|| About Computer Vision

AI and machine learning have some of the most fascinating domains, including computer vision. It can be used in a wide range of sectors, including robotics, augmented reality, and self-driving cars. You will learn about Computer Vision and its numerous applications in a variety of sectors in this course designed for beginners.

During this course, you will learn how to process images using Python, Pillow, and OpenCV. You will also do object identification and image categorization.


Computers can now read and comprehend visual data from the actual world thanks to the multidisciplinary discipline of computer vision. Students will receive a thorough introduction to computer vision concepts, methods, and applications in this course. Students will learn how to create computer vision systems for tasks including object identification, picture segmentation, and image classification through lectures, practical exercises, and hands-on projects.


Please contact the nearest BIT training institute or send an email to inquiry@bitbaroda.com with any additional questions you may have regarding our Computer Vision  training course. We offer a free demo by calling us at +91-9328994901. We offer top-notch Computer Vision classes in Vadodara-Sayajigunj, Vadodara - Waghodia Road, Vadodara - Manjalpur, Ahmedabad, Anand, and Nadiad.

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|| What will I learn?

  • Understand the fundamental principles and concepts of computer vision.
  • Process and analyze images and videos using computer vision techniques.
  • Implement algorithms for feature detection and matching.
  • Develop methods for object recognition and classification.
  • Apply deep learning techniques to computer vision tasks.
  • Solve real-world problems using computer vision technologies.

|| What will I learn?

  • Understand the fundamental principles and concepts of computer vision.
  • Process and analyze images and videos using computer vision techniques.
  • Implement algorithms for feature detection and matching.
  • Develop methods for object recognition and classification.
  • Apply deep learning techniques to computer vision tasks.
  • Solve real-world problems using computer vision technologies.

|| Requirements

  • Proficiency in a programming language (Python preferred)
  • Familiarity with machine learning concepts
  • Basic understanding of linear algebra, calculus, and probability

|| Requirements

  • Proficiency in a programming language (Python preferred)
  • Familiarity with machine learning concepts
  • Basic understanding of linear algebra, calculus, and probability


    Our computer vision course content encompasses a comprehensive journey into the realm of teaching computers to understand visual data. It begins with foundational concepts, introducing students to the fundamental principles of image processing to refine and manipulate images for analysis. From there, the course progresses into more intricate techniques, including feature extraction, where students learn to identify key elements within images. Advancing further, students explore object detection and recognition, mastering algorithms that can locate and categorize objects within visual data. A significant portion of the course is dedicated to deep learning methodologies, particularly convolutional neural networks (CNNs), renowned for their efficacy in deciphering images. As the curriculum unfolds, students delve into semantic segmentation, object tracking, and the complexities of 3D computer vision, gaining insights into interpreting visual data in both 2D and 3D domains. Throughout the journey, emphasis is placed on real-world applications spanning diverse fields such as facial recognition, medical imaging, autonomous vehicles, and augmented reality. The course is punctuated with hands-on projects, providing students with practical experience in implementing computer vision solutions and honing their skills. By the course's conclusion, students emerge equipped with a comprehensive toolkit and deep understanding, ready to navigate the intricacies of computer vision and contribute to its ever-evolving landscape.

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    • Computer Vision
    • Image Formation
    • Sampling and Quantisation
    • Image Processing – flipping, cropping, rotating, scaling
    • Image statistics & Histogram
    • Spatial Resolution
    • Gray level/Intensity Resolution
    • Spatial Filtering
    • Convolution
    • Smoothing, Sharpening
    • Color Space Conversion & Histogram


    • Thresholding for Binarization
    • Morphological Operations
    • Image Gradient
    • Bounding Box
    • Sobel’s Edge Detection Operator
    • Template Matching
    • Image Feature – Keypoint and Descriptor
    • Harris Corner Detector
    • Object Detection with HoG
    • Stream Video Processing with OpenCV

