Data Wrangling with Python 3.x

Learn the data life cycle—from acquisition to processing to analysis—in Python

Ratings: 3.35 / 5.00




Description

You might be working in an organization, or have your own business, where data is being generated continuously (structured or unstructured) and you are looking to develop your skillset so you can jump into the field of Data Science. This hands-on guide shows programmers how to process information.

In this course, you will gather data, prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, and more! This course will equip us with the tools and technologies, also we need to analyze the datasets using Python so that we can confidently jump into the field and enhance our skill set. The best part of this course is the takeaway code templates generated using the real-life dataset.

Towards the end of the course, we will build an intuitive understanding of all the aspects available in Python for Data Wrangling.

About the Author

Jamshaid Sohail is a Data Scientist who is highly passionate about Data Science, Machine learning, Deep Learning, big data, and other related fields. He spends his free time learning more about the field and learning to use its emerging tools and technologies. He is always looking for new ways to share his knowledge with other people and add value to other people's lives. He has also attended Cambridge University for a summer course in Computer Science where he studied under great professors and would like to impart this knowledge to others. He has extensive experience as a Data Scientist in a US-based company. In short, he would be extremely delighted to educate and share knowledge with, other people.

What You Will Learn!

  • Effectively pre-process data (structured or unstructured) before doing any analysis on the dataset.
  • Retrieving data from different data sources (CSV, JSON, Excel, PDF) and parse them in Python to give them a meaningful shape.
  • Learn about the amazing data storage places in an industry which are being highly optimized.
  • Perform statistical analysis using in-built Python libraries.
  • Hacks, tips, and techniques that will be invaluable throughout your Data Science career.

Who Should Attend!

  • This course is for Python developers, data analysts, and IT professionals who are keen to explore data analytics/insights to enrich their current personal or professional projects.