January 2026
Intermediate to advanced
254 pages
6h 48m
English
Content preview from AWS Certified Cloud Practitioner (CLF-C02) Study Guide
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Chapter 13. Artificial Intelligence and Data Analytics Tools
Artificial intelligence (AI) is reshaping industries faster than ever. International Data Corporation (IDC) predicts that by 2027, global spending on AI systems will reach $500 billion, more than double what organizations spent in 2023. Companies are investing heavily in AI to automate tasks, improve customer experiences, and innovate across their products and services.
You see AI at work every day, whether it’s the personalized recommendations on your favorite streaming app, an intelligent chatbot that answers your banking questions, or real-time systems that detect fraud before it impacts customers. As AI capabilities continue to grow, so does the demand for people who know how to build and deploy these solutions in the cloud. This is also a key reason that AI is covered in the AWS Certified Cloud Practitioner exam.
In this chapter, we’ll break down the core ideas behind AI, machine learning (ML), deep learning (DL), and generative AI (GenAI), and see how each fits into the broader AI landscape. We’ll also look at key AWS services that support these workloads. They include Amazon SageMaker for building and deploying ML models, AWS Lex for creating conversational interfaces like chatbots, and Amazon Kendra for enterprise search.
Finally, we’ll touch on AWS data analytics services such as Athena, Glue, Kinesis, and QuickSight.
Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI
AI covers a wide ...
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