100+ Exercises – Python Programming – Data Science – NumPy

Course Details

Description

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RECOMMENDED LEARNING PATH

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PYTHON DEVELOPER:

  • 200+ Exercises – Programming in Python – from A to Z
  • 210+ Exercises – Python Standard Libraries – from A to Z
  • 150+ Exercises – Object Oriented Programming in Python – OOP
  • 150+ Exercises – Data Structures in Python – Hands-On
  • 100+ Exercises – Advanced Python Programming
  • 100+ Exercises – Unit tests in Python – unittest framework
  • 100+ Exercises – Python Programming – Data Science – NumPy
  • 100+ Exercises – Python Programming – Data Science – Pandas
  • 100+ Exercises – Python – Data Science – scikit-learn
  • 250+ Exercises – Data Science Bootcamp in Python
  • 110+ Exercises – Python + SQL (sqlite3) – SQLite Databases
  • 250+ Questions – Job Interview – Python Developer

SQL DEVELOPER:

  • SQL Bootcamp – Hands-On Exercises – SQLite – Part I
  • SQL Bootcamp – Hands-On Exercises – SQLite – Part II
  • 110+ Exercises – Python + SQL (sqlite3) – SQLite Databases

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DESCRIPTION

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Some topics you will find in the exercises:

  • working with numpy arrays
  • generating numpy arrays
  • generating numpy arrays with random values
  • iterating through arrays
  • dealing with missing values
  • working with matrices
  • reading/writing files
  • joining arrays
  • reshaping arrays
  • computing basic array statistics
  • sorting arrays
  • filtering arrays
  • image as an array
  • linear algebra
  • matrix multiplication
  • determinant of the matrix
  • eigenvalues and eignevectors
  • inverse matrix
  • shuffling arrays
  • working with polynomials
  • working with dates
  • working with strings in array
  • solving systems of equations

The course is designed for people who have basic knowledge in Python and NumPy package. It consists of 100 exercises with solutions.

This is a great test for people who are learning the Python language and data science and are looking for new challenges. Exercises are also a good test before the interview. Many popular topics were covered in this course.

If you’re wondering if it’s worth taking a step towards Python, don’t hesitate any longer and take the challenge today.

Who is this course for?

  • everyone who wants to learn by doing
  • everyone who wants to improve their Python programming skills
  • everyone who wants to improve their data science skills
  • everyone who wants to prepare for an interview

Requirements

  • completed course ‘200+ Exercises – Programming in Python – from A to Z’
  • completed course ‘210+ Exercises – Python Standard Libraries – from A to Z’
  • completed course ‘150+ Exercises – Object Oriented Programming in Python – OOP’
  • basic knowledge of NumPy library

What You'll Achieve with Our Courses?

Career Growth

Move forward in your profession with skills that open real job opportunities.

Personal Mastery

Build confidence and habits that improve both your life and mindset.

Efficiency

Learn faster with concise modules and hands-on application.

Global Connections

Join an international community to learn, share, and grow together.

Recognised Certificate

Get a professional certificate that validates your efforts and skills.

Flexibility

 Study at your own pace, anytime, anywhere.

FAQ

What makes BrainLearn courses different?

Our courses combine expert-led content, real-world practice, and efficiency-driven design so you learn quickly and retain more.

Yes! Each course ends with a professional certificate you can use for your CV or LinkedIn.

That depends on your pace—our courses are flexible. With just a few hours per week you can make steady progress.

Absolutely. You can learn on desktop, tablet, or mobile—wherever and whenever suits you best.

Yes, BrainLearn includes mentorship and a global community where you can ask questions and exchange ideas.

No worries: since the path is self-paced, you can catch up on your own schedule without any penalties.

Explore the course descriptions, check the learning outcomes, or reach out to us—you’ll also find popular courses highlighted to help you choose.

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