Python for Data Science
This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. Upon its completion, you’ll be able to write your own Python scripts and perform basic hands-on data analysis. This course covers the key tools and libraries used by Python for Data Science including NumPy and Pandas.
About This Course
Data science has become the de facto field in computational and predictive statistical analysis and is used by various organizations to make data-driven decisions.
Python is a very versatile language since it has a wide array of functionalities already available. The sheer range of functionalities might sound too exhaustive and complicated, you don’t need to be well-versed with them all. Python has become an indispensable tool for the data science analyst and an important tool for any data scientist.
Most data scientists have a few go-to libraries for their daily tasks like:
- for performing data cleaning and analysis – pandas
- for basic statistical tools – numpy, scipy
- for data visualization – matplotlib, seaborn
Learning Objectives
Target Audience
- Anyone who wants to learn Data Science
Curriculum
Introduction to Python for Data Science
Overview of Python for Data Science
Python Essentials
IPython Interactive Interpreter
NumPy Open Source Extension Module
Read/Write in Python
Data Loading and Preprocessing
Practical Exercise
Introduction to Numpy
Introduction to Pandas
Manipulating and Analyzing Data in Pandas DataFrames
Data Visualization Using Seaborn
Advanced Data Visualization Using Seaborn
