Category: dataset
Question: What are resources available for getting started with a Data Project on Kaggle?
Answer: There are many resources available online to help you get started working on your open data project.

## Using Datasets

- [Getting Started on Kaggle video tutorials](https://www.youtube.com/playlist?list=PLqFaTIg4myu8gbDh6oBl7XRYNBlthpDEW): Just started on Kaggle? Not sure what is where and why? Here are our very own Kaggle team tutorials to orient you quickly on navigating the Kaggle platform and creating your own datasets and Notebooks.

- [A Guide to Open Data Publishing](http://blog.kaggle.com/2016/10/21/a-guide-to-open-data-publishing-analytics/): This article includes the key ingredients to an open data project.

- [Web scraping data in Python](http://blog.kaggle.com/2017/01/31/scraping-for-craft-beers-a-dataset-creation-tutorial/): A tutorial showing you how to scrape data with BeautifulSoup. It goes over the same code used to create the Craft Beers dataset published on Kaggle.

- [Making Kaggle the Home of Open Data](http://blog.kaggle.com/2016/08/17/making-kaggle-the-home-of-open-data/): Ben’s post shares instructions for publishing your open data project on Kaggle and how you can explore others’ datasets.

- [Creating an Organization](https://www.kaggle.com/organizations/new): If you’re publishing data from an organization, you can create an organization profile first. Then you just select the organization profile from the dropdown near your avatar when publishing.

- [Open Data Spotlights](http://blog.kaggle.com/tag/open-data-spotlight/): This series highlights some of the best open data projects on Kaggle.

- Have requests or want to discuss data collection, cleaning, or other aspects of open data projects? Post away in the Datasets Discussion forum on Kaggle.

## Using Notebooks

- [Getting Started on Kaggle video tutorials](https://www.youtube.com/playlist?list=PLqFaTIg4myu8gbDh6oBl7XRYNBlthpDEW): Just started on Kaggle? Not sure what is where and why? Here are our very own Kaggle team tutorials to orient you quickly on navigating the Kaggle platform and creating your own datasets and Notebooks.

- [Kaggle Learn](https://www.kaggle.com/learn/overview) is a great place to start getting hands on with data science and machine learning techniques using Notebooks.

- [Does open data make you happy? An introduction to Kaggle Notebooks](https://medium.com/@meganrisdal/does-open-data-make-you-happy-an-introduction-to-kaggle-kernels-d8cce437d5ff): Learn how to use Notebooks to explore any combination of datasets published on Kaggle.

- [Seventeen Ways to Map Data in Notebooks](http://blog.kaggle.com/2016/11/30/seventeen-ways-to-map-data-in-kaggle-kernels/): A collection of mini-tutorials by Kaggle users for Python and R users.

## Analysis

- [How to Get Started with Data Science in Containers](http://blog.kaggle.com/2016/02/05/how-to-get-started-with-data-science-in-containers/): One of our data scientists, Jamie Hall, explains how and why Docker containers are at the heart of Notebooks – reproducible analysis.

- [Approaching (Almost) Any Machine Learning Problem by Kaggle Grandmaster Abhishek Thakur](http://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/): Exactly what it says – a great tutorial.

## Other

- [Kaggle Datasets Twitter](https://twitter.com/KaggleDatasets): The new account features newly featured datasets plus open data news.

- [Collecting & Using Open Data](http://mlwave.com/how-to-produce-and-use-datasets-lessons-learned/): A blog by Kaggler MLWave recommended by Triskelion.