Cohort 1

2024: "I don't need Python to do SEO, I use Excel.”

1994: "I don't need Excel to do accounting, I use a calculator."

Elias Dabbas

Creator of advertools 

Data Science with Python for SEO

For absolute beginners in Data Science and Python. As a professional data practitioner, the ideal scenario is your ability to handle raw data with the full flexibility of a programming language. Opening files, analyzing data, creating simple charts, and automating some basic tasks are some of the outcomes you will leave with. You will also be exploring how to use some of the most important packages for data and SEO work. Practicing those tasks and tools every day will set you on the path of using the world's top tools for data manipulation, visualization, machine learning, and AI. Generous gifts from great partners (in alphabetical order) DemandSphere: 3 months (including API) access to our Startup plan (500 keywords daily SERP monitoring on Desktop &amp; Mobile) and 20% discount on any other plan for 12 monthsKeywordInsights: 6,000 lifetime credits and API accessWindsorAI: 15% lifetime discount on your accountWordLift: free Business+Ecommerce license for 2 months The total value exceeds the cost of the course.

Automate & scale your work, gain new insights, and use Python for daily tasks.

SEOs who have a lot of data to handle, want to get insights, and really love digging into data.

Search marketers who want to be on top of their data, and provide interesting insights that the typical tools cannot provide.

Opinionated data analysts who want the complete freedom to dig in to any dataset they want without any tool restrictions.

Who is this course for

What you’ll get out of this course

Easy-to-use "point and click" tools are very convenient and quick. Usually, this convenience comes with restrictions and limitations. We will take the first steps into starting to work with raw data and utilizing the full flexibility of a programming language - Python.

Take your data work to a new level

Many toy tools help you with analyzing a single page or a URL, but you really need to establish the ability to do everything in bulk. You will see examples of that, and will be pointed to tools in that direction.

Start to think programmatically and in bulk

Remember that moment after reading a great article when you felt really excited about new opportunities? You probably felt stuck, because you weren't sure how to do that on a website with 72,395 URLs. Data Science skills allow you to implement whatever you want with your data.

Think Implementation

Remember that moment after reading a great article: Part 2. Yes, but what is the current situation compared to the ideal one? Do you know how to assess a business/website with 72,395 URLs? Data Science skill can help in that.

Think analytics and diagnosis

We will start with very basic chart types and see how to programmatically build them with various options. You first need to "see" your data.

Data visualization - a chart is worth a thousand words!

Jupyter notebooks are the universal coding format for Data Scientists and analysts and are extremely flexible. We will learn how to run code and create basic documents with Jupyter. You also know about other topics for further exploration:<ul><li>HTML documents</li><li>Automated presentations</li><li>Interactive dashboards (Dash, Voila, ipywidgets)</li><li>Export formats</li></ul>

Jupyter Notebooks: Meet your new workbench

Once we establish a base for our work bench, we will start running Python code, and making sure we know how to create, delete, and modify various objects in Python. We will also learn about data types, data structures, and run basic loops.

Python: your new data language

We now run specific function and data workflows for your daily SEO work:<ul><li>Exploring GSC data</li><li>Auditing and analyzing XML sitemaps</li><li>Crawling a website and/or a list of URLs</li></ul>

advertools: You're here for the SEO, aren't you?

Start creating your own charts to provide and understanding and insights about your data: <ul><li>Make various types of charts: histograms, bar charts, and scatter plots</li><li>Use various visual elements to enrich your charts: color, size, multiple charts, and more</li></ul>

Data visualization with Plotly

Run the most important operations on the DataFrame &amp; Series data structures with real data:<ul><li>Filtering</li><li>Sorting</li><li>Subsetting</li><li>Text extraction</li><li>Handling dates</li></ul>

Data manipulation with pandas

Course syllabus

Meet your instructor

Designed to fit in your regular schedule, and to allow you time in between, to practice and absorb the topics discussed.

Monday, Wednesday, and Friday

You'll be given many additional resources, notebooks, and scripts to explore and try on your own.

Homework

Course schedule

We will be analyzing data and coding together throughout the course.

Active hands-on learning

Just like at work, you will get a chance to review other people's work, provide feedback, and get it for your work.

Work in groups

Start sharing and showcasing your work right from the beginning, and establish yourself as an authority on the topic(s) that you love.

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