For #BacktoSkills month, we’re spotlighting a series of skills that supercharge careers. This week’s skill is Python, a popular, general-purpose programming language that is ubiquitous in a lot of high growth industries, from web and software design to data analysis, machine learning, and AI. In this post, we’ve collected past blogs from our instructors who have written articles about different techniques they’ve found valuable in their experience using Python throughout the years.
A lot courses in the Udacity catalog cover Python, taught by instructors with a range of experience but at least one thing in common: when it comes to working with Python, they know what they’re talking about. The instructors who have contributed free Python tutorials to the blog include:
- Erick Galinkin; Principal AI Researcher, Rapid7: Erick is a hacker and computer scientist, leading research at the intersection of security and artificial intelligence at Rapid7. He has spoken at numerous industry and academic conferences on topics ranging from malware development to game theory in security.
- Matt Swaffer; General Manager, MBS: Matt has been working in software development and data science for over 20 years. Matt’s career is centered on the intersection of technology, data, and human psychology. He is passionate about using data science to have a meaningful impact on our people and our planet.
- Benjamin Larson; Data Architect / Analytics Consultant: Benjamin has over 15 years of experience working as a data professional in fields including medicine, telecomm, and finance, in roles ranging from data architect to data scientist and analytics consultant. He holds a Ph.D. in Decision Sciences, where his research was focused on rare event detection.
Free Python Tutorials
Below you’ll find links to articles sharing essential or innovative techniques to include in your Python practice:
- Python eval()
- While eval() may be the most powerful function you should never use, it’s still an important function to understand. It’s one of the few built-in functions that does not need to be imported from a module or the standard library, and for better or worse, you may encounter it when dealing with poorly-maintained or legacy code.
- Creating Fake Data in Python Using Faker
- Learn the difference between fake and synthetic data and how to generate a variety of fake data using the Python Faker library. This is a powerful way of generating large amounts of data quickly that can be used to test user interfaces and databases.
- Webscraping with Requests
- Web scraping is the process of extracting data from websites. It can be as simple as manually copying and pasting from a webpage. More commonly though, it refers to the use of scripts or bots to extract the data automatically.
- Python help ()
- help() is a function that invokes the built-in help system and importantly, is intended for interactive use. This means you are likely never going to see it invoked in scripts, but it can be very useful when using the read-eval-print loop (REPL) for experimentation.
- Webscraping with Selenium
- Python Iterators
- Iterators are an incredibly important part of Python code. Although the actual iterators are often abstracted away from you and you instead loop over iterable objects, there are times where you will want or need to implement your own iterable objects.
- Webscraping with PyAutoGUI
- Python’s pyautogui is a package that allows users to create scripts that can simulate mouse movements, click on objects, send text, and even use hotkeys. While not as elegant a solution as Selenium, pyautogui can be used to bypass systems that put up blocks against automated browser use.
Become a Python Expert
Python is already one of the most popular programming languages, and demand for engineers with Python skills will only grow as fields like AI and Data Science continue to expand their influence on jobs, companies, and societies. Whether you’re new to Python or looking to pick up the newest Python techniques, our catalog has plenty of options for you!