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Applying CV for Autonomous Vehicles using Python

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


Kirankrishna M

advance technologies

SDM Institute of Technology Institute of technology in Ujire, Karnataka


Amit Bangre Consulting Limited

Swami Vivekananda Institute of Science & Technology


Altener Solutions Private Limited

Government Polytechnic College Kannur Polytechnic college in Kerala

Smita Suryavanshi


KLE Dr. M.S. Sheshgiri College of Engineering and Technology

Jitendra kumar Vishwakarma

Mando Softtech India Pvt. Ltd.

Ambition institute of technology

Meganath Prabu S

Tech Mahindra

C K College of Engineering and Technology


Tata Technologies

SNS College of Technology

AnilKumar Hubballi

Aakruthi3D pvt ltd

KLE Polytechnic Bailhongal


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

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

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

Applying CV for Autonomous Vehicles using Python

Skill Lync provides the best online python course to learn different skills and apply them to computer vision. The best way to learn Python is to use it to solve real-time business cases practically. The python online course certification comes with a live project where students can experience a real problem and solve it using the basics that they learn.

The course will also talk about the application of Computer Vision in autonomous vehicles. It will give in-depth insights on how Computer Vision can be used in vehicles to detect objects like traffic lights, turns, pedestrians, etc., on roads. Also, students will learn how vehicles can create situational awareness as soon as the road conditions change.

Once students learn Python onlinethey can also build vehicles that can detect low light and create a map of the place based on what it detects. The python online course certification will last for 12 weeks, and it will give an in-depth understanding of how Computer Vision can be used in designing autonomous vehicles.

Computer Vision has now become one of the most critical aspects of technology. To know more about Computer Vision, students need to take the best online python course. Students can learn Python online in 12 weeks and get a python online course certification for just about Rs 30,000.

Who Should Take Python Courses for applying to Autonomous Vehicles?

Python courses have a lot to offer and are not just limited to basic programming and designing software. Students can use Python to learn Computer Vision which can later be applied for designing autonomous vehicles. Anyone interested in building a career in automobile engineering or image processing can take this course. This course will provide in-depth insight into how Computer Vision works and how it can find applicability in different industries and situations. 

People having a background in Science and Mathematics can opt-in for the course as the basic concepts of computer science and algorithms are a part of the course. This will help students understand Computer Vision and then bring it to practical use. Computer Vision finds its application in medicine, law, agriculture, and several other fields.

What Will you Learn?

Once students decide to learn Python online, they will be exposed to various tools and techniques that will help them in mastering Computer Vision. With python online course certification, they will learn the following things:

  • An overview of Computer Vision.
  • An Understanding of Autonomous Vehicles.
  • Several Image Processing Techniques.
  • Edges and Line Detection.
  • Geometry using projective and stereo techniques.
  • An understanding of 3-D Computer Vision.
  • How will software detect and describe objects?
  • Optical flow using methods like Horn-Shunk.
  • Object tracking.
  • Image Segmentation.

Students will learn about all the things listed above in depth. However, the course is not limited to theoretical knowledge. It comes with the practical aspects too. Students will be working on two projects. In the 1st one, they will be performing basic image manipulations to understand how image processing works practically. In the 2nd project, students will get hands-on experience in image detection and several other filtering techniques. There are about ten other similar projects students will work on every week.

Skills You Will Gain?

The python online course certification will teach students a lot of skills. Some transferrable skills that students will acquire with the help of this course are listed below:

  • Image Processing
  • Matlab
  • Python Scripting
  • Driving Scenario Design
  • Knowledge of images on object detection
  • Optical flow of images in a video

Key Highlights of the Programme

  • The course by Skill-Lync comes with a certificate of completion and will be given to everyone who completes the course.
  • This three-month Skill-Lync programme teaches students everything they need to know about computer vision. As a tool, MATLAB will be used.
  • The 12 weeks programme is unique as students will get a chance to work on a live project every week. In a nutshell, the course comes with 12 projects.
  • The course also has a mini project where an image classification model will be implemented.

Career Opportunities after taking the course

A course in Computer Vision can help students make a career in the same domain. Computer vision is gradually but steadily becoming an integral part of everyone's daily lives. Students can obtain a postdoctoral research position before moving into academia and eventually becoming professors. This option usually necessitates a strong publication record throughout the PhD. Students can also work as CV researchers or developers for a corporation.

The requirements differ from one company to the next. CV researchers are needed by many corporations, including Google, Microsoft, Amazon, Facebook, and almost all high-tech manufacturing firms. Students can even become members of their country's defence research organisation; many weapon technologies require a CV or CV-like algorithms.

FAQs on Applying CV for Autonomous Vehicles using Python

1, Does the course come with a live project?
Yes, the course comes with weekly projects, and there are 12 projects in total. Also, there is a mini project post 6th week of the course.

2, Can I find a job after this course?

This course will make you ready for the industry, and you can easily find a job after its completion.

3, Will I get a merit certificate once the course is completed?

The merit certificate will be awarded to the top 5% of the class. However, everyone will be given a certificate of completion.

4, Is MobileNet architecture a part of the course?

Yes, you will be taught about MobileNet architecture, and the mini-project will be based on its fundamentals.

5, Can a commerce graduate enrol for this course?

No, the course is designed for people who have some experience in programming and have come from an engineering background.

6, Can the course fee be paid in instalments?

Yes, we have a 0% EMI plan for paying the course fee in instalments.

7, Can I get a scholarship for this course?

Yes, you can take a scholarship test and get a 10% scholarship on the course fee.

8, Will Computer Vision help me in other industries too?

Computer Vision is finding its application in fields like law, agriculture, etc. Therefore, you should opt-in for this course for some exposure.

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

  • 5 Years 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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