Artificial Intelligence


480 DT


12 Weeks


Program :

  • Introduction to Artificial Intelligence

    • Introduce Artificial Intelligence and its fields of application

    • Introduce Artificial Intelligence sub-fields.

    • Differentiate between Artificial Intelligence, Machine Learning, Deep Learning and Data Science.

  • Learning Python

    • Learn how to write code with Python, dive deeper into its optimization methods, and advantages.

    • Learn how to manipulate Python by examining its data structures and predefined functions to solve mathematical problems

    • Master several Python libraries such as Numpy, Pandas…

    • Workshop: Live-coding.

  • Data pre-processing

    • Learn how to clean up unnecessary information, manage missing values and prepare data for the analysis and processing phase.

  • Data processing and visualization

    • Learn how to explore data and visualize graphs using the appropriate Python libraries: Matplotlib, Seaborn, Pandas, and Numpy.

    • Workshop: Live-coding on a specific use-case

  • Machine learning

    • Introduce the Scikit-learn library, explain the difference between supervised learning (linear regression, k-nearest neighbors, decision tree, random forests...) and unsupervised learning (Hierarchical classification, partitioning (k-means), association rule...) in Machine learning.

    • Understand the maths under machine learning models.

    • Understand feature selection techniques.

    • Understand optimization techniques.

    • Practice with some use cases.

    • Workshop: Live-coding of a machine learning pipeline

  • Final Project: Create an artificial intelligence pipeline based on everything that has been learned along the way.
  • Conference: Insights about Artificial Neural Networks

Target & Objectives

  • Target :

    • People 14 years of age or older.

    • Artificial intelligence enthusiasts.

    • People who wish to enter the field of artificial intelligence, and data science.

  • Prerequisite :

    • Familiarity with the basics of mathematics and statistics.

    • Have a sense of logic.

    • Ability to solve simple mathematical problems.

    • Have a simple knowledge of English to understand Python terms.

  • The objectives of this program :

    • To learn the most popular programming language today: Python.

    • Learn data pre-processing and data visualization

    • Learn how to manipulate the Python libraries: Numpy, pandas, matplotlib, seaborn and scikit learn.

    • Explore supervised and unsupervised learning.

    • Understand and use feature selection techniques.

    • Create a predictive analysis model.

    • Create a final project; a full artificial intelligence pipeline, based on everything you have learned along the way.