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Applying CV for Autonomous Vehicles using Python in Bangalore

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 Bangalore

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 Bangalore

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

Learn to Apply Computer Vision for Autonomous Vehicles Using Python with Skill-Lync Bangalore

The Autonomous Vehicle industry is growing rapidly, and so is the demand for skilled employees in the field. In this regard, Skill-Lync Bangalore has designed a comprehensive course: Apply Computer Vision (CV) for Autonomous Vehicles using Python. It is a 12 weeks course where you can learn Python online and get a Python online course certification.

At Skill-Lync, best-in-class industry experts with over 5 years of industry experience, teach Python courses. Also, it must be noted that the Python training in Bangalore by Skill-Lync is not limited to learning just Python. During the course, you get hands-on training in many other technologies like MATLAB, TensorFlow, OpenCV, and Keras TensorFlow2.

Skill-Lync is one of the best ways to learn Python, as it teaches you industry-relevant skills that make you ready for the industry. It is one of the best python training Institutes in Bangalore that offers training and certification for all its learners.

FAQs

Why choose Skill-Lync’s Apply Computer Vision (CV) for Autonomous Vehicles using Python course in Bangalore?
Skill-Lync offers python courses in Bangalore, that teaches industry-relevant skills and to make you job-ready. Through this course you will get to work on industry projects which will help you gain confidence in solving issues faced by industries.

What are the prerequisites for enroling in Skill-Lync’s Apply Computer Vision (CV) for Autonomous Vehicles using Python course in Bangalore?

There is no specific prerequisite for pursuing this course. This course is curated by industry experts for engineering students and graduates of computer science and related streams of engineering.

What are the Python course duration and fees in Bangalore?
The course duration is 3 months and the fee structure is flexible with three plans: the basic plan, the pro plan and the premium plan. The basic plan provides you with 2 months of access at INR 7000 per month for three months, the Pro plan provides you with 4 months of access at INR 10,000 per month for three months and the Pro plan provides you lifetime access at INR 15,000 per month for three months.

What are the benefits of Skill-Lync’s Apply Computer Vision (CV) for Autonomous Vehicles using Python course in Bangalore?
You get hands-on training in cutting-edge technologies like Python, MATLAB, TensorFlow, OpenCV, and Keras TensorFlow2. Also, you will learn CV using Python, which is highly demanded in the Autonomous vehicle industry. 

After completing Skill-Lync’s apply Computer Vision (CV) for Autonomous Vehicles using Python course in Bangalore, what are the career prospects?
After completing the course, you can apply for these jobs:

  1. Computer Vision Engineer (Mapping - Autonomous Vehicles)
  2. Autonomous Vehicles Test Engineer
  3. AI Computer Vision Developer
  4. Automation and Control Engineer
  5. Autonomous Vehicles Motion Planning Engineer

After completing Skill-Lync’s Apply CV for Autonomous Vehicles using Python course in Bangalore, what is the expected salary range?
In India, the average salary of computer vision engineers is approx. INR 5.4 Lakhs per annum. In Bangalore, computer vision engineers can earn a minimum salary of INR 1.8 Lakhs per annum and a maximum of INR 17 Lakhs per annum, depending on their capabilities.

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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