Online Trainings

Disclaimer: Over time, I wrote a lot of independent articles and decided to combine them in Online Trainings. I also added a lot of exclusive content for those trainings. I want those trainings to be completely free, but in exchange, I would be really grateful if you could leave comments under the articles when each time you finish reading one. This will allow me to collect feedback on the content and improve the quality of my content over time. Thank you in advance :)

Discover Python for Data Analysis

A training to discover Python for data analysis. No background is needed, but if you already master some of those topics, ignore them and jump to the next. In this training, you’ll learn:

  • What is a terminal and how to use bash commands
  • How to install Python
  • How to code in Python (IDEs, Jupyter Notebooks…)
  • How to write functions and classes in Python
  • How to share your code on Github
  • How to install packages from Github or Pypy
  • How to load and analyze data in Python
  • How to visualize data in Python
  • How to build your own dashboard
  • Key concepts of machine learning

Machine Learning with Python

A more advanced program targeted for those with a previous Python and data analysis experience, or who have finished the “Discover Python for Data Analysis” training, with some linear algebra and statistics understanding. We will dive in details into:

  • Statistics with Python
  • Key concepts of Machine Learning
  • The core libraries for Machine Learning in Python
  • Supervised Machine Learning algorithms and their implementation
  • Unsupervised Machine Learning algorithms and their implementation

Deep Learning with Python

Deep Learning is overperforming almost every approach developed so far in domain-specific as well as generic tasks. With this training, dive in the fascinating world of Deep Learning. This requires a descent level in linear algebra and calculus. We will cover:

  • What is deep learning
  • How is it similar to a neurone
  • What is the Rosenblatt’s perceptron
  • Multilayer perceptron
  • Deep Learning Frameworks (Tensorflow, Pytorch)
  • Classification and regression
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Generative Adversarial Networks

Natural Language Processing

Ever heard of Natural Language Processing (NLP)? This training requires to have finished the “Deep Learning with Python” training. We will cover the following concepts:

  • Overview of Natural Language Processing
  • Part-of-Speech and Named Entity Recognition
  • Text Embedding
  • Text Similarity
  • Text Classification
  • Introduction to chatbots
  • Sequence Models
  • Transformers