Data Analytics: Python Visualizations

Enrich Data Science, ML and Analytics with powerful Visualisations using Matplatlib, Seaborn and Bokeh

Ratings 4.25 / 5.00

What You Will Learn!

In depth coverage of Matplotlib, Seaborn and Bokeh Visualization Libraries.
Easy, step by step explanations with code to draw over 20 different kinds of Charts and Graphs using Python.
Extensive amount of Python - Matplotlib/Seaborn/Bokeh code used in the course are attached as downloadable resources for you to try out while you learn.
Use of Data Analytics Techniques / Exploratory Data Analysis (EDA) using several Data Generation and Manipulation Methods.
Extensive coverage of NumPy and Pandas Data capabilities using Python.
Learn the art of presenting Data in the form of Powerful, Innovative and Intuitive Visualisations that your stakeholders will love.
Application of Business and real-life Scenatios to create Visualisations.

Description

If you are working on Data Science projects and want to create powerful Visualization and Insights as outcome from your projects, this course is for you!!!

If you are working on Machine Learning Projects and want to find patterns and insights from your Data on your way to building Models, this course is for you!!!

If you are a Business Analyst or Functional Analyst and want to build powerful Visualizations for your stakeholders, this course is for you!!

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This course is exclusively focused on explaining how to build fantastic Visualizations using Python. Covers more than 20 types of Visualizations using the most popular Python Visualization Libraries Matplotlib, Seaborn and Bokeh. It covers Data Analytics that leads to building these visualizations so that the learners understand the flow of analysis to insights.

This course takes a holistic approach towards teaching Visualizations:

- Take real-life, business scenarios and raw data to go through detailed Exploratory Data Analysis (EDA) techniques to prepare your raw data to suit the appropriate Visualization needs.

- Data Analytics and Exploratory Data Analysis Techniques using multiple different data structures using Numpy and Pandas libraries.

- Explain Chart/Graph types, customization/configuration and vectorization techniques.

- Throughout the course, extensive amount of Code demo along with concepts as a balanced approach to teaching.

- Every concept is taught by going deeper into foundational techniques and deeper customizations on Visualizations.

Extensive Quizzes are infused at logical points to validate the learning effectiveness.

[NOTE: All the code used in the Lectures are attached as downloadable resources. You may download them and try out while going through the lectures.]

Who Should Attend!

Python, Machine Learning Developers
Data Scientists
Data Analysts
Big Data Professionals
Business Analysts
Leaders, Managers, anyone whose job involves presenting Data in the form of Visuals
Techno-Functional Analysts
Developers
Architects
Systems Analysts
Anyone who is in a role in handling and managing Data