silly rules or conditions – if you're not satisfied within your first 5 days then we'll refund you without any fuss. For full details, please refer to our Refund Policy.

AWS AI Engineer Certification

The AWS Certified Generative AI Engineer – Professional certification validates your ability to design, build, and deploy Generative AI solutions using AWS services such as Amazon Bedrock, SageMaker, Amazon Kendra, and Comprehend. It demonstrates your expertise in working with Large Language Models (LLMs), embeddings, and AI-driven applications on the AWS platform.

This certification is ideal for professionals who work with AI and Gen AI on AWS, including:

  • AI Engineers
  • Machine Learning Engineers
  • Data Scientists
  • Developers and Solution Architects building GenAI applications using AWS services

Before taking this exam, it’s recommended that you have:

  • Hands-on experience with AWS AI/ML services (Amazon Bedrock, SageMaker, Comprehend, Kendra, Lex).
  • Knowledge of Python programming and RESTful API integration.
  • Understanding of AI, machine learning, and large language model (LLM) concepts.
  • Familiarity with prompt engineering, vector search, and RAG-based solutions.

The AWS Certified Generative AI Engineer – Professional exam costs USD 300. Exam pricing may vary based on your location. You can visit the official AWS Certification Page for the latest details.

This certification enhances your AI career with:

  • High-paying roles: $120,000 - $180,000 (US) and ₹18,00,000 - ₹35,00,000 (India).
  • Job opportunities with top organizations such as Amazon, NVIDIA, Microsoft, and Deloitte.
  • Recognition as an expert in Generative AI, LLMs, and applied AI solutions using AWS tools.
  • Advancement in AI solution design, cloud architecture, and innovation-driven roles across industries like finance, healthcare, and retail.

Course Mentors

Shailendra Chauhan
10X MICROSOFT MVP AI ARCHITECT

Shailendra Chauhan

Microsoft MVP, Founder & CEO at ScholarHat

17+ Years of Industry Experience as Mentor & Solution Architect
Expert in .NET, Angular, React & Python
Azure Cloud & AI/ML/Gen AI Specialist
Bhawna Gunwani

Bhawna Gunwani

Corporate Trainer

15+ Years Technical & Corporate Training
Expert in Microsoft Tech, React, Angular & Node
Global Training: TCS, Infosys, Accenture & More
Vishwanathan Narayanan (VNN)

Vishwanathan Narayanan (VNN)

Mentor & Solution Architect

20 Years Solution Architecture Excellence
Expert in Java, Spring Boot & AWS Cloud
Cloud-Native Microservices Architect

Frequently Asked Questions

Q1. Can I Attend a Demo Session before Enrolment?
Yes, you can Attend a Demo Session before Enrolment in angular certification course. It gives you the opportunity to assess whether the training program aligns with your learning objectives. So, don't hesitate! Take advantage of this opportunity and attend a demo session before making your decision.
Q2. Can I request for a support session if I need to better understand the topics?
Yes, of course you can request for a support session if you need to better understand the topics. For that, you need to be in touch with the counsellor. Contact on +91- 999 9123 502 or you can mail us at hello@scholarhat.com
Q3. Who are your mentors?
All our mentors are highly qualified and experience professionals. All have at least 8-10 yrs of development experience in various technologies and are trained by ScholarHat to deliver interactive training to the participants.
Q4. What If I miss my online training class?
All online training classes are recorded. You will get the recorded sessions so that you can watch the online classes when you want. Also, you can join other class to do your missing classes.
Q5. Can I share my course with someone else?
In short, no. Check our licensing that you agree to by using ScholarHat LMS. We track this stuff, any abuse of copyright is taken seriously. Thanks for your understanding on this one.
Q6. Do you provide any course material or live session videos?
Yes we do. You will get access to the entire content including class videos, mockups, and assignments through LMS.
Q7. Do you provide training on latest technology version?
Yes we do. As the technology upgrades we do update our content and provide your training on latest version of that technology.
Q8. Do you prepare me for the job interview?
Yes, we do. We will discuss all possible technical interview questions and answers during the training program so that you can prepare yourself for interview.
Q9. Will I get placement assistance after receiving my course completion certificate?
Yes, you’ll get placement assistance after receiving your course completion certificate. The placement assistance provided by the US will guide you through the job search process, help you polish your resume, and connect you with potential employers. For that, you need to be in touch with the counsellor. Contact on +91- 999 9123 502 or you can mail us at hello@scholarhat.com
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