Optimization through MATLAB

Introduction

Optimization is at the heart of engineering, artificial intelligence, and scientific research, enabling smarter decisions and efficient solutions to complex problems. This course, "Optimization Techniques using MATLAB," provides a hands-on approach to mastering key optimization algorithms—Genetic Algorithm (GA), Gradient Descent (GD), and Particle Swarm Optimization (PSO)—using MATLAB’s powerful computational environment.

Whether you're a university student or an aspiring optimization specialist, this course will equip you with the skills to formulate, implement, and analyze optimization models for real-world challenges. From minimizing cost functions to tuning AI models, you’ll gain practical experience through coding exercises, case studies, and mini-projects.

Objectives

Understand the fundamentals of optimization problems.
Implement Genetic Algorithm (GA), Gradient Descent (GD), Particle Swarm Optimization (PSO in MATLAB.
Solve real-world engineering and web application problems using MATLAB-based optimization.
Model fitness/objective functions from actual case studies.
Compare algorithm performance with plots and statistical analysis.
Export optimized parameters to other environments.

Career Path

MATLAB Developer
Optimization Specialist
Control Systems Assistant
AI/ML Assistant (Optimization Models)
Research Assistant in Engineering/Math Fields
Freelance Optimization Expert

Fee Structure Optimization through MATLAB

Optimization through MATLAB
Duration	8 Weeks
Total Semester	1
Total Package	10,000
At Admission Time	10,000
Additional Charges at the time of Admission	0
Examination Fee	0
Total Amount (At Admission)	10,000
Installment	0 * 2

Additional Charges at the time of Admission
Web Portal fee per year for Learning Management Syste	0
Library Security Fee (Refundable)	0
Student Card	0
Library & Magazine Fund	0
Total Additional Charges	0