Career AI advisor

"SMART PLATFORM OF CAREER GUIDANCE JUST BY ENTERING YOUR SKILLS"

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What inspired me

I was inspired by my own experience. I was not aware of emerging domains for my true interest areas, which made it difficult to choose the right domain during my college exam registration. Although it was a sample exam in the first year, I realised that having a small, real-time guidance platform could help students make informed decisions quickly and avoid confusion.

What my project do

This project is a web-based application designed to provide personalized career guidance based on a user’s existing skills. Users enter the skills they currently possess (such as Python or C), and upon clicking “Analyse Career Options”, the system identifies suitable future job roles.

For each suggested role, the application highlights:

--> Skill gaps (missing skills required for the role).

--> A match percentage score indicating how well the user’s current skills align with the role.

After the initial analysis, the platform offers deeper career guidance, including:

--> Present industry demand and future scope for each role.

--> AI-generated career advice.

--> A curated list of companies with official application links for jobs and internships.

--> Relevant hackathons and coding competitions to enhance practical experience.

How I built it

-> The project was developed using Python and Streamlit to create an interactive and user-friendly web application. The frontend and backend logic were implemented within a single Streamlit application to ensure fast prototyping and smooth user interaction.

-> Career analysis logic was designed to map user-entered skills to relevant job roles, identify missing skills, and calculate a match percentage. I have used ChatGPT for guiding me for proper UI which was used to structure career recommendations, generate insights about present demand and future scope, and provide guidance for skill development.

->Throughout development, AI tools such as ChatGPT were used as a coding assistant to debug errors, improve UI. Final implementation decisions, feature integration, and testing were performed manually to ensure correctness and usability.

->The project was version-controlled using GitHub and deployed using Streamlit Cloud, enabling easy access to the live application.

Challenges I ran into

-> One major challenge was using an external AI model to generate accurate career recommendations. Initially, the project was built using Gemini 1.5 Flash, but it caused compatibility errors during local development.

-> Later, Gemini 2.0 was tested, but API access required payment, which was not feasible during the hackathon. Because of these limitations, the project was redesigned to avoid external API usage.

-> Instead, predefined data and logic were used within the application to ensure smooth execution and successful deployment. While this reduced the level of dynamic AI responses, it made the application stable and reliable.

Accomplishments that I am proud of

-> This was my first hackathon, and successfully building and deploying a complete working application was a major achievement for me. I am proud that I was able to design and implement AI-related logic to analyse skills and career paths, which also helped me better understand and identify my own areas of interest.

What I learned

Through my project, I learned how to design a UI and deploy a complete web application using Python and Streamlit. I gained hands-on experience in structuring application logic, handling user inputs, and presenting meaningful results in a clear interface. Earlier, I have learned in college from HTML&CSS as taking input creating button , but now with new langauge gives me more appropriate direction to improve my web skills.

I also learned how to handle real-world development challenges such as API limitations, debugging errors, and making practical design decisions under constraints. This hackathon helped me understand how AI concepts can be applied to solve real problems.

What's next for Career AI advisor

->In the future, Career AI Advisor can do work greatly by adding real-time AI models and APIs to provide more accurate recommendations. Expanding the dataset will allow the platform to cover a wider range of career paths and emerging technologies.

->Additional features such as filling form with user personal information , and progress tracking can help users continuously improve their skills. Adding the job portals, online learning platforms, and live hackathon listings can further support users in preparing for careers and placements.

->In conclusion , the long-term goal is to make Career AI Advisor a complete guidance platform that supports students from career exploration to skill development and job readiness.

Note

-> Hello, I wanted to note that after initial submission, I made enhancements to the career roadmap display and dynamic tabs in the app. The updated version is available on my GitHub. As I have already made the video link earlier so, as a reason of this I have not made any changes in the video as well as images that I have added in my project page

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