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Applying CV for Autonomous Vehicles using Python in Delhi

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 Delhi

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 Delhi

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 with Skill-Lync's best online Python course on How to Apply CV for Autonomous Vehicles in Delhi

Skill-Lync's Python courses in Delhi will cover computer vision applications in autonomous cars. It will take you through how Computer Vision can be utilized in automobiles to recognize objects on the road in traffic signals, turns, and so on. You will also explore how automobiles can generate situational awareness when driving conditions change. One of the most important parts of technology nowadays is computer vision. You should take the top online Python courses to learn more about Computer Vision.

If ride-hailing services have revolutionized the concept of transportation, autonomous vehicles will be the next renaissance, dramatically changing the whole transportation business. Researchers are expecting to see 8 million autonomous vehicles on road by 2025.

The comprehensive 12-week best online Python course focuses on developing new abilities and putting them to use in computer vision. The greatest approach to learning Python online is to apply it to real-world business problems. The Python training in Delhi includes industry projects that allow students to work on real-world problems. Curated by industry experts the Applying CV for Autonomous Vehicles course, will make you industry-ready and will enhance your employability skills.

FAQs About Applying CV for Autonomous Vehicles course in Delhi

Why go for Applying CV for Autonomous Vehicles course in Delhi?

According to Verified Market Research, the Computer Vision market is showing a growth rate of 45.64% CAGR from 2021 to 2028. Python is dominating in Computer Vision, hence Python online course certification in Delhi, will help you to upskill and land a job as Computer Vision Engineer.

What are the pre requisites for learning Python online courses in Delhi?

There is no pre requisite for learning Python online certification course in Delhi. However, engineering students and graduates with basic knowledge in coding and interested in autonomous vehicles can pursue this course.

What are the benefits of pursuing Applying CV for Autonomous Vehicles course offered by Skill-Lync?

By pursuing Applying CV for Autonomous Vehicles course,

  • You can gain industry-relevant skills
  • You can clear your doubts through expert mentorship
  • You can gain hands-on training in tools used by top OEMs.

What is the fee for Python courses in Delhi?

The Applying CV for Autonomous Vehicles course by Skill-Lync has a flexible fee structure and is available in three plans. The basic plan is available at INR 7,000 per month for 3 months, which has 2 months of access, a pro plan is available at INR 10,000 per month for 3 months, which has 4 months of access and the premium plan is available at INR 15,000 per month for 3 months for lifetime acces. You can choose a plan based on your convenience.

What are the career prospects after completing the Python online certification course in Delhi?

After completing the Python training in Delhi, several new opportunities will open up for you. Some exciting positions you can work for include:

  • Computer Vision Engineer
  • AI Engineer
  • Computer Vision Specialist
  • Automation and Control Engineer
  • Autonomous Vehicles Motion Planning Engineer

What is the expected salary range after completing the Python online course certification in Delhi?

The average annual salary of a Computer Vision Engineer is INR 6.9 lakhs per annum. However, your pay package tends to increase with your experience and expertise.

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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