Personalized Learning Path Dashboard for Skill Enhancement

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  Explore Learning Domains: Browse different learning domains and explore skills, technologies, and career-focused learning paths.

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  User Profile and Progress Dashboard: View the user's learning streak, skill progress, experience points, and completed certificates .

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  Personalized Learning Path: Follow a structured learning roadmap, track topic completion, and monitor progress toward career goals.

Inspiration

We noticed that many students want to improve their skills and prepare for their careers, but they often struggle to decide what to learn first and which resources are suitable for them. Existing platforms provide many learning resources, but they may not provide a learning path based on an individual's current skills and career goals. This inspired us to build a system that can provide more personalized guidance.

What it does

Our Personalized Learning Path Dashboard analyzes a user's skills, interests, and career goals to identify skill gaps. It then recommends suitable learning resources and generates a personalized learning path using a content-based recommendation approach. The dashboard also helps users track their learning progress and understand their career readiness.

How we built it

We started by collecting and organizing information related to skills, learning resources, and job requirements. We used Python and data preprocessing techniques to prepare the data. NLP techniques were used to extract relevant skills from job descriptions. We then used content-based recommendation and cosine similarity to match user skills with relevant learning resources and generate personalized recommendations. The results were presented through a simple dashboard.

Challenges we ran into

One of our main challenges was organizing different types of skill and job-related data in a useful format. Extracting meaningful skills from job descriptions and matching them with user skills also required careful processing. Another challenge was designing the recommendation process so that the suggested learning resources were relevant to the user's actual skill gaps.

Accomplishments that we're proud of

We are proud of developing a working concept that combines NLP, skill gap analysis, and content-based recommendation to solve a real-world learning problem. We were also able to bring these different components together in a single dashboard and create a structured learning path based on individual requirements.

What we learned

Through this project, we gained practical knowledge of Python, data preprocessing, NLP, skill extraction, recommendation systems, cosine similarity, and dashboard development. We also learned how to work with real-world data, identify problems during development, test different approaches, and improve the system based on feedback.

What's next for Personalized Learning Path Dashboard for Skill Enhancement

In the future, we plan to improve the recommendation accuracy by using more learning and job-related data. We also plan to add features such as AI-based career guidance, chatbot support, gamification, mentor interaction, and improved progress tracking. These improvements can make the platform more useful for students and help them build skills in a more structured way.

Built With

• analysis
• content-based
• cosine
• css
• data
• gap
• git
• html
• javascript
• learning
• machine
• mysql
• natural-language-processing
• numpy
• pandas
• preprocessing
• python
• recommendation
• science
• scikit-learn
• similarity
• skill
• streamlit