A step-by-step guide for creating an authentic data science portfolio project

A step-by-step guide for creating an authentic data science portfolio project

In this blog post, I want to show you how I develop interesting data science project ideas and implement them step by step, such as exploring Germany’s biggest frequent flyer forum Vielfliegertreff. If you are short on time, feel free to skip to the conclusion TLDR.

As an inspiring data scientist,** building interesting portfolio projects is key to showcase your skills.** When I learned coding and data science as a business student through online courses, I disliked that datasets were made up of fake data or were solved before like Boston House Prices or the Titanic dataset on Kaggle.

In this blog post, I want to show you how I develop interesting data science project ideas and implement them step by step, such as exploring Germany’s biggest frequent flyer forum Vielfliegertreff. If you are short on time, feel free to skip to the conclusion TLDR.

Step 1: Choose your passion topic that is relevant

As a first step, I think about a potential project that fulfills the following three requirements to make it the most interesting and enjoyable:

  1. Solving my own problem or burning question.
  2. Connected to somerecent event to be relevant or especially interesting.
  3. Has not been solved or covered before.

As these ideas are still quite abstract, let me give you a rundown of how my three projects fulfilled the requirements:

Overview of my own data science portfolio projects fulfilling the three outlined requirements.

As a beginner, do not strive for perfection, but choose something you are genuinely curious about and write down all the questions you want to explore in your topic.

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