The demand for Data Scientists who are proficient in Python is at an all time high. Python has helped people boost their careers in finance, consulting, research, software tech, and robotics. Explore 6 courses designed to help you learn Python.
By Jacob Samuelson
Python is one of the most versatile programming languages, and often touted as the best one to start a programming career because of a short learning curve. Python has been around for nearly 30 years and is still rising in popularity because of a neverending list of use cases, including the latest in data science and machine learning.
Python is the main programming language for data scientists, and allows the manipulation of data to inform critical business decisions. For this reason, the demand for Data Scientists who are proficient in Python is at an all time high.
In the information age, being proficient in manipulating data and creating automations can rocket launch your value in an organization. Knowing your way around Python instantly makes your resume more attractive, and opens up a world of interesting projects where you can make an impact. Python has helped people boost their careers in finance, consulting, research, software tech, and robotics.
Data scientists use Python at work to make internal tooling and different kinds of intranet APIs, but they also use it for their hobbies. Python is flexible enough that it is the language of choice to code use cases like smart home programming, REST APIs, web scraping, and robotics. No matter the use case, one thing is clear: learning Python is a worthwhile investment in your personal growth as a programmer as well as your future professional career.
CoRise combines industry-leading instructors, a global community of classmates, and interesting applied projects to create a learning experience far better than any other we saw out there. Their course is two weeks long and teaches you how to apply Python to your data science career, supporting you every step of the way. Highly recommend this to anyone hoping to dive in and get a ton out of their two-week experience.
This online course is provided by the University of Helsinki, and includes both text and video resources. It’s a great theory course to get you start in Python, and is akin to taking a CS 101 course in undergrad. You even have the option to transfer your credits to your home institution once you graduate from the course.
Harvard made a major step into democratizing its elite education programs with their partnership with EdX, through which this course and many others are offered. You can learn how to read and write code as well as how to test and “debug” it. Designed for students with or without prior programming experience who’d like to learn Python specifically, in an environment inspired by real-world Python problems.
This is a fun, interactive open-sourced web tool that allows you to learn Python by diving off the deep end, and includes integrated debuggers, enhanced tracebacks, hints for exercises and more. The long-term goals of this organization are ambitious: revolutionize computing education and make the best learning resources possible which everyone can contribute to and improve. It doesn’t hurt that their entire website sports an intergalactic travel vibe.
Coursera has partnered up with IBM to deliver this free, asynchronous course on using Python to get started on a Data Science career. The specialization consists of 5 self-paced online courses that will provide you with the foundational skills required for Data Science. Coursera provides hands-on practice using real-world data sets, and is an excellent educational tool for those who are diligent enough to complete it on their own.
This course is not free, but Udemy’s website advertises a steep discount of $14.99USD. For this price you get 56 hours worth of video content on a variety of Python content, covering every aspect of Python, from web development to data science. The structure of the course takes after the 100 Days of Coding Challenge, but this is assuming you block out 8-12 hours each day. Realistically you’ll probably use it as more of a useful reference for specific sections of Python you want to practice.
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