    • Computer Vision
    • Convolution Neural Networks (CNN)
    • Why CNN? Building an Intuition for CNN
    • CNN, Kernels, Channels, Feature Maps, Stride, Padding
    • Receptive Fields, Image Output Dimensionality Calculations, MNIST Dataset
    • Explorations with CNN
    • MNIST CNN Intuition, Tensorspace.js, CNN Explained, CIFAR 10 Dataset Explorations with CNN
    • Dropout & Custom Image Classification for Cat and Dog Datasets
    • Deployment in Heroku, AWS or Azure


    • CNN Architectures
    • LeNet-5
    • AlexNet, VGGNet
    • Inception, ResNet
    • Data Augmentation
    • Benefits of Data Augmentation
    • Exploring Research Papers
    • Exploring Augmentor


    • Object Detection Basics
    • What is Object Detection?
    • Competitions for Object Detection
    • Bounding Boxes
    • Bounding Box Regression
    • Intersection over Union (IoU)
    • Precision & Recall
    • What is Average Precision?
    • Practical Training using Tensorflow1.x
    • Custom Model Training in TFOD1.x
    • Our Custom Dataset
    • Doing Annotations or labelling data
    • Pretrained Model from Model Zoo
    • Files Setup for Training
    • Export Frozen Inference Graph
    • Inferencing with our trained model in Colab, Training in Local
    • Inferencing with our trained model in Local


    • Practical Training using Tensorflow2.x
    • Introduction to TFOD2.x
    • Using the Default Colab Notebook
    • Google Colab & Drive Setup


    • Visiting TFOD2.x Model Garden
    • Inference using Pretrained Model
    • Inferencing in Local with a pretrained model


    • Practical Object Detection Using YOLO V5
    • Introduction for YoloV5
    • YoloV5 Google Colab Setup
    • Inferencing using Pre-Trained Model


  • Prompt Engineering
  • Why Prompt Engineering?
  • ChatGPT
  • Few Standard Definitions:
  • Label
  • Logic
  • Model Parameters (LLM Parameters)
  • Basic Prompts and Prompt Formatting
  • Elements of a Prompt:
  • Context
  • Task Specification
  • Constraints
  • General Tips for Designing Prompts:
  • Be Specific
  • Keep it Concise
  • Be Contextually Aware
  • Test and Iterate
  • Prompt Engineering Use Cases
  • Information Extraction
  • Text Summarization
  • Question Answering
  • Code Generation
  • Text Classification
  • Prompt Engineering Techniques
  • N-shot Prompting
  • Zero-shot Prompting
  • Chain-of-Thought (CoT) Prompting
  • Generated Knowledge Prompting

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|| Scope of Computer Vision

The scope of computer vision in India is vast and continually expanding, driven by technological advancements, increasing digitization across industries, and growing demand for automation and artificial intelligence (AI) solutions. Here are some key factors contributing to the scope of computer vision in India:

 

  • Emerging Industries: India's economy is diversifying beyond traditional sectors like IT and manufacturing into emerging industries such as healthcare, agriculture, retail, and smart cities. Computer vision technologies have applications across these sectors, including medical imaging, precision agriculture, retail analytics, and intelligent surveillance systems.
  • Research and Development: Indian research institutions, universities, and companies are actively engaged in research and development in computer vision. Organizations like the Indian Institutes of Technology (IITs), Indian Institutes of Information Technology (IIITs), and Indian Statistical Institute (ISI) are conducting cutting-edge research in computer vision algorithms, techniques, and applications. 
  • Startup Ecosystem: India has a vibrant startup ecosystem with a growing number of startups focusing on AI, computer vision, and related technologies. These startups are developing innovative solutions for various industries, driving entrepreneurship and innovation in the field of computer vision.
  • Government Initiatives: The Indian government has launched initiatives such as the National Programme on AI and the National Digital Health Mission (NDHM), which emphasize the adoption of AI and digital technologies, including computer vision, to address societal challenges and drive economic growth.
  • Industry Adoption: Indian industries are increasingly adopting computer vision technologies to improve efficiency, productivity, and decision-making. Companies in sectors such as manufacturing, automotive, e-commerce, healthcare, and security are leveraging computer vision for tasks such as quality inspection, autonomous vehicles, image-based diagnostics, and surveillance systems.
  • Skill Development: There is a growing demand for skilled professionals in computer vision in India. Academic institutions, training organizations, and online platforms are offering courses and programs in computer vision, machine learning, and AI to meet this demand and equip individuals with the necessary skills for careers in this field. 
  • Global Opportunities: Indian professionals and companies are also tapping into global opportunities in computer vision, collaborating with international partners, participating in research projects, and providing outsourcing services in areas such as image annotation, data labeling, and model development.

