FR
Illustration: AI course

AI: Evolution, Understanding, Applications, and Programming

This artificial intelligence training course immerses you in the fascinating world of AI, from its origins to its modern applications. You will explore the fundamental concepts, advances in Machine Learning and Deep Learning, as well as their differences and complementary roles.

Special attention will be given to generative AI, its language models, and its practical applications. Through concrete demonstrations and hands-on exercises with Google Gemini, you will learn how to create, automate, and optimize AI models.

Finally, the course will address ethical considerations, bias, and technological challenges, while providing tools to assess the impact of AI across various sectors. This comprehensive learning path will give you the knowledge and skills needed to understand, experiment with, and innovate using AI.

1 day 9:00 a.m. to 4:30 p.m. Online, Montreal, Quebec City

Updated on

The AI course at a glance

Length
1 day
Schedule
9:00 a.m. to 4:30 p.m.
Format
Live virtual class or in person in Montreal and Quebec City
Audience
Tous
Price
$650 per participant, or $552 for public bodies and non-profits (plus taxes)
Language
English

Doussou Formation and AI: key facts

Upcoming AI sessions

Online

AI course outline

Introduction to Artificial Intelligence

  • Overview and Presentation with Q&A (1.5 Hours)
  • Definition and Evolution of AI:
    • Terminology and Evolution
    • From Early Algorithms to Neural Networks
    • Deep Learning and Generative AI
    • Narrow AI, Artificial General Intelligence, and Superintelligence
    • Examples of Applications Across Various Fields
    • Factors Supporting AI:
    • Algorithmic Structures and Heuristics
    • Hardware Components: CPUs, GPUs, and TPUs
    • Programming Languages: R, Python, C++, Rust, and Mojo
    • Software and Frameworks
  • Machine Learning Overview:
    • Main Categories of Models
    • Supervised and Unsupervised Learning
    • Applications and Fields of Use
  • Deep Learning Overview:
    • Differences Between Deep Learning and Machine Learning
    • Concepts and Models
    • Applications and Fields of Use
    • Specific Characteristics of Natural Language Processing
  • Generative AI Overview:
    • Language, Image, and Multimodal Models
    • Applications and Products Available on the Market
    • Example: Google Gemini
  • Issues and Risks:
    • Ethics and Bias
    • Privacy and Environmental Impact
    • Risk of Dystopian Outcomes

Artificial Intelligence Demonstrations

  • Overview and Presentation with Q&A (1.5 Hours)
  • DevOps and AI Pipelines:
    • Data Preprocessing
    • Training and Optimization
    • Deployment
  • Machine Learning in Practice:
    • Demonstration with Scikit-Learn
    • User-Friendly Approach with PyCaret
    • Note: Source Code Provided Through Google Colab
    • Deep Learning in Practice:
    • Demonstration with NumPy
    • Using PyTorch
    • Note: Source Code Provided Through Google Colab
  • Generative AI:
    • Exploring Large Language Models and Multimodal Models
    • Fine-Tuning and Autonomous Agents
    • Note: Practical Work with Google Gemini in the Following Module

Using Google Gemini

  • Hands-On Experimentation with Google Colab (3.5 Hours)
  • Using the Chatbot:
    • Writing Simple Prompts
    • Tips for Python and Other Programming Prompts
  • Using the Python API:
    • Designing Advanced Prompts
    • Code Optimization and Unit Testing
  • Using Google AI Studio:
    • Fine-Tuning and Retrieval-Augmented Generation
    • Building an Autonomous Agent
    • Experimental Projects with Python and Other Languages

Follow-Up Training with OpenAI

Your AI trainer

Scientifique de données

Hugues S.

A data scientist, Hugues explores data collected within organizations and develops analyses and forecasts, or collaborates on projects aimed at extracting value from collected data. His projects include, among others, customer segmentation, map-based data visualization, transaction matching, and subscription lifetime…

View full profile

Prices and practical information

Preferred rate

$552 / participant

Public bodies and non-profits · plus taxes

Standard price

$650 / participant

Businesses and individuals · plus taxes

Practical information

  • Length: 1 day
  • Schedule: 9:00 a.m. to 4:30 p.m.
  • Format: Live virtual class or in person in Montreal and Quebec City
  • Payment: online (PayPal or card) when registering, or by invoice for organizations
View dates and register Quote for my employer

Corporate AI training

Train your whole team as a private group, on your own documents, at your premises or in a virtual class, on the dates that suit you.

Request an offer

Participant reviews

97% satisfaction (end-of-course evaluations, 120 evaluations) · Read all testimonials

Why take this AI course

Objectives: what you will be able to do

  • Understand the evolution and key concepts of artificial intelligence.
  • Explore the fundamentals of Machine Learning and Deep Learning.
  • Discover generative AI and its practical applications.
  • Use Google Gemini to experiment with and automate AI models.
  • Evaluate the ethical considerations and limitations of AI technologies.

Prerequisites

Good knowledge of JavaScript

What is included

  • Course materials and exercise files for each participant
  • Certificate of attendance
  • Optional personalized coaching after the course
  • In public in-person sessions:
    • Tea and coffee
    • Lunch at a nearby restaurant
    • Parking (in some cities)
    • Wi-Fi access

View all courses: Artificial intelligence training

Interested in the AI course?

Quote for my employer Register now