Kaggle is a free online platform for data science with thousands of public datasets, browser-based notebooks, short courses and competitions. Beginners should start with its introductory courses, explore a dataset in a notebook, study well-explained public notebooks, then try beginner-friendly competitions, focusing on learning rather than leaderboard rank.
What Kaggle offers
- Datasets: thousands of public datasets on topics from sport to health to economics.
- Notebooks: write and run Python or R code in the browser, with free computing resources.
- Learn: short, practical courses on Python, pandas, machine learning, SQL and more.
- Competitions: problems with leaderboards, from beginner practice contests to advanced challenges.
- Discussion: community forums and shared solutions.
A beginner plan
Week 1 to 2: courses
Complete the introductory Python and pandas courses, then the intro to machine learning course.
Week 3 to 4: explore a dataset
Choose a dataset on a topic you care about, such as cricket, films or education. Clean it, answer five questions and make clear charts. Publish the notebook with explanations.
Week 5 to 6: learn from others
Read highly voted beginner notebooks on the same dataset. Note techniques you have not used. Recreate them in your own words rather than copying.
Week 7 onwards: beginner competitions
Try classic practice competitions designed for learning. Aim to understand every step, improve gradually and write up what you learned.
Tips
- Explain your work. A notebook with clear text is far more valuable for your portfolio than one with only code.
- Do not chase rank. Top competition solutions are often complex; your goal is learning.
- Be careful with copied code. Understand before you use.
- Link your Kaggle profile to your CV and LinkedIn.
Kaggle in your portfolio
Two or three well-explained projects on Kaggle or GitHub show employers you can work with real data. Combine with machine learning project ideas, or get one-to-one guidance in our machine learning and data science course.
Frequently asked questions
Is Kaggle free?
Yes, including notebooks with free computing resources, within usage limits.
Do I need to be good at maths to use Kaggle?
Not to start. Courses introduce concepts gradually.
Do employers care about Kaggle?
Well-explained projects and strong competition results can help, especially for junior data roles.
