This five-day course enables participants to discover and deepen their use of Artificial Intelligence in Data Science. It combines theory and practice to learn how to design, train, and deploy AI models adapted to business needs through hands-on workshops.
Objectives
The objective of this course is to enable participants to understand the fundamentals of AI, work effectively with data, and develop Machine Learning and Deep Learning models to address real-world problems.
Is it for you ?
Data scientists, data analysts, developers wishing to specialize in AI, software engineers, technical architects, and data-oriented technical project managers.
Prerequisite
Basic knowledge of Python, concepts in statistics and linear algebra, as well as familiarity with data science concepts.
Your benefits
Content
Chapter 1: Fundamental concepts
- Definition of AI, Machine Learning, Deep Learning.
- Applications in Data Science.
Chapter 2: Ecosystem and tools
- Python for AI.
- Key libraries: NumPy, Pandas, Matplotlib.
- Practical workshop:
- Exploration and visualization of a dataset.
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Chapter 3: Data collection and cleaning
- Handling missing data.
- Normalization and encoding.
Chapter 4: Feature Engineering
- Variable selection and transformation.
- Practical workshop:
- Preparing a dataset for a predictive model.
Chapter 5: Supervised learning
- Linear and logistic regression.
- Decision trees and Random Forest.
Chapter 6: Unsupervised learning
- Clustering (K‑means).
- Dimensionality reduction (PCA).
- Practical workshop:
- Implementation of an ML model with Scikit‑learn.
Chapter 7: Foundations of Deep Learning
- Neural network architecture.
- Activation functions and backpropagation.
Chapter 8: Advanced frameworks
- TensorFlow vs PyTorch.
- Creation of a simple network.
- Practical workshop:
- Development of an image classification model.
Chapter 9: Evaluation and optimization
- Performance metrics.
- Hyperparameters and tuning.
Chapter 10: Deploying an AI project
- Integration into a real‑world environment.
- Deployment tools (Flask, FastAPI).
- Practical workshop:
- Deployment of an AI model via an API.
💡 Useful information
Our training sessions are offered in Montreal or Quebec City, in person or in virtual format. Dates and locations are provided when you select your session below. If you have any questions regarding registration, schedules, the language of instruction, or cancellation policies, please consult our FAQ .
Trainers
Private or personalized training
Do you have several employees interested in the same training course? Whether in person at your offices or remotely in virtual mode, we offer private training courses tailored to your team's needs. Group rates are available. Contact us for more details or request a quote online.
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