Data Analysis with Python [Video]

More Information
  • Installing the core Python tools for data analysis
  • Dealing with different data types in Python
  • Using NumPy for fast array computation
  • Using Pandas for data analysis
  • Framing a Data Science problem and using Python tools to solve it

Python is a popular programming language ,widely used in many scenarios and easy to use to use. Data Science is an interdisciplinary field that employs techniques to extract knowledge from data. As one of the fast growing fields in technology, the interest for Data Science is booming, and the demand for specialized talent is on the rise.

This course introduces the audience to the field of Data Science using Python tools to manage and analyze data. You can learn some of the fundamental tools of the trade and apply them to real data problems. And along the way it discusses the use of Python stack for data analysis and scientific computing, and expands on concepts of data acquisition, data cleaning, data analysis and machine learning.

Style and Approach

A fun and friendly course packed with step by step instructions, it shows you how to get up and running with Python virtual environments using Conda. This course is divided into clear chunks so you can learn at your own pace.

We’ll discuss the creation and management of different environment, how to install Python packages for Data Science and how to use Jupyter notebooks as development tool.

  • Easy to follow guide that will take you from being a beginner to a regular data science task
  • Get solutions to your common and not-so-common data science problems. 
  • Highly Practical, real world examples that make data science your comfort zone.
Course Length 2 hours 26 minutes
ISBN 9781788290548
Date Of Publication 28 Apr 2017


Marco Bonzanini

Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a Ph.D. in information retrieval from the Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems.

He maintains a personal blog at, where he discusses different technical topics, mainly around Python, text analytics, and data science.

When not working on Python projects, he likes to engage with the community at PyData conferences and meetups, and he also enjoys brewing homemade beer.