In today’s resume-driven world, we’re often encouraged to “list your skills” — but what exactly counts as a skill?
Should you list Python after watching a tutorial? Is Git a skill if you’ve only used it once in a school project? Let’s break it down.
If you’ve applied the tool or concept in a real or personal project, that’s a skill. Whether it was a solo GitHub repo or part of a hackathon, using something in context shows you can do it — not just talk about it.
Example:
You built a model using scikit-learn, cleaned data with Pandas, and visualized it with Seaborn — all those are legit skills.
Took a course and coded along with exercises or projects? Great — list the skills it taught, but be honest with your comfort level.
Tip:
Mention the course certification separately, and the skills it taught under your Skills section.
Example:
Completed Andrew Ng’s ML course and implemented logistic regression from scratch — now you can claim basic ML, Python, and NumPy.
Work experience — even unpaid or part-time — often involves real applications. If you’ve used a tool like Git, SQL, or TensorFlow in a professional setting, that’s an employable skill.
If you’ve only:
- Watched a few tutorials
- Read some blog posts
- Heard of it but never applied it
…it’s not a skill yet. It’s a learning goal — and that’s okay.
You can add it to a “Learning” or “Exploring” section on your LinkedIn or resume if you want to show initiative.
“If you can do something basic with it without Googling every step — it’s a skill.”
Don’t just list the tool. Add context:
- “Used Git for version control in ML project”
- “Built CNN in PyTorch for image classification”
- “Analyzed real-world datasets using Pandas & Seaborn”
You don’t need to be an expert to list something as a skill. What matters is honesty, application, and context. Recruiters know you’re learning — just show what you’ve actually done.
Have thoughts or questions on how to frame your skills on LinkedIn or your resume? Drop them in the comments or DM me!