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What You’ll Learn


Data Analytics using Python is an intermediate level course in understanding how to play with data and perform visualizations and analytics in Python. Participants will learn to write programs in Python which will help in analysis, visualization, statistical calculations, data wrangling and manipulation. Participants who complete learning these skills will finish the course at an intermediate level of Python and will be ready to take up advanced courses in machine learning.

About the Course

These are the key takeaways that participants will gain:

  • Understand techniques to get data from different sources
  • How to analyze and make sense of data from a business perspective
  • Learn how to clean data in Python
  • Understand the functionalities of the pandas library
  • Learn how to create data models required for analysis
  • Exploratory Data Analysis using Python
  • How to formulate KPIs based on business cases
  • Understand how to plot complex visualizations
  • Learn how to extract key insights from data

Course Outline

Module 1: Understanding Data

To learn how to get data from external sources into the Python environment and manipulate and
analyze data. Before any data analytics project, it is very important to use statistical algorithms and
methods to analyze data as part of the data analytics process.

  • Python packages for data manipulation
  • Importing and Exporting datasets
  • Basics of analyzing the data

Module 2: Data Wrangling

To learn about how python libraries can be leveraged to deal with data inconsistencies, issues with
data and making them fit for data analytics. This is where 80% of today’s data scientists and
engineers spend their time and it is very important to know how to do it.

  • Dealing with data issues and preparation
  • Data Formatting and conversions in Python
  • Working with Pandas

Module 3: Exploratory Data Analysis

The objective of this module is to understand how to use appropriate statistical methods and
visualizations for descriptive analytics.

  • Performing descriptive statistics with Python
  • Correlations, Scatter-plots and charts with Matplotlib
  • Understanding data analysis with respect to various business scenarios

Module 4: Data Visualization

The objective of this module is to understand basic metric and KPIs (Key Performance Indicators)
of different business cases and plotting advanced interactive visualizations for data analysis to gain
insights from data.

  • Understanding basic metrics and KPIs
  • Visualizations using Python (Seaborn, Folium)

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