Corporate Machine Learning with MATLAB Training Course

Name: Machine Learning with MATLAB Training
Availability: InStock

Edstellar's instructor-led Machine Learning with MATLAB training course offers personalized guidance to professionals for mastering machine learning techniques using MATLAB. This approach fosters professionals skills in data analysis, predictive modeling, and algorithm implementation, enhancing their contribution to the teams.

Duration

16 - 24 hrs

Delivery Type

Instructor-led Group Training
(Virtual / On-site / Off-site)

Training Available in

10 Languages

Multiple Locations

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About Learning Outcomes Key Benefits Course Outline Target Audience Training Modes Certificate Trainers Request a Training Quote

Drive Team Excellence with Machine Learning with MATLAB Corporate Training

Machine Learning with MATLAB refers to applying machine learning algorithms and techniques using MATLAB, a high-performance language and interactive environment for numerical computation, visualization, and programming. Machine Learning with MATLAB benefits organizations, offering advantages that can significantly enhance their operational efficiency, decision-making processes, and innovation capabilities. This training program introduces professionals to the world of machine learning applications within MATLAB.

Edstellar instructor-led Machine Learning with MATLAB course distinguishes itself by offering both virtual/onsite training options, catering to diverse organizational needs and learning preferences. This flexibility ensures that the teams can engage in the training regardless of their location, providing convenience without compromising the quality of training. This course is tailored to meet each organization's unique needs and goals, ensuring that the learning experience is both highly relevant and directly applicable to the professional scenarios of the teams. Through a blend of theoretical concepts and practical exercises, professionals gain hands-on experience, empowering them to apply machine learning techniques effectively within their roles.

Get Customized Expert-led Training for Your Teams

Customized Training Delivery

Scale Your Training: Small to Large Teams

In-person Onsite, Live Virtual or Hybrid Training Modes

Plan from 2000+ Industry-ready Training Programs

Experience Hands-On Learning from Industry Experts

Delivery Capability Across 100+ Countries & 10+ Languages

Skills Your Employees Will Gain

These are the core, hands-on capabilities your team builds during the program.

Predictive Modeling
Predictive Modeling is the process of using statistical techniques to forecast future outcomes based on historical data. This skill is important for data analysts, marketers, and financial analysts, as it enables informed decision-making and strategic planning.
Data Preprocessing
Data Preprocessing is the technique of cleaning and transforming raw data into a usable format. This skill is important for data analysts and scientists to ensure accurate analysis and insights.
Machine Learning Algorithms
Machine Learning Algorithms involve designing systems that learn from data to make predictions. This skill is important for data scientists and AI engineers to develop intelligent solutions.
Clustering Analysis
Clustering Analysis is a data mining technique that groups similar data points. This skill is important for data scientists and analysts to uncover patterns, enhance decision-making, and drive insights.
Model Optimization
Model Optimization is the process of refining machine learning models to enhance performance and efficiency. This skill is important for data scientists and AI engineers, as it ensures accurate predictions and resource-efficient solutions.
Neural Network Design
Neural Network Design involves creating architectures for AI systems that mimic human brain functions. This skill is important for roles in AI development, data science, and machine learning, as it enables effective problem-solving and innovation in complex data analysis.

What Your Team Will Achieve After This Training

Develop predictive models for real-world problems, such as forecasting market trends, enhancing customer segmentation, or improving product recommendations
Implement advanced data preprocessing techniques to clean, normalize, and transform large datasets, ensuring that models are trained on high-quality data for more accurate predictions
Apply various machine learning algorithms, from basic classification and regression techniques to more complex ensemble methods and neural networks, to solve specific industry challenges
Utilize clustering algorithms to uncover hidden patterns and groups in data, enabling businesses to identify new market opportunities or understand customer behavior better
Optimize machine learning models by fine-tuning hyperparameters and selecting relevant features, thereby improving model performance and efficiency in practical applications
Design and evaluate neural network architectures for tasks such as image recognition, natural language processing, or time series forecasting, leveraging MATLAB's deep learning capabilities

Topics & Program Outline

The curriculum is organized into focused modules built by industry experts and delivered virtually or on-premise. Interactive sessions reflect the evolving demands of the workplace, keeping the learning both relevant and practical.

Introduction to Machine Learning with MATLAB

Overview of machine learning
- What is machine learning?
- Categories of machine learning
Getting started with MATLAB for machine learning
- Setting up the environment
- Basic MATLAB operations for machine learning

Importing and Organizing Data

Understanding data types
- Numerical and categorical data
- Dealing with missing values
Working with tables in MATLAB
- Creating and manipulating tables
- Table operations and indexing
Preparing data for machine learning
- Data cleaning
- Data normalization and standardization

Finding Natural Patterns in Data

Introduction to unsupervised learning
- Defining unsupervised learning
- Applications of unsupervised learning
Exploring clustering methods
- K-means clustering
- Hierarchical clustering
- DBSCAN and other clustering techniques
Evaluating and interpreting clusters
- Cluster validation techniques
- Interpreting cluster results

Building Classification Models

Fundamentals of supervised learning
- Defining supervised learning
- Applications of supervised learning
Training and validation in supervised learning
- Splitting data into training and test sets
- Validation techniques
Classification techniques in MATLAB
- Logistic regression
- Decision trees and random forests
- Support vector machines

Improving Predictive Models

Techniques for cross-validation
- K-fold cross-validation
- Leave-one-out cross-validation
Optimizing hyperparameters
- Grid search
- Random search
- Bayesian optimization
Feature engineering and selection
- Feature transformation methods
- Selecting features for model performance
Implementing ensemble learning
- Boosting
- Bagging
- Stacking

Building Regression Models

Parametric vs. nonparametric regression
- Linear regression
- Polynomial regression
- K-nearest neighbors and decision trees
Evaluating regression models
- Mean squared error and mean absolute error
- R-squared and adjusted R-squared

Creating Neural Networks

Clustering with Self-Organizing Maps (SOM)
- Introduction to SOM
- Applications of SOM in clustering
Classification with feed-forward neural networks
- Designing a feed-forward neural network
- Training and validating neural network models
Regression with feed-forward networks
- Neural networks for regression tasks
- Evaluating regression models with neural networks

Who Should Attend?

