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250+ Exercises – Data Science Bootcamp in Python


Enhance your Python programming abilities and remedy over 250 knowledge science workouts!

Requirements

  • accomplished course ‘200+ Exercises – Programming in Python – from A to Z’
  • accomplished course ‘210+ Exercises – Python Commonplace Libraries – from A to Z’
  • accomplished course ‘100+ Exercises – Python Programming – Data Science – NumPy’
  • accomplished course ‘100+ Exercises – Python Programming – Data Science – Pandas’
  • accomplished course ‘100+ Exercises – Python – Data Science – scikit-learn’

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 Commonplace Libraries – from A to Z
  • 150+ Exercises – Object Oriented Programming in Python – OOP
  • 150+ Exercises – Data Constructions in Python – Arms-On
  • 100+ Exercises – Superior Python Programming
  • 100+ Exercises – Unit checks 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 – Arms-On Exercises – SQLite – Half I
  • SQL Bootcamp – Arms-On Exercises – SQLite – Half II

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COURSE DESCRIPTION

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The course consists of 250 workouts (workouts + options) in knowledge science with Python.

Packages that you’ll use in the workouts:

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

Some matters you can find in the workouts:

  • working with numpy arrays
  • working with matrices
  • random numbers
  • regular distribution
  • picture as a numpy array
  • working with polynomials
  • working with dates
  • coping with lacking values
  • working with pandas Collection and DataFrames
  • studying/writing information
  • working with inventory market knowledge
  • creating visualizations utilizing seaborn and plotly
  • getting ready knowledge to the machine studying fashions
  • function extraction
  • splitting knowledge into practice and take a look at units
  • fixing programs of equations
  • constructing regression and classification fashions
  • working with neural networks – TensorFlow and Keras
  • working with laptop imaginative and prescient – OpenCV

This can be a nice take a look at for people who find themselves studying the Python language and are in search of new challenges. The course is designed for individuals who have already got primary information in Python and information about knowledge science libraries. Exercises are additionally a great take a look at earlier than the interview. Many in style matters have been lined in this course.

Don’t hesitate and take the problem in the present day!

Who this course is for:

  • individuals who wish to enhance their programming abilities in Python
  • people who find themselves getting ready for interviews
  • folks in knowledge science
  • knowledge scientists
  • knowledge analytics
  • machine studying engineers



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