Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB
Develop your optimization skills by enrolling for the Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course by NIT Patna.
Online
12 Days
1,000 INR Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English |
Course Overview
The Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course is being offered by the Electronics and ICT academy at National Institute of Technology Patna. It has been set up under the scheme of Department of electronics and information technology. It is a Joint Online Faculty Development Programme.
National Institute of Technology Patna, provides an opportunity of educational training, development and research in science, humanities and engineering technology along with education at UG, PG and PhD level. This course has been designed to provide the learners with an understanding of the various concepts of optimization.
They will learn the fundamentals of optimization and the various methods used for optimization such as the graphical method, the simple method, Multi-modal function Optimization, Multi objective Particle Swarm Optimization, Hybridization of optimization techniques with Neural Networks and Deep Neural Networks and Benchmark mathematical function optimization.
This course is beneficial for the students who wish to gain knowledge about optimization techniques and advance their career in this field of industry.
The Highlights
- Online learning
- Lectures by IIT experts
- Course certificate
- Alumni status of NIT Patna
Programme Offerings
- Online live web conferencing
- assignments
- Case Studies
Courses and Certificate Fees
| Certificate Availability |
|---|
| no |
For the Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course candidates have to pay:
- Faculties or PHD Scholars have to pay a fee of Rs. 500 (general quota) and Rs. 250 (SC/ST quota).
- Other candidates apart from the above need to pay Rs. 1000 (general quota) and Rs. 500 (SC/ST).
Fee details for Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course
Particulars | Amount ( General ) | ( SC/ST ) |
Faculty/ PhD Scholar | Rs. 500/- | Rs. 250/- |
Others (Except Faculty/PhD-Scholar) | Rs. 1,000/- | Rs. 500/- |
Eligibility Criteria
Certification Qualifying Details
Participants will be given a course certificate for the Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course upon successful completion of the assignments and exams given as a part of the course and payment of the certification fees.
What you will learn
After the course nears its completion Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course by NIT Patna participants will have knowledge about the following:
- Understand the basic principles of optimization
- Acknowledge the evolutionary computation of optimization
- Learn the different methods used for the optimization
- Understand the system of Linear and Nonlinear Identification
- Learn the genomic signal processing
Who it is for
Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course can be pursued by:
- The faculty/students having engineering or technical background.
- Faculty/students who wish to gain knowledge or develop their skills can also take this course.
Application Details
To register for the Advanced Optimization Techniques and Hands-on with MATLAB/SCILAB course candidates are required to follow the given steps:
Step1: Candidates can click on the URL to visit the official website of the course http://www.nitp.ac.in/ict/handsonmatlab.php
Step2: Candidates have to click on apply online option given on the right side.
Step3: As this course is currently not open for registration, the candidates can contact the institute officials and enquire regarding the registration details.
The Syllabus
- Unconstrained and constrained optimization
- Linear programming
- Newton’s method
- Graphical method
- Simplex method
- Derivative based optimization
- Symmetric dual problems
- Least mean square method
- Benchmark mathematical function optimization
- Dynamic system identification
- Device modeling
- Hybridization of optimization techniques with neural networks and deep neural networks
- Forecasting/prediction of time series
- Data classification and clustering
- Genomic signal processing
- Communication channel equalization
- Linear and nonlinear system identification
- Multi-modal function optimization
- Bio-inspired optimization (artificial immune system, bacterial foraging optimization)
- Physical algorithms (simulated annealing, colliding bodies optimization, gravitational search optimization)
- Evolutionary computation (genetic algorithm, genetic programming, differential evolution, social spider optimization)
- Swarm intelligence (particle swarm optimization, ant colony optimization, cat swarm optimization, cuckoo-search, grey wolf optimization, whale optimization)
- Non-dominated solutions
- Many-objective optimization
- Nsga-iii.
- Multi objective particle swarm optimization
- Non-dominated sorting genetic algorithm (nsga-ii)
Instructors
Articles
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