Python ML & AI Bootcamp: 1 Day Practical Workshop in Chicago, IL

Fri, 05 Dec, 2025 at 09:00 am to Fri, 12 Jun, 2026 at 05:00 pm UTC-06:00

regus IL, Chicago - 111 W. Jackson | Chicago

Mangates
Publisher/HostMangates
Python ML & AI Bootcamp: 1 Day Practical Workshop in Chicago, IL
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Dive into ML and AI using Python—master supervised and unsupervised learning, model evaluation, and neural network basics in one day.
About this Event

Group Discounts:

Save 10% when registering 3 or more participants
Save 15% when registering 10 or more participants


About the 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.

©2025 Mangates Tech Solutions Pvt Ltd. This content is protected by copyright law. Copy or Reproduction without permission is prohibited.



Our Royalty Referral Program

Know a team or professional who could benefit from our workshops? Refer them and earn attractive royalties for every successful registration.

For royalty-related queries, contact [email protected]


Looking to enhance your team's AI and machine learning capabilities?

We offer tailored in-house training sessions designed to fit your organization’s specific learning needs. Want your developers to build predictive models or enrich your team’s data expertise? Let us customize a course that aligns with your business goals and projects.

📧 Contact us today to schedule a customized in-house session:


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Agenda
Module 1: Introduction to Machine Learning & AI

Info:
• What is machine learning and AI?
• Role of Python in ML and AI
• Overview of ML workflow
• Activity


Module 2: Supervised Learning

Info:
• Regression vs classification
• Building basic linear and logistic models
• Using scikit-learn for model implementation
• Activity


Module 3: Unsupervised Learning

Info:
• Clustering basics
• K-means and hierarchical clustering
• Use cases for dimensionality reduction (PCA)
• Case Study


Module 4: Model Training and Evaluation

Info:
• Splitting datasets: train-test-validation
• Accuracy, precision, recall, F1-score, confusion matrix
• Cross-validation and tuning
• Activity


Module 5: Feature Engineering Essentials

Info:
• Handling missing data and outliers
• Feature scaling and encoding
• Feature selection techniques
• Activity


Module 6: Introduction to Neural Networks

Info:
• Understanding neurons and layers
• Basics of perceptrons and activation functions
• Overview of backpropagation
• Activity


Module 7: Deep Learning Concepts Overview

Info:
• Understanding deep networks
• Brief intro to TensorFlow and Keras
• Practical examples in image and text processing
• Case Study


Module 8: Mini Project

Info:
• Build a simple predictive model end-to-end
• Train, test, evaluate, and optimize
• Present insights and findings
• Activity


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Event Venue & Nearby Stays

regus IL, Chicago - 111 W. Jackson, 111 W. Jackson Suite 1700, Chicago, United States

Tickets

USD 560.73 to USD 726.65

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