250+ Exercises - Data Science Bootcamp in Python

250+ Exercises – Data Science Bootcamp in Python

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What you’ll learn:
  • solve over 250 exercises in data science in Python
  • deal with real programming problems
  • deal with real problems in data science
  • work with libraries numpy, pandas, seaborn, plotly, scikit-learn, opencv, tensorflow
  • work with documentation
  • guaranteed instructor support
Description:

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
  • 200+ Questions – Job Interview – SQL Developer

JOB INTERVIEW SERIES:

  • 250+ Questions – Job Interview – Python Developer
  • 200+ Questions – Job Interview – SQL Developer
  • 200+ Questions – Job Interview – Software Developer – Git
  • 200+ Questions – Job Interview – Data Scientist

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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
Who this course is for:
  • everyone who wants to learn by doing
  • everyone who wants to improve their programming skills in Python
  • people who are preparing for interviews
  • people interested in data science
  • data scientists
  • data analytics
  • machine learning engineers

Enroll Now -:

Free 12800 100% off

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