Master Python for Data Science in 5 Days—No Experience Required!

Say goodbye to feeling overwhelmed by technical jargon and hello to building confidence in data science. Learn the essentials of Python through relatable stories, real-world projects, and clear, step-by-step guidance.
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Bite-sized lessons
Interactive learning experience
Concrete examples
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In just 5 days, you’ll:

  • Build confidence with Python fundamentals like variables, loops, and lists.
  • Clean and analyze data using libraries like Pandas and NumPy.
  • Create stunning data visualizations with Matplotlib.
  • Solve real-world problems through data-driven projects.
  • Learn how to create a Data Analysis project.

Is our guide right for you?

  • You know how to code but you don't know very well how to use Python
  • You struggle to do simple data analysis
  • You want to understand the major Data Science libraries
  • You want to see concrete examples of Data Science libraries' implementation

By the end of this course, you’ll be able to …

Use Python in your Data Science projects

Learn the fundamentals of Python to quickly create Data Science projects.

Use Data Science libraries

We'll see concrete implementation examples of Data Science libraries like Pandas, NumPy, Scikit-learn.

Perform a simple data analysis

We'll finish the guide with a simple exploratory data analysis of the Netflix dataset.

What's inside?

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Day 1: Python Fundamentals

Variables, lists, dictionaries, and basic operations.
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Day 2: Data Wrangling 101

Clean, process, and analyze data with Pandas and NumPy. 
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Day 3: Data Visualization 

Create insightful charts with Matplotlib and Seaborn. 
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Day 4: Applying Insights

Analyze and visualize trends with concrete datasets. 
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Day 5: Real-World Project

Solve a meaningful problem by analyzing patient data to identify trends and improve outcomes.

Enjoy these extra bonuses

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Your Python Cheatsheet

Whether you’re solving your first project or revisiting Python basics, this cheatsheet will be your go-to resource to save time and boost confidence.
  • Simplify key concepts like variables, loops, and dictionaries.
  • Provide a quick reference for essential libraries like Pandas, Matplotlib, and NumPy.
  • Include clear, beginner-friendly examples of data wrangling, visualization, and more.
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Math for Data Science Essentials

Grasp fundamentals with engaging illustrations so you can understand quickly the concepts. This guide is designed to help you understand probability, statistics, linear algebra, and calculus and their applications to machine learning with visual explanations.

Join our exclusive course

I'll be waiting for you in the first module!

Frequently asked questions

Do I need to know how to code?

Not necessarily! You'll be able to test the code directly on Git Colab.

Will we be doing machine learning?

We will work on the previous steps which allow us to do data analysis.

Meet your Host

I’m Assitan, founder of Codistwa, and I’m passionate about helping underrepresented voices in tech build impactful, inclusive AI systems. With 10 years of experience in web development then as a data science mentor, I specialize in making complex concepts relatable and actionable.

Assitan Koné

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