This program suits professionals at many levels across the organization, including:

Data Scientists
Machine Learning Engineers
MATLAB Developers
Software Engineers
Research Scientists
IT Professionals
Data Analysts
AI Specialists
Systems Engineers
Technical Leads
ML Managers
Data Science Managers

What are the Prerequisites?

Professionals should have a basic understanding of fundamental concepts of programming languages like Python, C++, or Java and algorithms and data analysis techniques to take the Machine Learning with MATLAB training course.

Request a Quote for your Corporate Training Requirements

Delivering Training for Organizations across 100 Countries and 10+ Languages

Choose the Format That Fits Your Team

We design training your teams actually engage with, and deliver it the way that suits you best. Through a vetted global trainer network, Edstellar runs sessions in 10+ languages with consistent quality anywhere.

Virtual Machine Learning with MATLAB Training

Virtual / online: expert-led live sessions delivered anywhere, with consistency and easy scheduling.

We deliver anywhere worldwide

Standardized content for consistent outcomes

Join from own workspace, no travel

We scale to large groups across sites

Interactive tools keep remote learners engaged

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On-site Machine Learning with MATLAB Training

On-site (in-house): immersive, instructor-led learning at your office.

Our trainers run face-to-face at your office

We tailor setup/content to your workplace and tools

Group exercises drive collaboration

Live demos + hands-on practice

Direct trainer access to clarify doubts

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Off-site Machine Learning with MATLAB Training

Off-site: focused, instructor-led group learning away from everyday workplace distractions.

We host your teams at a venue of your preferred choice

Built-in group activities for bonding

Full uninterrupted schedule for focus/retention

Boosts morale and signals commitment

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What Sets Edstellar Apart

Experienced Trainers

Our trainers are drawn from a vetted global network and bring years of industry expertise, keeping every session practical and impactful.

Proven Quality

With a strong global track record, Edstellar is known for quality and engaging delivery.

Industry-Relevant Curriculum

Our programs are built by experts to match the demands of today's industry.

Fully Customizable

Every program can be tailored to your organization's goals.

Comprehensive Support

We provide pre- and post-session support for a complete learning experience.

Global Multi-Location & Multilingual Training Delivery

We deliver in multiple languages to support diverse global teams.

Hear from Organizations We've Trained

"The Machine Learning with MATLAB training provided me with comprehensive capabilities that elevated my expertise. As a Senior Business Intelligence Developer, I needed to understand strategic frameworks deeply, and this expert-led workshops gave me hands-on experience with industry best practices. I now handle complex technical scenarios with enhanced confidence and systematic efficiency. Highly recommend for anyone serious about this field.”

Jerry Porter

Senior Business Intelligence Developer,

Predictive Analytics Firm

"The Machine Learning with MATLAB training provided critical insights into industry best practices that enhanced my consulting capabilities. As a Principal Data Architect, I now leverage hands-on exercises with expertise exercises on interactive labs prepared me perfectly for real-world client scenarios. Our solution delivery efficiency and quality have increased substantially across the board, demonstrating immediate value from this investment.”

Alessio Ferrari

Principal Data Architect,

AI Solutions Platform Provider

"As a Lead MLOps Engineer overseeing technical mastery initiatives, the Machine Learning with MATLAB training significantly elevated our team's capabilities. The course expertly covered advanced methodologies, operational effectiveness. Our team delivered record-breaking results in the subsequent quarter, exceeding all targets. Our department has achieved remarkable improvements, demonstrating this course's lasting organizational impact.”

Ilyas Samir

Lead MLOps Engineer,

ML Model Development Platform

“Edstellar’s IT & Technical training programs have been instrumental in strengthening our engineering teams and building future-ready capabilities. The hands-on approach, practical cloud scenarios, and expert guidance helped our teams improve technical depth, problem-solving skills, and execution across multiple projects. We’re excited to extend more of these impactful programs to other business units.”

Aditi Rao

L&D Head,

A Global Technology Company

Recognition That Motivates Your Team

Upon successful completion of the training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

Corporate Machine Learning with MATLAB Training Course

Drive Team Excellence with Machine Learning with MATLAB Corporate Training

Skills Your Employees Will Gain

What Your Team Will Achieve After This Training

Topics & Program Outline

Introduction to Machine Learning with MATLAB

Importing and Organizing Data

Finding Natural Patterns in Data

Building Classification Models

Improving Predictive Models

Building Regression Models

Creating Neural Networks

Who Should Attend?

What are the Prerequisites?

Choose the Format That Fits Your Team

Get a Proposal Shaped to Your Needs

What Sets Edstellar Apart

Experienced Trainers

Proven Quality

Industry-Relevant Curriculum

Fully Customizable

Comprehensive Support

Global Multi-Location & Multilingual Training Delivery

Hear from Organizations We've Trained

Recognition That Motivates Your Team

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