Python for Machine Learning & AI: 1-Day Session | Charlotte, NC
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 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 the 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.
©2026 Mangates Tech Solutions Pvt Ltd. This content is protected by copyright law. Copy or Reproduction without permission is prohibited.
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 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 the 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.
©2026 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 orders@mangates.com
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: corporate@mangates.com
Good to know
Highlights
- ages 18+
- In person
Refund Policy
Location
HQ Charlotte City Center
525 North Tryon Street Suite 1600
Ph No +1 469 666 9332 Charlotte, NC 28202
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