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AWS AI & ML Scholars

Get started on your AI learning journey with education and upskilling for students and aspiring technologists.

Launch your career in AI

Whether you're new to generative AI or looking to upskill, the AWS AI & ML Scholars program powered by AWS Skill Builder provides foundational knowledge to help prepare you for a career in technology. 

Delivered in collaboration with AWS Training Partner Udacity, AWS AI & ML Scholars aims to sponsor 100,000 learners in 2026 who may not have had access to this kind of training. The program is designed by AWS experts and provides learners with hands-on experience with AWS tools like PartyRock, Amazon Quick, and Amazon Bedrock. 

Anyone 18 years or older may apply. No prior AI or ML experience is required. Applications are open through June 24, 2026. 

How AWS AI & ML Scholars works

AWS AI & ML Scholars is designed to help learners get started with AI and ML, with no prior technical knowledge required.

The program has two phases: Challenge and Udacity Nanodegree. When applying, you will be auto-enrolled in the Challenge phase, which runs from March 24 to June 24, 2026. 

In the Challenge phase, you'll gain foundational skills using generative AI tools and create your own application on AWS with PartyRock. All learners who complete the program's Challenge phase receive a three-month subscription to AWS Skill Builder, which offers expert-led digital courses, hands-on labs, certification exam prep, and interactive learning environments. 

When applying for the program, choose between three courses: 

  • AI Programmer
  • Agentic AI Business Professional
  • Agent Developer

The top 4,500 performers after the Challenge phase will advance to participate in a fully-funded Udacity Nanodegree, where you'll dive deeper into how generative AI skills align with a future career in technology.

AWS AI & ML Scholars covers the full cost of a three-month Udacity Nanodegree.

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Who's eligible?

  • Learners 18+ years old
  • No prior AI/ML experience needed
  • Available globally (where permitted)
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Specialized learning tracks

Join one of three learning tracks with real-world projects to build job-ready AI skills.

    Build a strong technical foundation to launch your career in AI and ML. In this track, you will:

    • Master advanced Python for data analysis and visualization.
    • Train machine learning models using PyTorch.
    • Explore neural networks, including transformers.

    With hands-on projects and real-world applications, you’ll graduate ready to tackle complex AI challenges and contribute to the future of intelligent systems.

    Unlock the power of no-code AI to drive smarter business decisions. This track teaches you how to:

    • Use Amazon Quick Suite to build AI agents and BI solutions.
    • Design, deploy, and optimize AI-driven decision systems.
    • Automate intelligence gathering and business workflows.

    Using AI without coding, you’ll learn to create intuitive, scalable solutions that boost productivity and deliver real business impact.

    Become an AI developer ready to build secure, responsible, and scalable production-grade AI systems. In this advanced track, you will:

    • Build AI systems using Amazon Bedrock and Amazon Nova models.
    • Apply prompting strategies, reasoning patterns, and Retrieval-Augmented Generation (RAG).
    • Develop single-agent systems with tools, memory, and APIs. 

    This track prepares you to lead real-world AI projects with confidence and a strong commitment to safety and accountability. 

     

A further look at the learning experience

Discover the generative AI tools used in the program.

Use natural language to build generative AI applications

Have fun learning about generative AI and build your own app using PartyRock, which allows you to experiment with AI models in a code-free, easy-to-use interface. Built on Amazon Bedrock, use natural language to describe the app you want and start building in PartyRock. 

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Unleash the power of generative AI for research, insights, and automation

Amazon Quick is an agentic teammate that quickly answers your questions and turns those insights into actions. Instead of switching between multiple apps to gather data, find important signals and trends or complete manual tasks, Quick brings AI-powered research, business intelligence, and automation capabilities into a single workspace. 

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Enhance productivity with generative AI capabilities

Amazon Bedrock is a platform for building generative AI applications and agents at production scale. Organizations choose Amazon Bedrock to deliver personalized experiences, automate complex workflows, and uncover actionable insights—all in a comprehensive platform that enables teams to innovate fast without compromising on security. 

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Key dates

Apply to AWS AI & ML Scholars now! Applications close on June 24, 2026.

March 24, 2026

Applications open on Udacity for AI & ML Scholars 

June 24, 2026

Applications close on Udacity (earlier if all 100,000 seats are filled)

August 4, 2026

AI & ML Scholars Udacity Nanodegree phase begins

November 4, 2026

AI & ML Scholars Udacity Nanodegree phase ends

Our impact

At AWS, we believe cloud and AI services are powerful tools for developers and organizations working to transform the world for the better. We’re passionate about empowering learners to harness AI to address the world’s urgent and complex challenges.
 
Learn more about our impact, and apply to AWS AI & ML Scholars to take your skills to the next level!
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FAQ

General program information

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    The AWS AI & ML Scholars program powered by AWS Skill Builder provides foundational AI education for up to 100,000 learners 18 years and older who may not have had access to this kind of training. Delivered in collaboration with AWS Training Partner Udacity, the program features a Challenge phase where you learn AI fundamentals and build a real AI application, followed by a Udacity Nanodegree phase for top performers.

    The AWS AI & ML Scholars program's Challenge phase covers AI fundamentals through AWS Skill Builder's AI Practitioner Learning Plan. The Challenge phase includes topics like large language models (LLMs), AWS AI services, agentic AI, and offers the chance to build a hands-on AI application using PartyRock. Top performers selected for the Udacity Nanodegree phase can pursue one of three specialized learning tracks: AI Programmer, Agentic AI Business Professional, or Agent Developer.

    The Challenge phase consists of a 15-hour course to learn the fundamentals of generative AI. The self-paced Udacity Nanodegree takes three months to complete.

    • Applications open on Udacity: March 24 - June 24, 2026 
    • Challenge phase: March 24 - June 24, 2026 
    • Assessment sent via email: July 7, 2026 
    • Assessment deadline: July 13, 2026 
    • Udacity Nanodegree phase: August 4 - November 4, 2026

    You must be 18 years or older to apply for the AWS AI & ML Scholars program. No previous experience is required in AI, coding, or cloud. The program is open to learners globally.

    New this year, all learners who graduate from the Challenge phase will receive a three-month subscription to AWS Skill Builder, which offers expert-led digital courses, hands-on labs, certification exam prep, and interactive learning environments. The top 4,500 performers after the Challenge phase will advance to participate in a fully-funded Udacity Nanodegree, where you’ll dive deeper into how generative AI skills align with a future career in technology.

Udacity Nanodegree selection

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    A Udacity Nanodegree is a unique online educational offering designed to bridge the gap between learning and career goals. Udacity is an AWS Training Partner, and you can read more about their Nanodegree program.

    All Challenge phase graduates will be invited to complete an online assessment, and then 4,500 seats in a Udacity Nanodegree will be awarded to top performers based on their application, project submission during the Challenge phase, and assessment results.

    No, once you have selected a Udacity Nanodegree course track during the application process, you must continue with the material if you're chosen for the Nanodegree.