Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Pattern Recognition And Application certification course explores Signal Processing, Probability, and Graph Theory. Covering pattern recognition, including statistical, nonparametric, and neural network techniques, the course explores applications in machine vision and speech recognition. With an emphasis on analytical aspects, it equips students to apply concepts to real-world challenges upon completion.
Open to any interested learners, the Pattern Recognition And Application certification by Swayam covering Electrical, Electronics, and Communications Engineering explores feature extraction, pattern representation, and time-varying pattern recognition. With practical examples from machine vision and speech recognition, it delves into unsupervised classification techniques.
Also Read: Online Artificial Intelligence And Machine Learning Certification Courses
The Highlights
- Elective Online Course
- 12 Weeks Duration
- Offered by IIT Kharagpur
Programme Offerings
- Certificate of completion
- Practical Learning
- Hands-on Experience
Courses and Certificate Fees
| Fees Informations | Certificate Availability | Certificate Providing Authority |
|---|---|---|
| INR 1000 | yes | IIT Kharagpur |
The Pattern Recognition And Application certification fees is free. However, if you want a certificate, you must register and take the proctored exam at designated centers, which is optional and comes with a fee of Rs 1000.
Pattern Recognition And Application Certification Fee Structure
Particulars | Total Fees |
Pattern Recognition And Application (exam) | Rs 1000/- |
Eligibility Criteria
Certification Qualifying Details
To receive the Pattern Recognition And Application certification by Swayam, you need a minimum average assignment score of 10/25 and an exam score of 30/75.
What you will learn
After completing the Pattern Recognition And Application certification syllabus, you will delve into the intricate world of pattern recognition, honing your understanding of feature extraction techniques and how to represent patterns in feature space effectively.
Upon completion of the Pattern Recognition And Application training, you will explore a comprehensive range of pattern recognition techniques, including statistical, nonparametric, and neural network approaches. You will also gain foundational knowledge of Signal Processing, Probability Theory, and Graph Theory.
Who it is for
The Pattern Recognition And Application online course is suitable for individuals seeking a comprehensive understanding of pattern recognition. This course is particularly beneficial for:
Admission Details
Follow these steps to join the Pattern Recognition And Application classes:
Step 1: Browse the URL below:
https://onlinecourses.nptel.ac.in/noc23_ee119/preview
Step 2: Click on the “Sign-in/ Register” button
Step 3: Fill out the necessary details and submit the form
The Syllabus
- Introduction
- Feature Extraction - I
- Feature Extraction - II
- Bayes Decision Theory - I
- Bayes Decision Theory - II
- Normal Density and Discriminant Function - I
- Normal Density and Discriminant Function - II
- Bayes Decision Theory - Binary Features
- Maximum Likelihood Estimation
- Probability Density Estimation - I
- Probability Density Estimation - II
- Probability Density Estimation - III
- Probability Density Estimation - IV
- Dimensionality Problem
- Multiple Discriminant Analysis
- Principal Component Analysis - Tutorial
- Multiple Discriminant Analysis - Tutorial
- Perceptron Criteria - I
- Perceptron Criteria - II
- MSE Criteria
- Linear Discriminator Tutorial
- Neural Network - I
- Neural Network - II
- Neural Network -III/ Hopefield Network
- RBF Neural Network - I
- RBF Neural Network - II
- Support Vector Machine
- Clustering -I
- Clustering -II
- Clustering -III
Evaluation process
The Pattern Recognition And Application certification offers an optional exam. Your final score is determined by averaging the best 8 out of 12 assignments (25%) and your proctored exam score (75%).
Instructors
IIT Kharagpur Frequently Asked Questions (FAQ's)
A basic understanding of Signal Processing, Probability Theory, and Graph Theory is assumed. It is designed for final-year undergraduate students in Electrical Sciences, but anyone with an interest can enroll.
The course spans 12 weeks, with an expected commitment of several hours per week. It is structured to accommodate both final-year undergraduates and postgraduates.
Yes. The course is open to any interested learners, making it suitable for individuals from diverse backgrounds who want to gain insights into pattern recognition and its applications.
Practical applications are a key focus. The course includes examples from machine vision, speech recognition, and movement recognition, ensuring that the concepts learned can be directly applied to real-world scenarios.
You will develop a comprehensive skill set, including proficiency in feature extraction, pattern representation, and various pattern recognition techniques.