Category: Building a Data Science Portfolio

Portfolio Project: Predicting Stock Prices Using Pandas and Scikit-learn

In this project, we’ll learn how to predict stock prices using python, pandas, and scikit-learn. Along the way, we’ll download stock prices, create a machine learning model, and develop a back-testing engine. As we do that, we’ll discuss what makes a good project for a data science portfolio, and how to present this project in […]

How to present your data science portfolio on GitHub

This is the fifth and final post in a series of posts on how to build a Data Science Portfolio. In the previous posts in our portfolio series, we talked about how to build a storytelling project, how to create a data science blog, how to create a machine learning project, and how to construct […]

Data Science Portfolios That Will Get You the Job

Data science skills are crucial for today’s employers, but listing data science on a resume isn’t enough to prove your expertise. Build a data science portfolio that showcases your prowess in a clear and undeniable way. Learn how to highlight your knowledge in a way that will inform, impress, and help you get the job.

Building a Data Science Portfolio: Machine Learning Project

Learn how to build an end to end machine learning project — a key part of any data science portfolio — in this free tutorial walkthrough.

Building a Data Science Blog for Your Portfolio

Data science blogs provide an ideal forum to show off your work in job applications and to the public. Learn to build one with Pelican, Jupyter Notebook, and Github pages.

Building a Data Science Portfolio: Storytelling with Data

This is the first in a series of posts on how to build a Data Science Portfolio. You can find links to the other posts in this series at the bottom of the post. Data science companies are increasingly looking at portfolios when making hiring decisions. One of the reasons for this is that a […]