Introduction to Python

with Martin Ganchev

Laying the foundations of programming in Python to prepare you for deploying machine and deep learning algorithms later in the training.

3 hours 41 lessons
Start course
41 High Quality Lessons
26 Practical Tasks
3 Hours of Content
Certificate of Achievement

Course Overview

Python is one of the most widely used programming languages among data scientists. This course will show you the technical advantages it has over other programming languages. You will start working with its modules for scientific computing, and you will begin to understand why these functionalities make Python the preferred choice in finance, econometrics, economics, data science, and machine learning.

Topics covered


What You'll Learn

This course will introduce you to the world of Python. You will learn about Python’s technical advantages, specific features, modules, functionalities, and more.

Basic Python syntax 
Work with variables, operators, and conditional statements 
Create and use functions 
Study Python sequences and iterations 
Understand Object-Oriented Programming (OOP) 
Import modules in Python 


Student feedback


3166 ratings
5 stars
2682 (85%)
4 stars
396 (13%)
3 stars
76 (2%)
2 stars
7 (0%)
1 star
5 (0%)
Filter by rating
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • Newest
  • Oldest
I enjoyed the course. Nevertheless I noticed that you often do not use the format which is suggest by PEP. You for example write print (n) instead of print(n). Also you are still using Jupyter Notebook while Jupyter Lab is much better. As I did not use Jupyter Notebook that often and it Jupyter Lab seems to be a much better version of it it's not that dramatic. Just the first sessions with key shortcuts and what you can and cannot do when browsing python files in notebook are outdated. Why should I learn Jupyter Notebook if there is Jupyter Lab and Jupyter Hub.
i have heard a lot about python programming from friends, and from the way they do talk about it, it seemed pretty clear it'd be really difficult to comprehend or even grasp a fraction of it, but after going through this course with you guys,the reverse became the case because my learning so far has been really smooth and that is absolutely why i think you guys are simply the best
It is a very good as a step ahead to me as a beginner in programming. Good content and lessons were structured in away that integrated to ease the way through. If i could add a comment from my point of view I would recommend to increase the exercises and their difficulties since many of which are close to the lectures in their content and not challenging to the learner.
The videos are too short. Covers very basic. Exercises , example should cover some medium or high level complexity questions too. Many questions in exercises are based on theoretical concepts. Videos could have been longer instead of these many short ones. Would have been better to get all exercises in to one shot in notebook
Overall I've liked this course - great intro but I have to admit this isn't my first course on python 101. Few of the exercises (e.g the for & while loop) contained some elements where I was slightly puzzled as that wasn't discussed in the lecture itself.
  • 1
  • 2
  • 3
  • ...
  • 52
  • ...
  • 102
Martin Ganchev

“If you want to become a data scientist, you definitely need Python! In this hands-on course, I will teach you Python programming fundamentals – the basic, foundational tool you need before diving into machine learning in Python.”

Martin Ganchev

Worked at the European Commission

Introduction to Python

with Martin Ganchev

Start Course