Python ML & AI Bootcamp: 1 Day Practical Workshop in Odense
Dive into ML and AI using Python—master supervised and unsupervised learning, model evaluation, and neural network basics in one day.
Group Discounts:
- Save 10% when registering 3 or more participants
- Save 15% when registering 10 or more participants
About This Course
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 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.
Learning Objectives:
By the end of this course, you will:
- 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
Target Audience:
Data scientists, ML engineers, developers, and advanced Python users.
Why is it right fit for you:
If you’re looking to take your Python programming skills into the realm of machine learning, this course is ideal. With a strong focus on applied learning and best practices, you’ll build models and analyze datasets that mirror real-world challenges. Our experienced instructors make complex concepts like algorithms and neural networks accessible through hands-on examples. This course helps you build confidence in working with machine learning tools and prepares you for advanced AI workflows.
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Good to know
Highlights
- 8 hours
- ages 18+
- In person
- Paid parking
Refund Policy
Location
ODENSE, Dannebrogsgade
Regus office space
Ph No: +1 469 666 9332 5000 Odense
How do you want to get there?
Agenda
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