Who should attend this course?
If you're an SEO who knows the basics of Python and you want to take your knowledge to the next level - this is the course for you.
With hands-on, SEO-relevant Python examples you can do yourself - you'll learn how to pull data from a wide variety of sources (like the Search Console API, machine learning APIs, web pages, and Google Sheets), process it, and automatically share your results so that you, or colleagues, can get quick access to new insights.
You'll also learn how to work with different kinds of data, how to handle errors to minimise your time spent fixing them, and how to run code automatically in the cloud so your Python is working while you sleep.
Almost all of the course will be directly in Google Colab (a free, online tool from Google that helps you run Python without having to worry about installation) so you won't just be sat looking at slides - you'll see your trainer code as you learn new concepts, which will help you get a real understanding of how to actually use what you're learning.
Course Content
Key concepts
A run through important concepts and ways of working with lists, dictionaries, and handling errors in a smart way. This will set you up with a strong foundation for working with a big range of data sources.
APIs
An explanation of what APIs are and a quick dive into some popular APIs so you can get to grips with them. By the end of this section you'll be able to pull data from the Search Console API, summarise it, put the results in Google Sheets, and send a colleague an email letting them know the report is ready.
The concepts you learn in this block will help you understand how to use other APIs in future.
Working with the internet
You'll learn how to pull data from web pages and extract important information, how to "puppeteer" a browser so it'll click around a website without you lifting a finger, and how to interact directly with web-based APIs by using http requests.
As our direct API example - we'll work with a free machine learning API to summarise text, translate it, and quickly find keyword categories
Advanced work with Pandas
Building on a basic knowledge of Pandas - we'll explore some more advanced ways to work with table data - for example merging two data sets, pivoting and "melting", using apply to write our own functions, and creating interactive visualisations that you can explore
Working with local files
Now that you're creating more and more valuable data - you'll need some ways to save it. We'll go through how to file your results away neatly so that as you run more and more code, you always know where to look for the results.
Analysis methods
To expand our tool kit we'll look at some other ways to break down or summarise data, for example RegEx, N-Grams, and machine learning.
Running code in the cloud
To give you more freedom to run your code when you aren't around - we'll run through how to run your code in the cloud.
Keyword categorisation
Finally - we'll go through a script that applies a few of the different concepts we've learned to take a slightly different approach to keyword categorisation.
Who is this course for?
SEOs who know how Python works, and how to do thing like open files with Pandas, and are looking to expand their knowledge.
What you'll gain from this course
Confidence in
- Pulling data from a variety of sources (popular APIs, web pages, local files)
- Exploring the data with a range of analysis techniques
- Summarising your findings with tables or visualisations
- Sharing your findings so that you or colleagues can easily access the results without having to touch an code
You don't need anything installed to make the most of this course, just access to Google Colab and enthusiasm to reach the next stage of your Python journey.
