250+ Exercises – Data Science Bootcamp in Python

Short Description

Improve your Python programming skills and solve over 250 data science exercises

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

SQL DEVELOPER:

  • SQL Bootcamp – Hands-On Exercises – SQLite – Part I
  • SQL Bootcamp – Hands-On Exercises – SQLite – Part II

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COURSE DESCRIPTION

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The course consists of 250 exercises (exercises + solutions) in data science with Python.

Packages that you will use in the exercises:

  • numpy
  • pandas
  • seaborn
  • plotly
  • scikit-learn
  • opencv
  • tensorflow

Some topics you will find in the exercises:

  • working with numpy arrays
  • working with matrices
  • random numbers
  • normal distribution
  • image as a numpy array
  • working with polynomials
  • working with dates
  • dealing with missing values
  • working with pandas Series and DataFrames
  • reading/writing files
  • working with stock market data
  • creating visualizations using seaborn and plotly
  • preparing data to the machine learning models
  • feature extraction
  • splitting data into train and test sets
  • solving systems of equations
  • building regression and classification models
  • working with neural networks – TensorFlow and Keras
  • working with computer vision – OpenCV

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

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