Python ML & AI Essentials – 1 Day Workshop in Toronto
Overview
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Duration: 1 Full Day (8 Hours)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs/Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, Snacks and beverages will be provided during the session
Course Overview:
The Machine Learning & AI in Python course provides you with the practical skills needed to understand, build, and evaluate predictive models using Python. You will explore essential concepts in supervised and unsupervised learning, model evaluation methods, and feature engineering, along with an introduction to neural networks and deep learning. Through hands-on exercises and real-world examples, the course bridges the gap between theory and application, enabling you to confidently apply Python-based machine learning techniques in practical scenarios.
Learning Objectives
By the end of this course, you will be able to:
- Understand core machine learning concepts and complete end-to-end workflows
- Build and train supervised and unsupervised models using Python and scikit-learn
- Evaluate and interpret model performance using appropriate metrics
- Apply feature engineering techniques to enhance model accuracy
- Gain foundational knowledge of neural networks and deep learning concepts
- Use Python to solve real-world AI and machine learning problems
Target Audience
This course is ideal for data scientists, machine learning engineers, developers, and advanced Python users looking to expand into AI and ML.
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Looking to enhance your team's AI and machine learning capabilities?
If you are looking to advance your Python skills into machine learning and AI, this course offers a strong and practical foundation. With a focus on applied learning and industry best practices, you will work with realistic datasets and scenarios that reflect real-world challenges. Our expert instructors simplify complex topics such as algorithms and neural networks through hands-on demonstrations, helping you build confidence in using machine learning tools and preparing you for advanced AI workflows.
Contact us today to schedule a customized in-house, face-to-face session: eventbrite@mgaussie.com
Good to know
Highlights
- 8 hours
- ages 18+
- In person
- Paid parking
Refund Policy
Location
Regus - ON, Toronto - Yonge & Shuter
229 Yonge Street Suite 400
Ph No +1 469 666 9332 Toronto, ON M5B 1N8 Canada
How do you want to get there?
Module 1: Introduction to Machine Learning & AI
• What is machine learning and AI? • Role of Python in ML and AI • Overview of ML workflow • Activity
Module 2: Supervised Learning
• Regression vs classification • Building basic linear and logistic models • Using scikit-learn for model implementation • Activity
Module 3: Unsupervised Learning
• Clustering basics • K-means and hierarchical clustering • Use cases for dimensionality reduction (PCA) • Case Study
Frequently asked questions
Organized by
MG Aussie
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