Course Overview

Data science has emerged as one of the most important and fastest growing fields in the modern corporate world. The demand to build intelligent systems from historical data is at an all-time high. Supplying the computational firepower behind this demand is the powerful and popular Python programming language which has the flexibility to build nearly any application.

This two-day data science training course is designed for those just getting acquainted with the field of data science. By the end of the course, the foundations of Python will be covered as well as an introduction to the most common tools and concepts that are used during a data analysis.

Key Learning Areas

Python is easy to learn with concise and expressive syntax, and capable of powering any organization’s analytics requirements. This course will focus on teaching the fundamentals so that you can explore datasets and build simple machine learning workflows.

You will learn:

  • Setting up your Python environment for data science
  • Basic data types and their operations
  • Working with strings
  • Everything is an object with attributes and methods
  • Common data structures - lists, tuples, dictionaries, and sets
  • Jupyter Notebook as a development environment
  • Data manipulation and exploration with Pandas
  • Data Visualization with Matplotlib and Seaborn
  • Developing a routine for doing end-to-end data analysis

The ultimate goal of this course is to teach ‘end-to-end’ data analysis. Upon completion, you will be able to ingest any messy dataset, transform it so that it is tidy, detect and correct anomalies, make insightful and beautiful visualizations, run machine learning models, and deliver a final product.

Course Outline

The course uses the latest version of Python 3 to cover the fundamentals of Python before diving into data science. All material is contained in Jupyter Notebooks with over 100 exercises with detailed solutions.

Course Introduction and Setup

  • Installation of the Anaconda Python distribution
  • Setting up an environment to properly run Python

Introduction to Python

  • Basic data types
  • Python as a calculator
  • Strings
  • Lists
  • Control flow
  • Functions
  • Data Structures

Introduction to Data Science

  • Selecting subsets of data
  • Split-Apply-Combine
  • Tidying messy datasets
  • Visualization
  • Applied machine learning

Who Benefits

This course is for those with little to no programming experience that want to get introduced to data science and machine learning.


There are no formal prerequisites as this class is designed for absolute beginners, but previous exposure to programming will be helpful.