 

Overall, the scope of computer vision in India is promising, with ample opportunities for innovation, entrepreneurship, and career growth in this exciting and rapidly evolving field. As technology continues to advance and industries embrace digital transformation, computer vision is poised to play a significant role in shaping the future of various sectors in India and beyond.

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|| Computer Vision Career Option in India

Computer vision offers numerous career options and job opportunities in India, given its wide-ranging applications across industries. Here's a look at some potential career paths and job roles in computer vision, along with the job market scenario in India:

 

  • Computer Vision Engineer/Researcher: Computer vision engineers work on developing algorithms and systems for tasks such as object detection, image classification, facial recognition, and video analysis. They may also conduct research to advance the field of computer vision. Roles can be found in both industry and academia.
  • Machine Learning Engineer: Machine learning engineers specialize in building and deploying machine learning models, including those used in computer vision applications. They develop algorithms, preprocess data, train models, and optimize performance. Many machine learning engineer roles in India involve computer vision projects. 
  • Data Scientist: Data scientists analyze large datasets to extract insights and solve complex problems. In the context of computer vision, they may work on tasks such as image processing, feature extraction, and pattern recognition. Data science roles in India often include computer vision projects, especially in industries like healthcare, e-commerce, and manufacturing.
  • Software Developer (Computer Vision): Software developers with expertise in computer vision build applications and systems that incorporate visual data processing capabilities. They may work on developing computer vision libraries, frameworks, or applications for specific domains such as augmented reality (AR) or autonomous vehicles.
  • AI/Computer Vision Product Manager: Product managers in the AI and computer vision space are responsible for defining product strategies, prioritizing features, and overseeing the development and launch of computer vision-based products or solutions. They work closely with cross-functional teams to ensure that products meet user needs and market requirements.
  • Research Scientist (Computer Vision): Research scientists focus on advancing the state-of-the-art in computer vision through innovative research and experimentation. They may work in research labs, academic institutions, or industrial research divisions, contributing to the development of new algorithms, techniques, and applications.

 

In terms of job opportunities, the demand for computer vision professionals in India is on the rise, driven by the growth of industries such as healthcare, e-commerce, automotive, robotics, and security. Major technology companies, startups, research organizations, and multinational corporations in India actively recruit professionals with expertise in computer vision.

 

 

|| Computer Vision holds a Prominent Position in Indian job Market 

In India, computer vision offers a plethora of placement opportunities across various industries. With the rapid advancement of technology and the increasing demand for automation and digitalization, companies in sectors such as healthcare, automotive, e-commerce, manufacturing, and security are actively seeking professionals skilled in computer vision. From developing intelligent surveillance systems to enhancing medical diagnostics, the applications of computer vision are vast and diverse. Tech giants, startups, research institutions, and multinational corporations are all investing in this field, creating a thriving job market for computer vision engineers, researchers, and specialists. With India's strong presence in the global IT sector and its burgeoning startup ecosystem, individuals with expertise in computer vision can explore a wide range of career paths and find ample opportunities for growth and innovation. Whether it's working on cutting-edge projects in artificial intelligence, contributing to advancements in autonomous vehicles, or revolutionizing retail with image recognition technologies, the placement opportunities in computer vision in India are abundant and promising for those with the right skills and passion for innovation.


