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!
Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. Beyond that, you do not need to be an expert programmer to use this material. To get started, the Python sections are linked at the left -- Python Set Up to get Python installed on your machine, Python Introduction for an introduction to the language, and then Python Strings starts the coding material, leading to the first exercise. The end of each written section includes a link to the code exercise for that section's material. The lecture videos parallel the written materials, introducing Python, then strings, then first exercises, and so on. At Google, all this material makes up an intensive 2-day class, so the videos are organized as the day-1 and day-2 sections. This material was created by Nick Parlante working in the engEDU group at Google. Special thanks for the help from my Google colleagues John Cox, Steve Glassman, Piotr Kaminksi, and Antoine Picard. And finally thanks to Google and my director Maggie Johnson for the enlightened generosity to put these materials out on the internet for free under the Creative Commons Attribution 2.5 license -- share and enjoy!
We're like Duolingo for learning to code. When learning to code, most people get stuck on the "bridge" between memorizing syntax and understanding the logic that makes it all work. We believe the most effective way to learn a programming language is to break the process into three phases:(1)Memorize syntax; (2) Solve problems; and (3) Make stuff. Most beginners jump from memorizing syntax directly into making stuff (or trying) without fully understanding how syntax is used to solve problems. In other words, they haven't learned how to think like a programmer, yet they're trying to solve problems like a programmer. Edabit was created to bridge this gap, while also making the process fun and addictive.
Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly. It's also easy for beginners to use and learn, so jump in!
Scikit Learn provide simple and efficient tools for predictive data analysis. Assessible to everybody, and reusable in various contexts. It built on NumPy, SciPy, and matplotlib. It is open sources, commercially usable under the BSD License.
GitHub is a development platform inspired by the way you work. From open source to business, you can host and review code, manage projects, and build software alongside 50 million developers. GitHub brings teams together to work through problems, move ideas forward, and learn from each other along the way. You can write better code, manage your chaos, and find the right tools in GitHub.
SPSS means “Statistical Package for the Social Sciences” and was first launched in 1968. Since SPSS was acquired by IBM in 2009, it's officially known as IBM SPSS Statistics but most users still just refer to it as “SPSS”. SPSS is software for editing and analyzing all sorts of data. These data may come from basically any source: scientific research, a customer database, Google Analytics or even the server log files of a website.
W3Schools is optimized for learning, testing, and training. Examples might be simplified to improve reading and basic understanding. Tutorials, references, and examples are constantly reviewed to avoid errors, but we cannot warrant full correctness of all content.
Brilliant helps you see concepts visually and interact with them, and poses questions that get you to think. Our courses show you that math, science, and computer science are – at their core – a way of thinking. All of our courses are crafted by award-winning teachers, researchers, and professionals from MIT, Caltech, Duke, Microsoft, Google, and more, with these principles of learning in mind. Get started as a beginner with the fundamentals, or dive right into the intermediate and advanced courses for professionals. Brilliant is for ambitious and curious people ages 10 to 110.
freeCodeCamp is a proven path to your first software developer job.
More than 40,000 people have gotten developer jobs after completing this – including at big companies like Google and Microsoft.
If you are new to programming, we recommend you start at the beginning and earn these certifications in order.
To earn each certification, build its 5 required projects and get all their tests to pass.You can add these certifications to your résumé or LinkedIn. But more important than the certifications is the practice you get along the way.If you feel overwhelmed, that is normal. Programming is hard. Practice is the key. Practice, practice, practice. And this curriculum will give you thousands of hours of hands-on programming practice. And if you want to learn more math and computer science theory, we also have thousands of hours of video courses on freeCodeCamp's YouTube channel. If you want to get a developer job or freelance clients, programming skills will be just part of the puzzle. You also need to build your personal network and your reputation as a developer.
You can do this on Twitter and GitHub, and also on the freeCodeCamp forum.
Happy coding.
Learn to Code for Free. We're here to make coding more accessible, so everyone can learn the skills they need to upgrade their careers. For example, you can learn Python, HTML, CSS, and JavaScript.
Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. Learning an algorithm gets much easier with visualizing it.
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and games.