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