Tech giants like Google, Microsoft, Amazon, and IBM have significant research and development centers in India, actively working on projects related to computer vision. Additionally, Indian IT services companies such as TCS, Infosys, Wipro, and Cognizant are integrating computer vision into their offerings, creating opportunities for professionals in this domain. Startups like Flipkart, Ola, Swiggy, and Zomato are leveraging computer vision to enhance user experiences and streamline operations in e-commerce, transportation, and food delivery. Automotive companies like Mahindra & Mahindra, Tata Motors, and Maruti Suzuki are investing in computer vision for developing advanced driver-assistance systems and autonomous vehicles. Moreover, research institutions and academic organizations like IITs (Indian Institutes of Technology) and IIITs (Indian Institutes of Information Technology) are conducting cutting-edge research in computer vision, providing avenues for both employment and further academic pursuits. With a diverse range of companies and industries embracing computer vision technologies, professionals in India have a multitude of exciting career opportunities to explore and contribute to groundbreaking innovations in this field.

|| Job Roles and Salary

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|| Average Salary for Computer Vision in India

It seems there might be a bit of confusion in your question. The average salary of a computer vision course itself wouldn't typically be quantified as it's an educational program rather than a profession. However, if you're referring to the average salary of individuals who have completed a computer vision course in India at different levels of experience, that's a different matter.

 

Here's a breakdown of how the average salary might vary based on experience levels:

 

  • Entry-level: Individuals who have recently completed a computer vision course and have little to no work experience might expect salaries ranging from ₹300,000 to ₹800,000 per year (approximately $4,000 to $11,000 USD) depending on factors such as location and company.
  • Mid-level: With a few years of experience or additional specialized training, individuals might command salaries ranging from ₹800,000 to ₹2,500,000 per year (approximately $11,000 to $34,000 USD). At this level, professionals are expected to have more hands-on experience and may take on more complex projects or leadership roles. 
  • Senior-level: Professionals with extensive experience, advanced degrees, or specialized expertise in computer vision could earn salaries upwards of ₹2,500,000 per year (approximately $34,000 USD) or more. At this level, individuals may lead teams, manage projects, or hold strategic roles within organizations.

 

It's important to note that these salary ranges are approximate and can vary based on factors such as location (e.g., salaries might be higher in tech hubs like Bangalore or Hyderabad), company size, industry, and individual negotiation skills. Additionally, staying updated with the latest advancements in computer vision technologies and continuously honing one's skills can contribute to higher earning potential over time.

|| Become an Expert in Computer Vision

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|| Some Prominent Companies in India that use Computer Vision

Several companies in India leverage computer vision for various applications across different sectors. Here are some prominent companies that use computer vision technology:

 

  • Flipkart: As one of India's largest e-commerce platforms, Flipkart employs computer vision for tasks such as image recognition, product categorization, visual search, and quality inspection. Their computer vision solutions help enhance user experience, optimize search results, and streamline operations.
  • Myntra: Myntra, a subsidiary of Flipkart, focuses on fashion e-commerce and utilizes computer vision for tasks such as virtual try-on, product recommendations based on visual similarity, and trend analysis. Their computer vision algorithms enable personalized shopping experiences for users. 
  • Zomato: Zomato, a leading food delivery and restaurant discovery platform, uses computer vision for menu digitization, dish recognition, and quality assurance. Computer vision technology helps improve menu accuracy, enhance user engagement, and maintain quality standards. 
  • Swiggy: Similar to Zomato, Swiggy employs computer vision for menu digitization, dish recognition, and quality assessment to enhance the food ordering and delivery experience. Their computer vision solutions enable faster and more accurate order processing.
  • Ola: Ola, one of India's largest ride-hailing companies, integrates computer vision for driver verification, safety monitoring, and vehicle tracking. Computer vision technology enhances passenger safety, driver accountability, and overall service reliability. 
  • Drone Startups: Several Indian startups specialize in drone technology and utilize computer vision for applications such as aerial surveillance, agricultural monitoring, infrastructure inspection, and disaster response. These startups leverage computer vision algorithms for object detection, tracking, and analysis from drone-captured images and videos. 
  • Healthcare Companies: Healthcare companies in India leverage computer vision for medical imaging analysis, disease diagnosis, telemedicine, and healthcare analytics. Computer vision algorithms assist healthcare professionals in tasks such as pathology analysis, radiology interpretation, and patient monitoring. 
  • Retail Chains: Retail chains in India utilize computer vision for inventory management, shelf monitoring, customer analytics, and cashier-less checkout systems. Computer vision technology helps retailers optimize store operations, improve inventory accuracy, and enhance customer service.
  • Automotive Companies: Indian automotive companies and startups integrate computer vision into vehicles for applications such as driver assistance systems, pedestrian detection, traffic sign recognition, and autonomous driving. Computer vision technology enhances vehicle safety, navigation, and efficiency on Indian roads. 
  • Security and Surveillance Providers: Security and surveillance companies in India leverage computer vision for facial recognition, object detection, crowd analysis, and anomaly detection. Computer vision solutions enhance security measures, public safety, and law enforcement efforts.

