Analyzing Marketing Campaigns with pandas
4.8(427)34k studentsBEGINNEREnglish
Korshub's take
Bridging the Gap Between Code and Commerce
Many learners struggle to see how Python libraries apply to actual business scenarios. This course solves that by moving past abstract syntax and focusing on practical marketing analytics. Using a simulated online subscription dataset, you will learn how to transform raw data into actionable business intelligence.
Who is this for?
- Marketing Professionals looking to automate reporting and level up their technical toolkit.
- Aspiring Data Scientists wanting to understand the specific workflows used within marketing organizations.
Key Learning Outcomes
- Translating business inquiries into measurable data outcomes.
- Mastering essential pandas operations like groupby(), merging, and slicing.
- Visualizing campaign performance using matplotlib.
About this course
One of the biggest challenges when studying data science technical skills is understanding how those skills and concepts translate into real jobs. Whether you're looking to level up in your marketing job by incorporating Python and pandas or you're trying to get a handle on what kinds of work a data scientist in a marketing organization might do, this course is a great match for you. We'll practice translating common business questions into measurable outcomes, including "How did this campaign perform?", "Which channel is referring the most subscribers?", "Why is a particular channel underperforming?" and more using a fake marketing dataset based on the data of an online subscription business. This course will build on Python and pandas fundamentals, such as merging/slicing datasets, groupby(), correcting data types and visualizing results using matplotlib.
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