What you will 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
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RECOMMENDED LEARNING PATH
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PYTHON DEVELOPER:
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200+ Exercises – Programming in Python – from A to Z
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210+ Exercises – Python Standard Libraries – from A to Z
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150+ Exercises – Object Oriented Programming in Python – OOP
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150+ Exercises – Data Structures in Python – Hands-On
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100+ Exercises – Advanced Python Programming
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100+ Exercises – Unit tests in Python – unittest framework
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100+ Exercises – Python Programming – Data Science – NumPy
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100+ Exercises – Python Programming – Data Science – Pandas
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100+ Exercises – Python – Data Science – scikit-learn
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250+ Exercises – Data Science Bootcamp in Python
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110+ Exercises – Python + SQL (sqlite3) – SQLite Databases
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250+ Questions – Job Interview – Python Developer
SQL DEVELOPER:
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SQL Bootcamp – Hands-On Exercises – SQLite – Part I
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SQL Bootcamp – Hands-On Exercises – SQLite – Part II
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110+ Exercises – Python + SQL (sqlite3) – SQLite Databases
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200+ Questions – Job Interview – SQL Developer
JOB INTERVIEW SERIES:
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250+ Questions – Job Interview – Python Developer
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200+ Questions – Job Interview – SQL Developer
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200+ Questions – Job Interview – Software Developer – Git
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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:
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numpy
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pandas
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seaborn
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plotly
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scikit-learn
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opencv
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tensorflow
Some topics you will find in the exercises:
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working with numpy arrays
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working with matrices
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random numbers
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normal distribution
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image as a numpy array
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working with polynomials
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working with dates
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dealing with missing values
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working with pandas Series and DataFrames
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reading/writing files
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working with stock market data
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creating visualizations using seaborn and plotly
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preparing data to the machine learning models
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feature extraction
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splitting data into train and test sets
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solving systems of equations
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building regression and classification models
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working with neural networks – TensorFlow and Keras
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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.
Don’t hesitate and take the challenge today!
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