Inspiration
Many learners want to enter AI/ML and other technical careers but struggle to identify which skills they lack, what to learn next, and how to turn learning into practical job-ready abilities. Generic roadmaps often fail to adapt to an individual's existing skills and progress. This inspired us to build EduPath 2.0.
What it does
EduPath 2.0 is an AI-powered personalized learning platform that helps learners understand their skill gaps and follow a structured path toward their target career. Learners can provide their existing skills, career goals, and supporting documents. The platform analyzes their profile, identifies priority skill gaps, recommends relevant learning resources, creates structured study objectives, and provides hands-on practice missions.
How we built it
We built EduPath 2.0 using Python and Streamlit for the application interface, FastAPI and supporting backend components where applicable, and LangGraph to orchestrate the AI-powered analysis workflow. Groq-powered language models support selected AI interactions. The platform organizes learner information, skill-gap insights, learning objectives, resources, and progress into a unified experience.
Challenges we faced
One of the main challenges was connecting learner-profile analysis with actionable learning objectives and a useful practice workflow. We also worked on integrating multiple components, improving the interface, and making the learning experience more structured and adaptive.
What we learned
We learned how to combine AI workflows, structured skill analysis, learning-resource recommendations, and interactive interfaces into a practical career-learning application. EduPath represents our effort to make career preparation more personalized, measurable, and focused on building real skills.
What's next
We aim to improve multimodal evidence analysis, progress persistence, learning recommendations, and personalized feedback so that EduPath can become an even more capable AI learning companion.


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