Machine Learning & AI in Python
The Machine Learning & AI in Python course empowers you to understand, build, and evaluate predictive models using Python. You will learn the fundamentals of supervised and unsupervised learning, model evaluation metrics, feature engineering, and get a glimpse into neural networks and deep learning. With practical hands-on exercises, this course prepares you to transition from theory to real-world machine learning applications.
Boston, Massachusetts, USA
March 23, 2026
Classroom Session
1 Day
About this course
The Machine Learning & AI in Python course empowers you to understand, build, and evaluate predictive models using Python. You will learn the fundamentals of supervised and unsupervised learning, model evaluation metrics, feature engineering, and get a glimpse into neural networks and deep learning. With practical hands-on exercises, this course prepares you to transition from theory to real-world machine learning applications.
What you'll learn
- Understand core machine learning concepts and workflows
- Build supervised and unsupervised models using scikit-learn
- Evaluate model performance using appropriate metrics
- Apply feature engineering techniques to improve predictions
- Gain basic knowledge of neural networks and deep learning
- Use Python for real-world AI and ML problem-solving
Course Contents
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
Who Should Attend
- Data scientists
- ML engineers
- Developers
- Advanced Python users
Prerequisites
None
Course Materials
Participants will receive ML frameworks, code samples, and project templates.
Course Price
Need Help?
USA/Canada:
+1 469 666 9332
Australia:
+61 (0) 2 28015 5605
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