CERTIFIED COMPUTER VISION EXPERT CERTIFICATION AUTHORITIES

CERTIFIED COMPUTER VISION EXPERT COURSE FEATURES

DEEP LEARNING LEAD MENTORS

CERTIFIED COMPUTER VISION EXPERT COURSE FEE

Live Virtual

Instructor Led Live Online

660
545

  • IABAC®  Global Certification
  • 4-Month | 200 Learning Hours
  • 80-Hour Live Online Training
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship +Job Assistance

Blended Learning

Self Learning + Live Mentoring

360
303

  • Self Learning + Live Mentoring
  • IABAC®  Global Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

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BEST COMPUTER VISION EXPERT CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR CERTIFIED COMPUTER VISION EXPERT COURSE

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SYLLABUS OF CERTIFIED COMPUTER VISION EXPERT COURSE

  • Evolution of Human Intelligence
  • What is Artificial Intelligence?
  • History of Artificial Intelligence
  • Why Artificial Intelligence now?
  • AI Terminologies
  • Areas of Artificial Intelligence
  • AI vs Data Science vs Machine Learning
  • Foundation of AI Data
  • Data Lake
  • Four Stages of Building and Integrating Data Lakes within Technology Architectures
  • Issues and Concerns around AI
  • AI and Ethical Concerns
  • AI and Bias
  • AI: Ethics, Bias, and Trust
  • Challenges of AI Implementation
  • Pitfalls and Lessons from the Industry
  • Usecases from top AI Implementation
  • Future with AI
  • The Journey for adopting AI successfully
  • Introduction to Tensorflow 2.X
  • Tensor + Flow = Tensorflow
  • Components and Basis Vectors
  • Sequential and Functional APIs
  • Creating a Tensor
  • Tensor Rank /Degree
  • Shape of a Tensor
  • Create Flow for Tensor Operation
  • Usability-Related Changes
  • Performance-Related Changes
  • Tensorflow 2.X Installation and Setup
  • Anaconda Distribution Installation
  • Colab – Free Powerful Lab from Google
  • Databricks
  • Tensorflow V1.X  Vs Tensorflow V2.X
  • Tensorflow Architecture
  • Tf 2.0 Basic Syntax
  • Tensorflow Graphs
  • Variables and Placeholders
  • Operations and Control Statements
  • Tf 2.0 Eager Execution Mode
  • Tf 2.0 Autograph Tf.Function
  • Application of Tensorflow Platform
  • Keras Package Introduction
  • Inbuilt Keras in Tensorflow2.X
  • Using Keras Modules for Nn Modelling
  • Neural Networks - Inspiration from the Human Brain
  • Introduction to Perceptron
  • Binary Classification Using Perceptron
  • Perceptrons - Training
  • Multiclass Classification using Perceptrons
  • Working of a Neuron 
  • Inputs and Outputs of a Neural Network
  • Parameters and Hyperparameters of Neural Networks
  • Activation Functions
  • Flow of Information in Neural Networks - Between 2 Layers
  • Learning the Dimensions Weight Matrices 
  • Feedforward Algorithm
  • Vectorized Feedforward Implementation
  • Understanding Vectorized Feedforward Implementation
  • What does training a Network mean?
  • Complexity of the Loss Function
  • Comprehension - Training a Neural Network
  • Updating the Weights and Biases
  • Sigmoid Backpropagation
  • Batch in Backpropagation
  • Training in Batches
  • Regularization
  • Batch Normalization 
  • Imports and Setups
  • Defining Network Variables
  • Creating Feed Forward Module
  • Creating Back Propagation Module
  • Integrating all Modules for Complete Neural Network
  • Predictions using the Network Model
  • Introduction To CNNs
  • Image Processing Basics
  • Understanding Mammals Eye Perception
  • Understanding Convolutions
  • Stride and Padding
  • Important Formulas
  • Weights of a CNN
  • Feature Maps
  • Pooling
  • Putting the Components Together
  • Building CNNs In Keras - Mnist
  • Comprehension - Vgg16 Architecture
  • Cifar-10 Classification with Python
  • Overview of CNN Architectures
  • Alexnet and Vggnet
  • Googlenet
  • Residual Net
  • Introduction to Transfer Learning
  • Use Cases of Transfer Learning
  • Transfer Learning with Pre-Trained CNNs
  • Practical Implementation of Transfer Learning
  • Transfer Learning in Python
  • An analysis of Deep Learning Models
  • Introduction to Style Transfer
  • Style Loss and the Gram Matrix
  • Loss Function
  • Style Transfer Notebook
  • Object Detection
  • Examining the Flowers Dataset
  • Data Preprocessing: Shape, Size and Form
  • Data Preprocessing: Normalisation
  • Data Preprocessing: Augmentation
  • Data Preprocessing: Practice Exercise Solutions
  • Resnet: Original Architecture and Improvements
  • Building the Network
  • Ablation Experiments
  • Hyperparameter Tuning
  • Training and Evaluating the Model
  • Examining X-Ray Images
  • Cxr Data Preprocessing – Augmentation
  • Cxr: Network Building

