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Applying CV for Autonomous Vehicles using Python in Pune

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.

Book a Class, for FREE


Jayesh Suryawanshi

Volkswagen (I) Pvt. Ltd.,

RMD Sinhgad

Mithin SanthaKumar

Timetooth Technology

Cochin University of Science and Technology University in Kochi, Kerala

Manthan Waghaye

Altigreen Propulsion Labs Pvt Ltd

Shri Sant Gajanan Maharaj College Of Engineering

Hemant Sagar

KN Associates

PM polytechnic, Delhi ncr , sonipat

Jangaiah Chikonda



sai dinesh


usharama college of engineering and technology

Vadapalli A S Krishna Maruthi Srinivas

advance technologies

Jawaharlal Nehru Technological University, Kakinada

Manas Metar

Sphinix World Biz Limited

University of Wolverhampton


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 Pune

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 Pune

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.

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Upgrade Your Skills In Computer Vision Through Applying CV for Autonomous Vehicles using Python Course in Pune

Skill-Lync offers one of the best Python courses that allow students to learn the fundamentals of computer vision that can be applied in autonomous vehicles. Computer vision is a multidisciplinary field that focuses on how computers can assist in making meaningful interpretations of images and videos.

While computer vision (CV) has a decades-long history, the applications have been extended to various scientific fields, including automobile engineering. In recent times, CV has been used to help autonomous vehicles detect static and dynamic objects in their environment, such as traffic lights, turns, cars, and even pedestrians. Thus, anyone interested in learning about the necessary insights into how to increase situational awareness of autonomous vehicles can enrol in this Python course.

If you are wondering what are some of the best ways to learn Python and where to learn Python online, then this Python training with a job guarantee in Pune is for you. Once you complete this online Python course, you can apply for industry and research-based computer vision jobs. 

FAQs About the Ways to Applying CV for Autonomous Vehicles using Python in Pune

Why should I opt for this Python course? 

If the field of computer vision fascinates you, then this Python course in Pune is an ideal choice for you. With the help of the Python online course certification, you will be exposed to various updated computer vision technologies that they can integrate while designing autonomous vehicles.

What is the eligibility to join this Python online course certification?

There is no prerequisite to joining this course. Students and professionals interested in the field can enrol for this course.

How much is the total program fee for this Python course?

Skill-Lync's Python course in Pune fee is flexible with three plans. These options are: basic for INR 7,000 for three months with 2-months of access, pro for INR 10,000 for three months with 4-months of access, and premium for INR 15,000 for three months with lifetime access. 

How will I benefit from enrolling in this Python course?

This course will help you develop many skill sets, including image processing, MATLAB, Python scripting, and object detection MobileNet architecture. The course also has two live projects that help students gain practical insights and theoretical understanding of CV. 

What job roles can I apply for after completing this course?

After completig the Python course at Skill-Lync you can apply for the following job roles.

  • Computer Vision Engineer
  • AI Computer Vision Developer
  • Computer Vision and ML researcher

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

Your salary range is highly contingent upon your job role and the domain you are working in. According to Glassdoor, the average salary of a computer vision engineer is around INR 7 LPA. Likewise, a computer vision researcher can earn an average remuneration of around INR 4.5 LPA.



Flexible Pricing

Talk to our career counsellors to get flexible payment options.


INR 40,000

Inclusive of all charges

Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals

  • 1 Year Accessto Skill-Lync’s Learning Management System (LMS)

  • Personalized Pageto showcase Projects & Certifications

  • Live Individual & Group Sessionsto resolve queries, Discuss Progress and Study Plans.

  • Personalized & Hands-OnSupport over Mail, Telephone for Query Resolution & Overall Learner Progress.

  • Job-Oriented Industry Relevant Curriculumavailable at your fingertips curated by Global Industry Experts along with Live Sessions.

Instructors profiles

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


1 industry expert

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


5 years in the experience range

Instructors with 5 years extensive industry experience.


Areas of expertise

  • Autonomous Vehicle Controls

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