Course Description

Learn the fastest growing programming language in the world!

Python is the most popular programming language in the world since 2019, according to GitHub and Google Trends, surpassing longstanding Java, and JavaScript in popularity. Python is the most prefered language in Data Science. It is the easiest and most efficient language to use when manipulate, analyze, and visualize big amounts of data! This course is designed for learners that have never used Python before.

Introduction to Python for Data Science is a hands on course, you will learn to write code from the first lesson!


Course Outcomes

  • Store, access, and manipulate data in lists and dictionaries

  • Write Python functions to facilitate code reuse

  • Use Jupyter Notebook, which is an interactive computational environment, in which you can combine code execution, rich text, mathematics and plots

  • Get certification in Python upon successful exam fulfillment





Training Content

Data structures are the fundamental constructs that provides a particular way of organizing data so it can be accessed efficiently, depending on your use case.

  • List
  • Tuples
  • Dictionaries
  • Sets
  • Boolean operators
  • Functions
  • MAP
  • Working with files
  • Time library
  • JSON files

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

  • Series
  • Dataframes
  • Basic commands
  • Slices
  • Transformations
  • Map / apply functions
  • Cleaning

Pandas groupby is used for grouping the data according to the categories and apply a function to the categories. An essential piece of analysis of large data is efficient summarization using aggregations.

  • Pandas groupby
  • Pandas aggregations

Data visualization is the most important step in the life cycle of data science, data analytics, or we can say in data engineering. It is more impressive, interesting and understanding when we represent our study or analysis with the help of colours and graphics. 

  • Pandas visualizations: histograms, bar plots, scatter plots

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