From ML to GenAI: Building Real-World Apps on AWS
Learn to scope ML projects, craft prompts, and build Bedrock-powered chatbots – even if you’re new to machine learning.
About
Bridge the gap between AI theory and working products.
Start with ML fundamentals for decision-makers and learn prompt-engineering best practices. From there, you’ll dive into practical machine learning on AWS, training models with SageMaker and building real-world generative AI applications using Amazon Bedrock and LangChain. You’ll also work with foundation models on Bedrock (RAG, agents, guardrails) and learn how large language models are trained and optimized on AWS. No heavy math is required, and all steps are demonstrated in a sandbox environment.
By the end, you’ll have:
- A Bedrock-powered chatbot or RAG assistant running with guardrails and cost tracking.
- A project brief, data readiness checklist, and ROI storyboard ready to present to stakeholders.
- Certificates confirming your ability to scope, prototype, and pitch LLM solutions.
What is a Skill Path?
Built in collaboration with AWS, Skill Paths are integrated learning journeys that combine JetBrains IDE projects, AWS video lessons, and hands-on cloud Labs to give you real-world practice.
Content
1. Introduction to Machine Learning: Art of the Possible
2. Machine Learning Terminology and Process
3. Planning a Machine Learning Project
4. Python Libraries – NumPy
5. Amazon Bedrock Getting Started
6. Mastering Large Language Models
7. Building Language Models on AWS
8. Building Generative AI Applications Using Amazon Bedrock
FAQ and troubleshooting
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Alternatively, use the JetBrains redeem page. Enter the same email address that's linked to your JetBrains Account, choose PyCharm from the Product dropdown menu, and apply your coupon code.
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Please make sure you're signed in with the same account on the JetBrains Toolbox App and the web version of the course. If the problem persists, please report it through our issue tracker.