OFFERED DEEP LEARNING TRAINING COURSES

CERTIFIED COMPUTER VISION EXPERT CAREER SUCCESS STORIES

CERTIFIED COMPUTER VISION EXPERT COURSE REVIEWS

ABOUT CERTIFIED COMPUTER VISION EXPERT TRAINING COURSE

Computer Vision refers to the ability of machines/computers to see, comprehend images(Photo/Video), and derive meaning out of them. Online platforms like Instagram and Youtube have photos and videos uploaded in great quantum, daily. For indexing certain videos or images, an algorithm needs to know, knowledgeable about the images or videos.

The Certified Computer Vision Expert course primarily talks about employing deep learning techniques for the processing of images, construction of Convolutional Neural Networks(CNN). The practical application of the concepts into tasks which involves vision, such as object tracking and image processing. It also involves the execution of various computer vision projects.

ABOUT DATAMITES CERTIFIED COMPUTER VISION EXPERT COURSE

To equip the candidate with the knowledge of Computer Vision.

  • No mandatory prerequisites
  • Completed the course on Certified Deep Learning Expert.
  • Knowledge of Deep Learning.
  • Any individual who is involved in the computer vision domain.
  • A fresher who possesses a good amount of knowledge in Computer Vision.
  • Wide Recognition.
  • Higher Pay.
  • Designed in tune with the current industry requirements.

DataMites™ is an authorized institute by the International Association of Business Analytics Certifications (IABAC™) providing global data science certification courses

  • DataMites™ is founded by Data Science/Analytics Experts, who had deep roots in the industry in the USA and Europe for decades.

  • You benefit from course syllabus of DataMites™ as designed inline with job requirement in the current market

  • You can choose from flexible learning options: Traditional classroom, Live Virtual classroom, and Self-learning.

  • DataMites™ has a dedicated Placement Assistance Team (PAT), which assists you to find the right data science job

  • If you are a worthy candidate, you can get an opportunity to work in global data science consulting projects

  • You can treat your DataMites™ relationship manager as your pal. We value your every request.

Deep Learning is a branch of machine learning that utilizes artificial neural networks to imitate the learning capabilities of the human brain. It involves training neural networks with multiple layers to extract complex patterns and achieve precise predictions or classifications.

Deep Learning operates by constructing and training neural networks with multiple layers of interconnected nodes called neurons. Each layer processes and transforms data, passing it to the next layer for further computation. Through backpropagation, the network adjusts connection weights to minimize errors and enhance predictions.

Deep Learning finds applications in diverse industries, including image and speech recognition, natural language processing, autonomous vehicles, healthcare diagnostics, recommendation systems, and fraud detection.

Noteworthy Deep Learning frameworks include TensorFlow, PyTorch, Keras, Caffe, and Theano. These frameworks provide efficient tools and libraries for building, training, and deploying deep neural networks.

Deep Learning is a subset of Machine Learning that concentrates on training deep neural networks with multiple layers. Unlike traditional Machine Learning, Deep Learning models automatically learn hierarchical representations from raw data, reducing the need for manual feature engineering.

To embark on a Deep Learning journey:

  • Develop a basic understanding of Deep Learning concepts and algorithms.
  • Learn programming languages like Python and relevant libraries such as TensorFlow or PyTorch.
  • Familiarize yourself with Deep Learning frameworks and tools.
  • Explore online resources, tutorials, and courses to gain practical knowledge.
  • Practice by implementing small-scale projects and conducting experiments.
  • Join online communities and forums to collaborate and learn from experts.

Deep Learning offers a broad range of career opportunities, including roles like Deep Learning Engineer, Data Scientist, Research Scientist, Machine Learning Engineer, Computer Vision Engineer, and Natural Language Processing Engineer. These roles span across sectors such as healthcare, finance, e-commerce, and autonomous vehicles.

