Artificial Intelligence (AI) enables machines to perform tasks requiring human-like intelligence, such as decision-making and problem-solving. Its subsets include Machine Learning (ML), which uses data to improve systems without explicit programming, Deep Learning (DL), which employs neural networks for advanced pattern recognition, and Generative AI (Gen AI), which creates new content like text and images by analyzing data. Together, these technologies drive innovation, streamline processes, and deliver personalized experiences, making them essential in today’s digital world.



Exam Prep AIF-C01: AWS Certified AI Practitioner

Instructor: Whizlabs Instructor
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What you'll learn
Understand the fundamental concepts and services related to AI and ML, including their applications in real-world scenarios.
Discover the steps to build, train, and deploy machine learning models using AWS tools and services.
Explore Responsible AI practices for developing fair, transparent, and explainable AI solutions.
Discuss the best practices for securing AI/ML workloads and ensuring compliance with AWS security standards.
Skills you'll gain
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There are 5 modules in this course
Welcome to Week 1 of the Exam Prep AIF-C01: AWS Certified AI Practitioner course. In this week, we will be introduced to the features and use cases of Foundation Models and Generative AI models. We will learn about the RAG Architecture of LLM and implement it using Amazon Bedrock. By the end of the week, we will be able to understand Vector Embeddings, GuardRails, and Agents feature of Amazon Bedrock.
What's included
19 videos5 readings3 assignments1 discussion prompt
Welcome to Week 2. This week, we will be introduced to the differences between AI, Deep Learning, and Machine Learning. We will learn Machine learning lifecycle, different types of data used in Machine learning, and machine learning techniques. At the end, we will explore MLOps and its related AWS services.
What's included
15 videos2 readings2 assignments
Welcome to Week 3. This week, we will be introduced to AWS managed AI/ML services. We will learn to implement Amazon Comprehend, Amazon Translate, Amazon Transcribe, Amazon Polly, Amazon Rekognition, and, Amazon Augmented AI (A2I).We will be exploring features of Amazon SageMaker with its components. At the end of the week, we will learn Amazon Q, a generative AI–powered assistant developed by AWS.
What's included
24 videos4 readings3 assignments
In the Week 4, we will be introduced to the concepts of Prompt Engineering and Responsible AI. We will learn different techniques to design effective prompts used to optimize generative AI model. We will also explore the key principles of Responsible AI and use them to select a generative AI model. By the end of the week, we will discover AWS services to select the model and guide them to produce the desired outputs.
What's included
11 videos3 readings2 assignments
Welcome to Week 5. This week, we will be introduced to shared responsibility model in AWS to secure AI/ML solutions. We will learn to identify and apply security and privacy considerations for AI systems. By the end of the week, we will explore AWS services and features to assist with governance and security of AI solutions.
What's included
5 videos2 readings2 assignments
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Reviewed on Jun 25, 2025
This has been designed really well and i could learn and took AWS practice exam where i could achiever 95%

