Basic Python for Data Science

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Course Objectives

The objective of this course is to introduce participants to the Python programming language,
which is a widely used and up-coming statistical programming language. In this course,
participants will be exposed to data manipulation and data wrangling with Python, produce visualization for data exploration.

Description

By the end of the class, students learn to:

  • Utilize Anaconda and Jupyter Notebook for Python programming
  • Acquire and manipulate data using the Pandas package.
  • Comprehend and apply the Numpy package for scientific computing
  • Produce visualization using basic graphics functions and experience the matplotlib
    packages.

Target Audience

This short course intended audiences are IT professionals, data analyst and professionals who
want to learn about Python programming.

Training Outline

Day 1
  • Overview of Python Programming Language
  • Installing and setting up Anaconda and Jupyter Notebook
  • Python Data Types: String, List
  • Laboratory Exercise
  • Python Data Types: Tuple, Dictionary
  • Laboratory Exercise
Day 2
  • Control Structures
  • Creating and Using Functions
  • Python Logic
  • Laboratory exercise
  • Python Repetition – For loop, While Loop
  • List Comprehension
  • Laboratory exercise
Day 3
  • Numpy Package
  • Working with arrays
  • Laboratory Exercise
  • Understanding of broadcasting
  • Laboratory Exercise
  • Manipulation of arrays
  • Laboratory Exercise
Day 4
  • Introduction to Pandas Package
  • Series and Data Frame
  • Creating, Viewing, Loading and Saving Data
  • Laboratory Exercise
  • Select, Manipulate and Analyze Data
  • Laboratory Exercise
  • Wrap Up

Prerequisite

Basic knowledge of programming is preferable.