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Applying CV for Autonomous Vehicles using Python in Mumbai

This 3 month program from Skill-Lync teaches the student everything there is to know about computer vision. MATLAB will be used as a tool.

12 weeks long course | 100% Online

Learn from leading experts in the industry

Project based learning with 2 industry level projects that learners can showcase on LinkedIn.

Learn Key Tools & Technologies MATLAB, Python, TensorFlow, OpenCV, Keras TensorFlow 2

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Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

  • The program is designed to provide an introductory /Intermediate level explanation of the various concepts in Computer Vision
  • The course is essentially for a sequential approach towards learning computer vision.
  • The course covers the basics of computer vision, understanding the perception of an image/Image sequence (video), working of a camera and applications of computer vision in Industry.
  • The course provides hands-on experience with coding challenges and projects that are relevant in the autonomous vehicle industry.
  • This course is designed to provide an overview and a platform for students to learn the concepts of computer vision and work on collaborative projects.

Course Syllabus in Mumbai

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week - 01 Introduction to Computer Vision

  • In this session, we will learn about
    • Introduction to Autonomous Vehicles
    • Introduction to Computer Vision
    • Applications of Computer Vision
    • Course Content - Introduction 
    • Understanding Images 

Week - 02 Image Processing Techniques – I

  • In this session, we will learn about
    • Image Filters 
    • Correlation 
    • Convolution
    • Noise in Images
    • Types of Noise
    • Filters for Noise
    • Image Gradients 
    • Edge Detection Techniques

Week - 03 Image Processing using Edge and Line Detection

  • In this session, we will learn about:
    • Canny Edge Detector 
    • Hough Transformation - Lines
    • Hough Transformation - Circles 
    • Domain Transformation 
    • Understanding Frequency Domain 
    • Spatial to Frequency Domain transformations

Week - 04 Projective and Stereo Geometry

  • In this session, we will learn about
    • Image coordinate systems 
    • Projective Geometry
    • Perspective Projections
    • Multiview Geometry 
    • Stereography and Depth Imaging 
    • Stereo Correspondence

Week - 05 3D Computer Vision

  • In this session, we will learn about:
    • Projective Geometry for 3D
    • Camera calibration methods 
    • Epipolar Geometry
    • Stereovision

Week - 06 Feature Extraction , Neural Networks and Image Classification

  • In this session, we will learn about:
    • Image Classification
    • Dimensionality Reduction
    • Principal Component Analysis
    • Convolutional Neural Networks 
    • Datasets
    • Mobile Net Architecture
    • Image Classification - Performance Metrics

Week - 07 Feature Detectors and Descriptors

  • In this session, we will learn about:
    • Feature Detectors
      • Moravec’s Detector
      • Harris Corner Detector
    • Feature Descriptors
      • SIFT 
      • ORB
    • Feature matching methods

Week - 08 Optical Flow

  • In this session, we will learn about:
    • Optical Flow
    • Horn-Shunck method
    • Lucas Kanade sparse optical flow 
    • Gunnar-Farneback Optical flow 
    • Deep learning based optical flow models 

Week - 09 Object Tracking

  • In this session, we will learn about:
    • Introduction to Object Tracking 
    • Deep SORT
    • Lucas-Kanade-Tomasi(KLT) Tracker 
    • Minimum Of Sum Squared Error (MOSSE) Tracker
    • Mean Shift Tracker  

Week - 10 Image Segmentation

  • In this session, we will learn about:
    • Introduction to Image Segmentation
    • Methods of Segmentation
    • Applications of Segmentation
    • Thresholding based segmentation
    • Otsu’s Thresholding
    • Morphological Operations
    • Connected Components
    • Datasets for image segmentation
    • Deep learning architectures for image segmentation

Week - 11 Object Detection

  • In this session, we will learn about:
    • Introduction to Object Detection
    • Region Proposals
    • Graph cut segmentation
    • Selective search
    • Object Detection Datasets
    • Object Detection Models
    • Tensorflow model zoo
    • Evaluation metrics for object detection models 