 

These are just a few examples of companies in India that use computer vision technology across diverse sectors. As the adoption of artificial intelligence and computer vision continues to grow, more Indian companies are expected to integrate these technologies into their products, services, and operations.

|| Top Hiring Companies

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|| Get Certified, Get Ahead

Three easy steps will unlock your Computer Vision Certification:

 

  • Finish the online / offline course of Computer Vision Course and the Assignment
  • Take on and successfully complete a number of industry-based Projects
  • Pass the Computer Vision Certification exam


The certificate for this Computer Vision Certification will be sent to you through our learning management system, where you can also download it. Add  a link to your certificate to your CV or LinkedIn profile.


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|| Frequently asked question

BIT offers a wide range of programs catering to various interests and career paths. These may include academic courses, vocational training, professional development, and more. Please visit our website – www.bitbaroda.com or contact our admissions office at M.9328994901 for a complete list of programs.

This course is suitable for students, professionals, and enthusiasts interested in gaining expertise in computer vision. It caters to individuals with varying levels of experience, from beginners with no prior knowledge to experienced practitioners looking to specialize in computer vision techniques.

Most reputable Computer Vision courses offer a certificate of completion, which can enhance your credentials and be added to your resume or LinkedIn profile. It's essential to verify the accreditation and recognition of the issuing institution or organization.

Yes, many Computer Vision courses are available online, offering flexibility in terms of timing and location. Online courses often provide video lectures, interactive exercises, and discussion forums to facilitate learning.

After completing the course, you may continue to have access to course materials, online resources, alumni networks, career services, and professional development opportunities to support your continued learning and career growth.

For any questions or assistance regarding the enrolment process, admissions requirements, or program details, please don't hesitate to reach out to our friendly admissions team. Please visit our website – www.bitbaroda.com or contact our admissions office at M.9328994901 for a complete list of programs or Visit Our Centers – Sayajigunj, Waghodia Road, Manjalpur in Vadodara, Anand, Nadiad, Ahmedabad

BIT prides itself on providing high-quality education, personalized attention, and hands-on learning experiences. Our dedicated faculty, state-of-the-art facilities, industry partnerships, and commitment to student success make us a preferred choice for students seeking a rewarding educational journey.

BIT committed to supporting students throughout their academic journey. We offer a range of support services, including academic advising, tutoring, career counselling, and wellness resources. Our goal is to ensure that every student has the tools and support they need to succeed.

We will use Python and libraries such as OpenCV, TensorFlow, and Keras. Course materials include lecture notes, videos, and relevant articles.

Yes, the Computer Vision course by BIT is designed to equip you with practical skills that are directly applicable to real-world projects.

There will be a discussion forum for students to ask questions and collaborate. Instructors and teaching assistants will also provide support.
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