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Master AWS Certified AI Practitioner AIF-C01 Exam
This course covers the GenAI revolution and its role in securing a career with AWS Certified AI Practitioner AIF-C01, focusing on AI services, machine learning, and cloud AI.
4.8
129 lessons
23 cloud labs
20h
Created by Naeem ul Haq
What's included
- 129 lessons across 17 modules
- 14 quizzes with instant feedback
- 23 cloud labs with no setup required
- AI Tutor on every lesson
Why this course
- Ace the AWS AI Practitioner ExamDemonstrate your knowledge of AI and ML principles and AWS services to confidently pass the AIF-C01 certification exam.
- Build AI Solutions with AWSDesign and implement AI applications using AWS services like SageMaker and Rekognition, enhancing business processes and decision-making.
- Apply Responsible AI PracticesEnsure ethical AI deployment by integrating fairness, transparency, and compliance measures into your AI solutions.
- Optimize Generative AI ApplicationsLeverage generative AI techniques to create innovative solutions, improving user engagement and operational efficiency in real-world scenarios.
Who wrote it
Naeem ul Haq
Educative co-founder and CTO. Ex-Microsoft (Azure). Full-Stack, Cloud, Product & Engineering Leadership.
Naeem ul Haq is the co-founder and CTO of Educative, a hands-on learning platform for software engineers. Before co-founding Educative, he spent seven years as a software engineer at Microsoft, where he worked on the Windows Azure Fabric Controller, a core component of what became Microsoft Azure, and on Remote Desktop for Windows Server. Naeem co-founded Educative in 2015 alongside his brother Fahim to make developer education more interactive and accessible. His courses on Educative cover cloud technologies and full-stack web development, drawing directly from his experience building production infrastructure at Microsoft.
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What You'll Learn
- Understand the core concepts of AI and ML and their applications within AWS services.
- Explore the structure and key domains of the AWS Certified AI Practitioner exam.
- Apply responsible AI practices and ethical considerations in AI model development.
- Utilize AWS services like Amazon SageMaker, Comprehend, and Rekognition for AI solutions.
- Implement foundational models and generative AI techniques in real-world applications.
- Evaluate model performance metrics and optimize AI solutions for compliance and governance.
Learning Roadmap
1.
Introduction
Introduction
Gain foundational knowledge of AWS AI and machine learning for career advancement.
2.
AWS Fundamentals
AWS Fundamentals
Explore cloud computing fundamentals, AWS account setup, global infrastructure, and different ways of using AWS.
3.
AWS Core Services
AWS Core Services
8 Lessons
8 Lessons
Explore AWS core services, including EC2, S3, Lambda, VPC, and container management.
4.
Fundamentals of AI and ML
Fundamentals of AI and ML
11 Lessons
11 Lessons
Explore AI and ML fundamentals, including neural networks, data types, ML techniques, and model performance metrics.
5.
AWS Pre-Build Machine Learning Models
AWS Pre-Build Machine Learning Models
11 Lessons
11 Lessons
Explore AWS machine learning services for improved data processing, analysis, and user interaction.
6.
Amazon SageMaker
Amazon SageMaker
8 Lessons
8 Lessons
Explore Amazon SageMaker's tools for efficient, reliable, and ethical machine learning workflows.
7.
Fundamentals of Generative AI
Fundamentals of Generative AI
7 Lessons
7 Lessons
Explore generative AI’s capabilities, applications, and effective prompting techniques for optimal results.
8.
Amazon Bedrock
Amazon Bedrock
8 Lessons
8 Lessons
Explore Amazon Bedrock's capabilities in generative AI and foundational model optimization.
9.
AWS Security Services
AWS Security Services
10 Lessons
10 Lessons
Explore AWS security services, focusing on IAM, compliance, and data protection strategies.
10.
AWS Analytics Services
AWS Analytics Services
8 Lessons
8 Lessons
Explore AWS analytics services for data processing, integration, visualization, and marketplace solutions.
11.
AWS Databases
AWS Databases
7 Lessons
7 Lessons
Explore AWS's diverse database services, focusing on their features and applications.
12.
AWS Management and Governance
AWS Management and Governance
9 Lessons
9 Lessons
Explore services for effective governance, compliance, and monitoring of AWS cloud infrastructure.
13.
AWS Billing and Cost Management
AWS Billing and Cost Management
4 Lessons
4 Lessons
Master AWS cost management tools to optimize spending and control budgets effectively.
15.
Practice Exam I Solution
Practice Exam I Solution
14 Lessons
14 Lessons
Test your understanding of AI and ML fundamentals, foundation models, responsible AI, security, and compliance measures for AI solutions.
16.
Practice Exam II Solution
Practice Exam II Solution
14 Lessons
14 Lessons
Test your understanding of AI and ML fundamentals, foundation models, responsible AI, security, and compliance measures for AI solutions.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
About this course
WHY I WROTE THIS COURSE
AI is quickly becoming part of every developer’s workflow, from building intelligent features to integrating foundation models into production systems. As AWS expands its AI and ML ecosystem, the AWS Certified AI Practitioner certification has emerged as a practical entry point for engineers who want to understand how these systems are built and used in real environments. The challenge is knowing how to use the tools correctly and responsibly.
I built this course from my experience working on large-scale cloud systems. A pattern I’ve seen is that learners are often introduced to AI concepts in isolation, without understanding how they connect to real cloud services. When preparing for the AWS Certified AI Practitioner exam, many struggle to bridge that gap between theory and practical application. This course is designed to make that connection clear.
We focus on the fundamentals of AI and ML, then map them directly to AWS services like Amazon SageMaker, Bedrock, Comprehend, and Rekognition. You’ll learn how to think about real use cases, apply responsible AI practices, and understand how foundation models fit into modern applications. The course also includes hands-on Cloud Labs and exam-style practice questions that reflect the format and difficulty of the actual certification.
This approach has helped learners build confidence not just for the AWS Certified AI Practitioner exam, but for applying AI in real projects. If you’re starting your journey as an AI practitioner and want a clear, practical path, this course is designed to get you there.
ABOUT THE AUTHOR
Naeem ul Haq
Educative co-founder and CTO. Ex-Microsoft (Azure). Full-Stack, Cloud, Product & Engineering Leadership.
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