Listing skills on your resume is fairly easy. Listing the right skills in the right way is a little bit trickier. Are you mentioning the right skills for the job, or are you boring the HR manager with irrelevant information? The hiring manager for the software development team couldn’t care less about your expertise in marketing. What they’re dying to know, though, is your skill level in Python and how you get along with the team. In this guide, we’re going to walk you through the process of putting skills on your resume from start to finish. We’ll explain how to identify the right skills and how to list them in a way that catches the hiring manager’s attention! Here’s what you’re going to learn:
Hard Skills Vs Soft Skills - What’s the Difference?
Why Should You List Your Skills on a Resume?
8 Best Skills to Put on a Resume
How to List Skills on a Resume
120+ Skills to Put on Your Resume (For 10+ Fields)
Python can be easy to pick up whether you're a first time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way writing programs with Python!
In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.
This project was started in 2007 as a Google Summer of Code project by David Cournapeau. Later that year, Matthieu Brucher started work on this project as part of his thesis. In 2010 Fabian Pedregosa, Gael Varoquaux, Alexandre Gramfort and Vincent Michel of INRIA took leadership of the project and made the first public release, February the 1st 2010. Since then, several releases have appeared following a ~ 3-month cycle, and a thriving international community has been leading the development.
Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access GPUs at no cost to you and a huge repository of community published data & code. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 50,000 public datasets and 400,000 public notebooks to conquer any analysis in no time.
GeoPandas is an open source project to make working with geospatial data in python easier. GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types. Geometric operations are performed by shapely. Geopandas further depends on fiona for file access and matplotlib for plottin
Colaboratory, or "Colab" for short, allows you to write and execute Python in your browser, with (1) Zero configuration required (2) Free access to GPUs (3) Easy sharing Whether you're a student, a data scientist or an AI researcher, Colab can make your work easier. Watch Introduction to Colab to learn (https://www.youtube.com/watch?v=inN8seMm7UI) more, or just get started below!