What you will learn

  • how to use a classification model to automate tasks

  • Develop a POC using a low-code machine learning

  • Develop your intuition on how to automate low-value tasks using Machine Learning

  • Your learning experience

    Learn by doing, develop your intuition and understand basic concepts.

  • Our objective

    To provide you with a learning experience to help you achieve your goals.

  • Prerequisites

    Basic concepts in python

  • Applications

    (low value) tasks automation

  • Tools

    Jupyter Notebook or Visual Studio Code, PyCaret, (optional) Power BI

Content of the hands-on project

    1. Welcome!

    2. How to use this hands-on project

    3. Prerequisites

    4. Premium Option

    5. Before we start...

    1. Project overview

    2. Learning objective

    3. Resources

    4. Targeted Learners

    5. Setting up the environment

    6. Data

    1. Description of the task

    2. Solution

    1. Description of the task

    2. Tips and Tricks

    3. Solution

    1. Description of the task

    2. Tips and Tricks

    3. Solution

    1. Description of the task

    2. Tips and Tricks

    3. Solution

About this course

  • Gratuit
  • 43 leçons
  • 0 heures de contenu vidéo


This project is for people who are interested in using a low-code Machine Learning library in order to build IA product. I’ll teach you how to build an end-to-end classification model using PyCaret a low-code Python Machine Learning Open-Source Library. You don’t need to be a data scientist to take this project, but you should be familiar with Python and the main concepts on Machine Learning to get the most out of this project. the primary objective is to give you a concrete example of how to use a classification model to automate tasks (intelligent automation). You will then be equipped to think about which low value tasks (done by you, your team, or at the company level) that can be automated using machine learning models. You will also be equipped to quickly and confidently develop a POC using a low-code tools like PyCaret.


Mohamed Jendoubi

Data Scientist, Founder of Uluumy

I am passionate about artificial intelligence, entrepreneurship and learning new knowledge. I am motivated every day by the desire to have a positive impact around me. At the Business Development Bank of Canada (bdc), where I was a data scientist for more than a decade, I contributed to several analytical and digital transformation projects within the marketing and financing teams. My work at bdc has also allowed me to see the magnitude of the challenges of digital transformations for small and medium-sized businesses. To succeed in their transformation, these companies need to improve the skills of their employees. I founded Uluumy, to help transform the challenges experienced by entrepreneurs and professionals into opportunities by focusing on professional development and continuing education.