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
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
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.
Details to know
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February 2025
Assessments
12 assignments
Taught in English
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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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Frequently asked questions
The cost of AWS Certified AI Practitioner certification is USD 100 for the exam.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.