LearnGenie AI

Inspiration

Learning today is fragmented. Many learners struggle to identify what to learn, where to begin, and how to stay consistent throughout their learning journey.

Although countless online learning resources are available, learners often lose motivation due to the lack of personalized guidance, progress tracking, and continuous engagement.

LearnGenie AI was inspired by the idea of creating an AI-powered learning mentor that guides learners from roadmap creation to course completion and future learning recommendations.

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What it does

LearnGenie AI is an Agentic AI-powered learning mentor built on AWS.

The platform helps learners:

• Generate personalized 7-day learning roadmaps
• Receive AI-generated daily quizzes
• Track learning progress automatically
• Receive roadmap, reminder, and completion emails
• Generate AI-powered completion summaries
• Discover personalized next-course recommendations
• Receive recommendations through WhatsApp

The solution provides a complete learning journey instead of simply recommending courses.

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How I built it

LearnGenie AI was built using:

• Amazon Bedrock Nova Lite
• Amazon DynamoDB
• Amazon SES
• Amazon EventBridge
• AWS End User Messaging Social
• AWS IAM
• Streamlit
• Python

Amazon Bedrock powers roadmap generation, quiz generation, completion summaries, and next-course recommendations.

Amazon DynamoDB stores learner history, roadmap details, progress, and completion status.

Amazon SES delivers roadmap emails, reminder emails, and completion summary emails.

Amazon EventBridge supports automated reminder notifications.

AWS End User Messaging Social delivers AI-generated recommendations through WhatsApp.

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Challenges I ran into

One of the biggest challenges was creating a seamless end-to-end learning workflow while maintaining continuity across multiple learning days.

Another challenge was integrating multiple AWS services into a single user experience, including Bedrock, DynamoDB, SES, EventBridge, and AWS End User Messaging Social.

Delivering AI-generated recommendations through WhatsApp required understanding the WhatsApp onboarding process and configuring AWS End User Messaging Social correctly.

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Accomplishments that I'm proud of

• Built a complete Agentic AI learning experience
• Integrated Amazon Bedrock for personalized learning content
• Implemented automated email workflows using Amazon SES
• Added learner progress tracking with DynamoDB
• Implemented reminder automation using EventBridge
• Delivered AI-powered recommendations through WhatsApp
• Created an end-to-end learning journey from roadmap creation to completion

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What I learned

This project provided hands-on experience with:

• Amazon Bedrock for Generative AI workloads
• DynamoDB data modeling and persistence
• Event-driven workflows with EventBridge
• Email automation using Amazon SES
• WhatsApp communication through AWS End User Messaging Social
• Building Agentic AI experiences on AWS

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What's next for LearnGenie AI

Future enhancements include:

• Multi-language learning support
• Personalized AI coaching conversations
• Advanced recommendation engine
• Learning analytics dashboard
• Gamification and achievement badges
• Learning community integration

Built With

• agentic-ai
• amazon-bedrock
• amazon-bedrock-agentcore
• amazon-dynamodb
• amazon-eventbridge
• amazon-ses
• aws-end-user-messaging
• aws-lambda
• generative-ai
• large-language-models
• python
• strands-agents