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Machine Learning using MATLAB

Accelerate your Career

Learn machine learning algorithms with MATLAB. Explore regression, classification, clustering, and deployment for real-world AI applications.

5 Modules
with Certifications
4:50 Hours
of Recorded Content
5.0 Ratings
by 610 Learners
English
Language
Paid Course
Get this Course @ ₹799
610 enrolled in this course
About Curriculum Key Features Certificate Testimony FAQs

Machine Learning using MATLAB

Machine Learning using MATLAB is an explorer-level course designed to introduce learners to the practical implementation of machine learning algorithms using one of the most widely used engineering and research platforms. The curriculum covers regression models, classification techniques, clustering algorithms, dimensionality reduction, and ensemble learning methods through guided examples and project-based exercises. Participants will gain hands-on experience with supervised and unsupervised learning techniques while developing analytical skills applicable to engineering, scientific computing, and AI research domains
MASTERING THE DATA SCIENCE LIFECYCLE

Comprehensive Syllabus Outline

A comprehensive curriculum designed to take you from beginner to professional.

M1

Module 1 — Supervised Machine Learning using MATLAB

Predictive Modeling using Linear Regression in MATLAB
Classification using Logistic Regression Models

M2

Module 2 — Classification Algorithms and Pattern Recognition

Decision Tree-Based Classification and Decision Making
Object Classification using Support Vector Machines (SVM)
Probabilistic Classification using Naïve Bayes Algorithms
Predictions using Naïve Bayes
Find out nearest neighbour using kNN

M3

Module 3 — Clustering and Feature Reduction Techniques

Data Clustering using K-Means Algorithms
Dimensionality Reduction for High-Dimensional Datasets

M4

Module 4 — Ensemble Learning and Advanced Prediction Models

No items available.

M5

Module 5 — Classification and Pattern Analysis Projects

DNA Fragment Classification and Pattern Recognition Project

Capstone Project

DNA Fragmentation Pattern Classification

Develop a machine learning solution capable of analyzing and classifying DNA fragmentation patterns using supervised learning techniques within MATLAB.

A complete preprocessed dataset of genomic fragmentation profiles.
PROJECT

A complete preprocessed dataset of genomic fragmentation profiles.

Access hands-on simulation modules to master production level engineering challenges.

An optimized Support Vector Machine (SVM) and Random Forest classifier script in MATLAB.
PROJECT

An optimized Support Vector Machine (SVM) and Random Forest classifier script in MATLAB.

Access hands-on simulation modules to master production level engineering challenges.

A feature extraction pipeline utilizing dimensionality reduction techniques.
PROJECT

A feature extraction pipeline utilizing dimensionality reduction techniques.

Access hands-on simulation modules to master production level engineering challenges.

Performance evaluation matrices including Confusion Matrices, ROC curves, and AUC metrics.
PROJECT

Performance evaluation matrices including Confusion Matrices, ROC curves, and AUC metrics.

Access hands-on simulation modules to master production level engineering challenges.

CORE TOOLING MASTERY

Tech Stack

Master the primary professional software development packages and workflow tools.

MATLAB
MATLAB Machine Learning Toolbox
Statistics and Machine Learning Toolbox
Decision Trees
Support Vector Machines (SVM)
k-Nearest Neighbours (kNN)
K-Means Clustering
Random Forest
XGBoost
Boosting Algorithms
Career Impact

After this Course, You will be Able to

Observe the real-world utility outcomes you gain after program completion.

Build regression models for predictive analytics using MATLAB.
Develop classification systems using Logistic Regression, Decision Trees, SVM, Naïve Bayes, and kNN algorithms.
Implement clustering and dimensionality reduction techniques for data exploration and analysis.
Apply ensemble learning methods including Random Forest and Boosting algorithms for improved prediction accuracy.
Analyze engineering and scientific datasets using MATLAB's machine learning ecosystem.
Develop practical machine learning projects and strengthen your portfolio for AI, research, and data science applications.

Course Stats

₹12.35 LPA

Average Salary

₹42 LPA

Highest Salary

135%

Salary Hike

7+ Companies

Hiring Partners

Key Features

Mentorship

Receive guidance and insights from industry experts

Hands-on Experience

Gain practical skills in a real-world cutting-edge projects.

Networking

Connect with professionals and peers in your field

Skill Development

Enhance your technical and soft skills

Career Advancement

Boost your resume with valuable experience

Dual Certificate

Get a certification to showcase your achievements
DIGITAL VERIFIABLE CREDENTIAL

Let Your Certificates Speak For You

Our certification formally validates your skill set in recruiter searches with unique QR code verification and LinkedIn-ready structures.

Unique Credential ID & QR Code
Recruiters can scan to instantly verify your project files, source repository, and official completion marks.

Linkedin Certified Recognition
Easily push to your Linkedin profile with 1-click credential linking to increase high-end corporate recruiter views.

Certificate Sample
Status
Verified

Where Our Learners Work

Our alumni are driving innovation at the world's most prestigious technology companies.

Flipkart
Freshworks
Juspay
Chargebee
Zoho
PayPal
PREMIER PLATFORM EXPERIENCE

Why Pantech?

An expert-crafted learning infrastructure built for technical fluency.

Industrial Expert Mentors

Direct guidance and weekly doubt clearing sessions hosted by hardware, embedded, and software engineering veterans.

24/7 Interactive Support

Ask coding doubts anytime on our student community workspace and receive instant assistance.

Self-Paced Learning Engine

Access lifetime recorded modules with adaptive pacing to balance academics and professional work.

Career Guidance Support

Exclusive resume review, mock interviews, and placement assistance from industry experts.

We are Accredited by

Our Awards & Achievements
Award 1
VERIFIED STUDENT REVIEWS

What Our Students Say

See how Pantech courses accelerated career transitions across India.

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VERIFIED LEARNER

Get exclusive lifetime access to coursework, simulators, custom templates, and direct placement opportunities.

Need immediate counseling?

+91 8925533488/89

HAVE QUESTIONS?

Frequently Asked Questions

Find instant answers to all common questions about our technical certificate courses.

1. Do I need prior experience?

No prior experience is required for foundational modules. Advanced topics may recommend basic knowledge in programming or electronics.

2. What if I face technical issues?

You can reach our support team at training@pantechelearning.com or call +91 89255 334 88 / 89.

3. What will I learn in this course?

You’ll cover: MATLAB basics for machine learning Regression techniques for prediction Classification algorithms for decision-making Clustering methods for pattern recognition Model deployment for real-world AI applications

4. How long is the course?

The program includes 5 structured modules, designed to be completed at your own pace, typically within 4–6 weeks.

5. Will I get a certificate?

Yes, upon completion you’ll receive a verified certification from Pantech eLearning, which can be shared on LinkedIn and with employers.

6. What is the course fee?

The Machine Learning Algorithms using MATLAB course is available for ₹1,499, inclusive of all modules and certification.

7. Is there any project work included?

Yes, you’ll apply your skills in a guided ML project, such as building regression or classification models, to reinforce concepts and demonstrate practical learning outcomes.

8. Can I access the course materials anytime?

Absolutely. Once enrolled, you’ll have lifetime access to the course videos, notes, and resources

9.Does the course include practical projects?

Yes. Learners complete a hands-on DNA Fragmentation Pattern Classification project that applies multiple machine learning concepts in a real-world scenario.

10.Will this course help prepare for advanced AI and data science learning?

Yes. It establishes a strong foundation in machine learning algorithms and predictive modeling, providing a solid pathway toward advanced AI, deep learning, and research-oriented applications.

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