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Data Analytics with Python; Python for Data Scientists

Course Code

BD80

Duration

3 Days

Experience and background in software development.
Helpful to have some background in analytics or machine learning.
Some background in Python highly recommended though a brief intro is included.
Python has become a powerful language and environment for performing data science. It combines a robust, object-oriented language with a powerful library of data science packages, such as numpy, scipy, matlibplot, scikit-learn, and pandas. These tools together make python one of the best combinations of robust programming language together with great library support.
This course is designed for Data Analysts, Data Scientists, and Developers.

In this course, participants will learn:

  • Quick Python primer
  • Quick primer on data science algorithms
  • NumPy
  • SciPy
  • Pandas
  • Scikit-learn
Python language Overview
Basics of Python language
ow to edit, run, and test python code
ntroducing the Anaconda distribution of Python.
DEs
Using Jupyter notebooks.

Pandas
Series and Dataframes
Loading data using Pandas
Labs

NumPy and SciPy
Arrays
Matricies
Linear Algebra
Labs
Visualizing data with matlibplot

Doing Data Science with Scikit-learn
Introducing Scikit-Learn
Clustering Data
Building a Classifier

Big Data With PySpark
Introduction to Spark and PySpark
Using the Spark framework for Big Data
Using MLLib or Data Science in PySpark
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