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Data Analysis and Visualization with Python

Extend your Python skills to provide a solid foundation in data analysis & visualization.

  • 100% Online
  • 8 Weeks
Course Description

As a data scientist you will need to build powerful predictive models using Machine & Deep Learning techniques, and interpret these models. Before you can do so, however, you will need to know how to get data into Python, analyze and visualize them.

You will learn about NumPy, the fundamendal Python library for efficient scientific computations and how to import data into Python from various sources, such as CSV, Excel, SQL databases and the web.

Pandas DataFrames are the de facto industry standard to work with tabular data in Python. You will learn all aspects of working with DataFrames like importing, tidying, manipulating and rearranging data. You will also learn how to compine and merge DataFrames.

Data visualization is a key skill for aspiring data scientists. Matplotlib makes it easy to create meaningful and insightful plots. You will learn how to build various types of plots, and customize them to be more visually appealing and interpretable.

Finally, you will learn how to work with and visualize two special kinds of data: Time Series and Geospatial.

Who is this for?

Anyone interested in, planning to learn, or already learning data science.

Basic knowledge of Python is required. Consider taking course Programming with Python first if you are new to programming.

What is provided to you?
  • Updated syllabus written by industry experts
  • Weekly live classroom with certified trainers
  • Classroom video recordings
  • Assignments and code reviews by mentors
  • Full access to our Social Learning platform
  • Free certicate of completion

We enlist industry experts to plan, author and review our syllabus. It will guide you from fundamental concepts all the way to full scale implementations. It is constantly updated, and you get lifetime access.

Week 1
Powerful Computing with NumPy

NumPy is a fundamental Python package to efficiently practice data science. Expand your skillset by learning scientific computing.

Importing Data from Everywhere

Learn to import data into Python from various sources, such as CSV, Excel, SQL and the web.

Week 2
Week 3
DataFrames with Pandas

Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

Manipulating DataFrames with Pandas

Learn how to tidy, rearrange, and restructure your data using versatile Pandas DataFrames.

Week 4
Week 5
Merging DataFrames with Pandas

Learn how to compine and merge DataFrames, an essential part of your Data Scientist's toolbox.

Data Visualization with Matplotlib

Learn complex visualization techniques using Matplotlib library.

Week 6
Week 7
Working with Time Series

Learn how to analyze time series data and visualize seasonality, trends and other patterns.

Working with Geospatial Data

learn how to interact with, manipulate and augment real-world data using their geographic dimension in the most common formats (GeoJSON, shapefile, geopackage) and visualize them in maps.

Week 8