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DATA SCIENCE WITH PYTHON ONLINE TRAINING  COURSE

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Data science with python Course Content

 

Unit 1: Introduction to Python

Python is a high-level programming language. You will learn the basic syntax and data structures in Python. We demonstrate and run codes within Ipython notebook, which is a great tool providing a robust and productive environment for interactive and exploratory computing.

Introduction to I python notebook

Basic objects in Python

Variables and self-defining functions

Control flow

Data structures

Unit 2: Explore Deeper with Python

Python is an object-oriented programming (OOP) language. Having some basic knowledge of OOP will help you understand how Python codes work. More often than not, you will have to deal with data that is dirty and unstructured. You will learn many ways to clean your data such as applying regular expressions.

Introduction to object-oriented programming

How to deal with files

Run Python scripts

Handling and processing strings

Unit 3: Scientific Computation Tool

There are two modules for scientific computation that make Python powerful for data analysis: Numpy and Scipy. Numpy is the fundamental package for scientific computing in Python. SciPy is an expanding collection of packages addressing scientific computing.

Numpy

Scipy

Unit 4: Data Visualization

Python can also generate graphics easily using “Matplotlib” and “Seaborn”. Matplotlib is the most popular Python library for producing plots and other 2D data visualizations. Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing statistical graphics.

Seaborn

Matplotlib

Unit 5: Data manipulation with Pandas

Pandas provides rich data structures and functions for working with structured data. The “DataFrame” object in Pandas is just like the “data.frame” object in R. Pandas makes data manipulation (filter, select, group, aggregate, etc.) as easy as in R.

Pandas

Final Project