On this course you will start Python programming language from the beginning, but it is of great help to have basic programming concepts and knowledge. With the right instructor training programming does not need to be difficult, programming is structured and logic. This training is 100% in practice “Hands On”. We learn by doing.

Python is a general-purpose programming language gaining a lot of ground rapidly in the last few years. Python is a popular language for data science and machine learning. Companies process data from different sources to gain more insights to their data. In this course you will learn data processing from different sources and ways to store and manipulate data, and helpful data science.

Audience profile

Programming beginners and students with basic programming experience who wish to continue learning Python programming language to prepare themselves with world market knowledge. This course is a basic course and from here on you can continue to advance in data science and machine learning.


This course teaches the fundamentals of the Python programming language. This course is oriented towards data processing. At the end of this course you will be able to process data from different sources and different formats, like JSON etc and independently code and learn any Python package of your interest.

This course includes a project coded by the students and the instructor.

  • General introduction
    • Python programming introduction, history and usage
    • Installation, configuration and first python program
    • Variables and basic data types (strings, lists, dictionaries, …)
    • Input / Output operations
    • Basic operators
  • Python knowledge
    • Control Flow ( if-else conditions, For and While loops, …)
    • Boolean and binary operations
    • Lists, tuples, sets, dictionaries
    • Functions
    • String methods
    • List & dictionary comprehension
    • Data conversion – date functions
    • Packages
  • Object Oriented Programming
    • Intro to Object-Oriented programming (OOP)
    • Objects & Class
      • Attributes and methods
    • Polymorphism and Inheritance
    • Exceptions
    • Generators
    • Read and write files
  • Numpy and Pandas, HTTP, JSON format
    • Introduction to Numpy and Pandas
    • Connection between Numpy and Pandas
    • HTTP protocol – Import data from online sources
    • JSON format – Import data from online sources
  • Advancing with Pandas and data manipulation
    • Indexing
    • Cut
    • Filter
    • Revision
  • Matplotlib, data visualization
    • Data visualization: scatter plots, line plots, box plots, bar charts,and histograms with matplotlib
    • Interpreting picture structure
    • Modifying charts, important attributes and arguments
  • Summary and Project
    • Recall of all the knowledge gained
    • Project with real data sets
    • Conclusion


Basic programming concepts with any programming language and the desire to learn Python programming aiming at technologies of the future.