Hello from a Data Science Student! 🎓👋

[Sahithi-K2006]

🏷️ Discussion Type

Product Feedback

💬 Feature/Topic Area

Study Projects & Resources

Hi everyone,

Hi everyone,

My name is Sahithi, and I am a third-year undergraduate student pursuing a degree in Data Science. I am incredibly excited to be part of the GitHub Education community!

About Me & My Tech Journey:

💻 Languages & Tools: I love working with Python and Java to build machine learning, AI, and backend software development projects.

🚀 Experiences: I enjoy challenging myself through tech hackathons, virtual training programs, and internships to expand my skills in cloud infrastructure and software development.

🎯 Current Focus: I am always looking to collaborate on interesting data science or AI projects and learn more about industry best practices from fellow student developers and mentors here.

I’m looking forward to connecting, sharing resources, and growing alongside everyone in this community!

Feel free to reach out or connect with me.
This is my linkedIn page: https://www.linkedin.com/in/sahithikodidasu/

Best regards,
Sahithi

[github-actions[bot]]

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[Serhiibd]

Hi! Would you mind accepting this answer? I really need it

[Sahithi-K2006]

Thank you so much for the warm welcome and for sharing this valuable resource. I really appreciate your encouragement and support for my learning journey in Data Science and AI. I will definitely explore the course and keep learning new skills in Python and analytics. Looking forward to contributing more to the GitHub Education community.

[shamilahmdt]

Hi Sahithi, welcome to the GitHub Education community! 🌟

It’s amazing to see your enthusiasm for Data Science, AI, and backend development at such an early stage in your journey. Your involvement in hackathons, internships, and cloud-focused learning already shows a strong growth mindset.

Since you’re interested in AI and industry best practices, you might also enjoy exploring this resource:
https://www.coursera.org/articles/data-science-career-path

It gives a good overview of different Data Science career paths, important technical skills, and how students can prepare for real-world AI and analytics roles.

Wishing you the very best in your projects, collaborations, and future achievements. Looking forward to seeing your contributions in the community! 🚀

[Farshidbagheri]

Hi Sahithi, welcome to the GitHub Education community! 👋

It is great to see that you are already combining Data Science, AI, backend development, hackathons, internships, and cloud learning. That combination can become very strong if you organize your learning around real, well-documented projects.

Since you are a third-year Data Science student, one suggestion I would give is to build your GitHub profile around a few complete portfolio projects rather than many small unfinished experiments.

A strong beginner-to-intermediate roadmap could look like this:

1. Data Science foundation project
   Pick a clean dataset, perform data cleaning, exploratory data analysis, visualization, feature engineering, model training, and evaluation.

2. Machine Learning project
   Build a supervised learning project with a clear problem statement, train/test split, baseline model, improved model, metrics, and conclusion.

3. AI or NLP project
   Try a text classification, sentiment analysis, recommendation, or small LLM-based project where you explain the pipeline clearly.

4. Backend + ML integration project
   Since you are interested in backend development, create a small API using Flask, FastAPI, or Spring Boot that serves a trained model.

5. Cloud or deployment project
   Deploy one project using a simple cloud service or containerized workflow, and document how someone else can run it.

For each GitHub repository, try to include:

README.md
problem statement
dataset source
installation steps
how to run
model/method used
evaluation metrics
screenshots or demo
limitations
future improvements

This matters because recruiters, mentors, and collaborators often do not only look at the code. They also look at how clearly you explain your work, how reproducible the project is, and whether you understand the limitations of your model.

For collaboration, you could also create a short “Looking to collaborate on” section in your GitHub profile, for example:

Open to collaborating on:
- beginner-friendly data science projects
- machine learning model evaluation
- AI project documentation
- backend APIs for ML models
- cloud deployment of student projects

That makes it easier for other students to know how to approach you.

Wishing you the best in your Data Science journey. Keep building, documenting, and sharing your projects. A clear and consistent GitHub portfolio can become one of your strongest assets as a student developer.

[GitNimay]

Welcome, Sahithi! Great to have you here.

Your background in Python, Java, ML, and cloud infrastructure sounds like a strong foundation, and it's clear you're being intentional about your growth through hackathons and internships.

A few resources that might be useful given your focus areas:

For Data Science / AI projects:
GitHub has a solid collection of student-built ML repos worth exploring for inspiration and collaboration opportunities. Searching topics like machine-learning, data-science, or open-to-collaborate can surface active projects looking for contributors.

For cloud infrastructure:
If you haven't already, GitHub Student Developer Pack includes free credits and access to tools like AWS, Azure, and DigitalOcean, which are great for hands-on cloud practice outside of internship environments.

For connecting with others here:
Posting a specific project idea or a skill you want to develop tends to get more traction than a general intro, so if you have something in mind, feel free to share it as a follow-up thread.

Looking forward to seeing what you build. Feel free to tag me if you're looking for feedback on a project or want to bounce ideas around.

[Sahithi-K2006]

Thank you so much for the warm welcome and for sharing these valuable resources. I really appreciate the guidance.

It feels great to share my project ideas and accomplishments with the community. Recently, I've been working on building a full SaaS product that combines AI and Data Science, and I've been facing a few challenges along the way, especially around architecture, scalability, and implementation decisions.

If you're open to it, I'd be grateful for any guidance or feedback you could provide. It would be great to connect and learn from your experience whenever I run into doubts or technical roadblocks.

Looking forward to interacting more and contributing to the community. Thank you again!

[Farshidbagheri]

If this answered the original question, could you please mark my reply as the accepted answer? (Green color)

[Sahithi-K2006]

Hi everyone! 👋 First-time applicant here for the GitHub Campus Experts program (July 2026 cycle), hoping to learn from those who've been through it.
A bit about me: I'm currently in my second year of college, and I've been organizing events for students at my campus — most notably Dataverse, a coding and quiz challenge where participants build and present projects within a set time. We're planning the next edition on July 15, 2026, and I'm leading it as the main organizer. I don't have a large, formal tech community built up yet, but I'm genuinely passionate about helping students — especially freshers — get comfortable with tools like GitHub, and I want to use this program to turn that into something more structured and ongoing.
I'd really appreciate advice from anyone who's applied or been selected before:

For the application form, how specific should answers be about campus impact if you're still early in building your community rather than leading an established one?
Any tips for the video resume — how long should it be, and what actually makes an answer stand out (without needing professional editing)?
What does the selection and training process actually look like after submission — realistically how long from application to becoming an official Campus Expert?
What are common mistakes first-time applicants make?

Would love to hear real experiences. Thanks in advance for any guidance! 🙏