We recommend these courses for those who wish to learn Python without prior computer programming experience. You might be interested in learning how to automate accounting processes, or ways to bring efficiency to day-to-day marketing analytics and data mining. Python is used in large-scale functions and software engineering jobs, such as game development, machine learning, database management, and more. Regardless of your end goals, this collection covers the fundamentals of programming in Python.

A quick search of Indeed.com returns over 40,000 job openings with Python programming skills or experience listed as a requirement. The wide adoption of the language across many industries results in a large number of job opportunities. Common job titles include Python Developer, Python Software Engineer, Full Stack Developer and Python Database Programmer. Of the Python-specific jobs listed, 43% of offered salaries are above $100K per year, and some senior-level Python programming engineer positions offer over $200K per year. It’s very fair to say that Python skills and experience can lead to a lucrative and secure career. The proper Python certification can influence hiring managers looking to fill specific roles on their team.

Following is an excerpt from a Coursera Community forum topic about what programming languages our Community members use.

"I've been in software development for 50 years (now retired) and languages come and go. If you're into software development, keep active in several, and strive to learn a new and different culture language every year or two. In simple terms today I like Python and JavaScript. For longevity in marketable skills, C and C++ are essential base skills. I used C for over 30 years. Learn Haskell, it'll improve all your other programming skills even if you never use it in a project." - Gordon

"For data science it is most important to understand and implement algorithms. Python is one of the languages that is really self describing. And one of the major reasons why I use it for data science projects especially machine learning is that it is very light. Anyway, for all my projects that have complicated algorithms, I use OCTAVE for trying out algorithms (since I have all datascience codes stored there). Mainly by breaking it into simpler problems and then in the end I convert it into desired language and join the simpler and shorter algorithms." - Hardi