Training: Artificial Intelligence Fundamentals for Engineers and Technicians
This training course provides a practical introduction to the fundamentals of artificial intelligence, specifically designed for engineers and technicians. It covers the foundations of Machine Learning, including the essential mathematical and algorithmic concepts required to understand it. Through case studies, participants will explore Machine Learning application scenarios and learn how to select the appropriate tools for their technical projects.
The course also explores the main supervised and unsupervised Machine Learning models, as well as the use of PyCaret, a Machine Learning automation tool, with guidance on installation and data integration. A dedicated Deep Learning module introduces neural networks and their applications in engineering contexts.
Finally, engineers and technicians will gain an in-depth understanding of Large Language Models (LLMs) by exploring how they work and how they can be used in various technical projects.
This comprehensive training course enables participants to develop strong technical skills for applying artificial intelligence within their specific fields.
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The Artificial Intelligence Fundamentals for Engineers and Technicians 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 Artificial Intelligence Fundamentals for Engineers and Technicians: key facts
- Since 2016Doussou Formation has been delivering professional training in Quebec
- 300+specialized courses in our catalogue
- 97 %satisfaction according to client evaluations
- RAP · CPMTAccredited supplier and recognized training organization
Upcoming Artificial Intelligence Fundamentals for Engineers and Technicians sessions
Artificial Intelligence Fundamentals for Engineers and Technicians course outline
Foundations for Understanding Artificial Intelligence
- Introduction to Key AI Concepts: Algorithms, ML, DL, and LLMs
- Exploring the Algorithms Used in ML, DL, and LLMs
- The Importance of Machine Learning Before Moving on to Deep Learning and LLMs
Overview of the Main Deep Learning Models
- Introduction to the Key Concepts of Deep Learning and Neural Networks
- Overview of Deep Learning Applications and Limitations
Overview of the Main Large Language Models (LLMs)
- Understanding How LLMs Work and Their Applications
- Exploring the Limitations and Challenges of LLMs
Introduction to Machine Learning
- Fundamental Machine Learning Concepts
- Overview of Algorithms Used in Machine Learning
- Why Machine Learning Is a Key Step Before Deep Learning and LLMs
Machine Learning Models
- Supervised Learning: Theoretical Principles and Application Examples
- Unsupervised Learning: Methods and Use Cases
Using PyCaret for Machine Learning
- Installing and Configuring PyCaret
- Exploring the Models Available in PyCaret
- Working with Datasets for Machine Learning
Follow-Up Training for Developers
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
Corporate Artificial Intelligence Fundamentals for Engineers and Technicians 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.
Participant reviews
97% satisfaction (end-of-course evaluations, 120 evaluations) · Read all testimonials
Why take this Artificial Intelligence Fundamentals for Engineers and Technicians course
Objectives: what you will be able to do
- Understand the fundamental concepts of Machine Learning and their technical applications.
- Master the use of PyCaret to automate Machine Learning processes.
- Explore neural network architectures and their role in Deep Learning.
- Gain practical knowledge of Large Language Models (LLMs) and their applications.
Prerequisites
- Have a solid general understanding of computer science.
- Have a basic knowledge of mathematics, including algebra and probability.
- Understand fundamental statistical concepts.
- Be familiar with development and data analysis tools.
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