Week - 12 3D Object Detection

  • In this session, we will learn about:
    • Introduction to 3D Object Detection
    • Types of 3D Object Detection
    • Stereo Image based Detection
    • Monocular 3D Object Detection

Our courses have been designed by industry experts to help students achieve their dream careers

Industry Projects in Mumbai

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Implementation of an image classification model using MobileNet architecture

Image Classification is a very important task in deep learning employed in vast areas and has a very high usability and scope. Student will have to understand and implement an image classification model using MobileNet architecture. Also, students should classify the same image with the provided custom dataset

2D Object Detection with tensorFlow

The TensorFlow Object Detection API is an open source framework built on top of TensorFlow that makes it easy to construct, train and deploy object detection models. Student will have to perform 2D Object detection with tensorFlow object detection API. Student will have to submit report on the performance of the model

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.6

Upskill In Autonomous Vehicles By Enrolling Applying CV For Autonomous Vehicles In Mumbai

Automated driving is a rapidly evolving concept that is likely to transform how the automotive industry works. With the rising number of self-driving vehicles backed by big technology companies, the need for qualified professionals is also rising.

This python course in Mumbai about how to apply CV for Autonomous Vehicles is a step-by-step guide to understanding the process of building an autonomous vehicle. This course will offer in-depth insight into how Computer Vision works and its applications in different industries and situations. The python courses are specifically designed to offer an introductory/intermediate level explanation of the various concepts in Computer Vision.

The certification program is divided into four different modules with various projects available in each and is one of the best ways to learn python. This 3 months autonomous vehicle course in Mumbai allows you to learn python online and covers a range of concepts, including computer vision, understanding the perception of an image/Image sequence (video), and applications of computer vision in the industry.

FAQs About Applying CV for Autonomous Vehicles Course In Mumbai

Why go for the best python online course in Mumbai?

Skill-Lync is one of the best Python training institutes in Mumbai that offers one of the best online Python courses to learn various skills and apply them to computer vision. This Python online course certification also comes with a live project where you can experience a real problem and solve it using the basics.

What are the prerequisites for taking up Applying CV in the Autonomous Vehicles course in Mumbai?

There are no prerequisites for this course. To enrol in the autonomous vehicle certification course, you need to be interested in building a career in automobile engineering or image processing. 

What is the program fee of Skill-Lync's Applying CV in Autonomous Vehicles course in Mumbai?

The python online course certification in Mumbai comes with a flexible fee structure where you have three enrollment options-Basics, Pro and Premium plans. The basic plan is for INR 7,000 for three months for 2 months of access, the pro plan is for INR 10,000 for three months for 4 months of access, and the premium plan is for INR 15,000 for three months for a lifetime of access. 

What are the benefits of Applying CV for Autonomous Vehicles course in Mumbai?

By taking up Skill-Lync's Applying CV for Autonomous Vehicles course you gain industry-relevant skills. After completing the course you will receive a course completion certificate which you can showcase in your professional portfolio. You will get email and forum support to clear your doubts during your coursework. You will get a chance to work on industry projects which will help to boost your confidence in solving real-time problems.

After completing Applying CV in Autonomous Vehicles course In Mumbai, what are the career prospects?

After completing the course, you can apply for these jobs:

  • Computer Vision Engineer (Mapping - Autonomous Vehicles)
  • Autonomous Vehicles Test Engineer
  • AI Computer Vision Developer
  • Automation and Control Engineer
  • Autonomous Vehicles Motion Planning Engineer

What is the expected salary after completing this python online course certification in Mumbai?

After completing this python online certification course in India, the average expected salary is approx INR 3,86,745.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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5 years in the experience range

Instructors with 5 years extensive industry experience.

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Areas of expertise

  • Autonomous Vehicle Controls

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