In order to thrive in a Deep Learning career, it is crucial to have a solid grasp of mathematics, specifically in areas like linear algebra and calculus. Proficiency in programming languages like Python and hands-on experience with popular Deep Learning frameworks such as TensorFlow or PyTorch are indispensable. Furthermore, possessing skills in data preprocessing, model optimization, and effective problem-solving are highly advantageous in this field.

Salary prospects for Deep Learning professionals vary based on factors such as experience, location, and industry. On average, Deep Learning engineers and Data Scientists earn competitive salaries. According to industry reports, the median salary for a Deep Learning Engineer in the United States is $164,095 per year, with senior-level professionals earning even higher. (Indeed)

Networking and professional connections play a crucial role in Deep Learning careers. Building connections with peers, researchers, and industry experts can lead to collaborations, mentorship opportunities, and access to job openings. Networking platforms, industry events, and online communities dedicated to Deep Learning provide avenues for meaningful connections.

Continuous learning is vital in Deep Learning careers due to the rapid advancements and evolving nature of the field. Staying updated with the latest research papers, attending conferences and workshops, and exploring new techniques and tools are essential to remain relevant and competitive. Continuous learning equips professionals to tackle new challenges and embrace emerging opportunities.

The future of Deep Learning looks promising as it continues to advance and find applications across various industries. Ongoing research and development are expected to enhance the efficiency, interpretability, and ability of Deep Learning models to handle complex tasks. With the exponential growth of data, Deep Learning's capability to extract valuable insights from large datasets will become increasingly valuable, driving further innovation and adoption.

Computer vision is an area of artificial intelligence dedicated to empowering computers with the ability to comprehend and interpret visual data obtained from images or videos. It encompasses the extraction of valuable information, identification of objects, and the execution of tasks such as object detection, image segmentation, and image classification.

A computer vision expert is a professional with specialized knowledge and expertise in the field of computer vision. They possess deep understanding and practical experience in developing algorithms, models, and systems to analyze and interpret visual data using techniques such as image processing, pattern recognition, and deep learning.

Computer vision and deep learning are closely related. Deep learning, specifically deep neural networks, has revolutionized computer vision by enabling the automatic learning of hierarchical representations from raw image data. Deep learning models have achieved remarkable results in various computer vision tasks, surpassing traditional computer vision techniques in accuracy and performance.

Learning computer vision opens up numerous opportunities in fields like robotics, autonomous vehicles, healthcare, surveillance, and augmented reality. It allows you to develop applications that can understand and interpret visual data, enabling automation, object recognition, and intelligent decision-making based on images or videos. Computer vision skills are in high demand and offer exciting career prospects.

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FAQ’S OF CERTIFIED COMPUTER VISION EXPERT TRAINING COURSE

The trainers for the Computer Vision Expert  course have experienced Data Scientists, AI and Machine Learning experts who possess good knowledge of the subject matter.

 No. Coding is not required to learn Computer Vision Expert courses.

This course is perfectly aligned to the current industry requirements and gives exposure to all the latest techniques and tools. The course curriculum is designed by specialists in this field and monitored and improved by industry practitioners on a continual basis.

You can enrol for the Computer Vision Expert Course by visiting our website, and doing the payment through Debit/Credit card, Visa. The receipt for the payment done will be sent to your registered E-mail id.

Yes. You will be given a certificate after the completion of the Computer Vision Expert course.

You will receive certification from IABAC® - International Association of Business Analytics Certification.

No, the exam fees are already included in the course fee and you will not be charged extra.

Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constraints, your relation manager at DataMites™ shall assist you with part payment agreements

DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on an individual basis in assisting for the right Data Science job.

 

You get a 100% refund training fee if the training is not to your satisfaction but the exam fee will not be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis

DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with the latest information on Data Science as well as job updates.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • Job connect
  • Resume Building
  • Mock interview with industry experts
  • Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

DataMites is widely recognized as one of the best deep learning course providers. They offer a comprehensive curriculum, renowned faculty, and industry-recognized certifications, making them a global institute for deep learning education.

DataMites offers the following Deep Learning Certification Training: Certified Deep Learning Expert, Certified Computer Vision Expert, Deep Learning with Python Courses, and Deep Learning - Tensorflow.

The DataMites Certified Computer Vision Expert Course is designed to equip individuals with expertise in computer vision, a subfield of deep learning. Participants learn to apply deep learning algorithms and techniques to tasks such as image classification, object detection, image segmentation, and facial recognition. The course covers popular computer vision frameworks and tools, enabling students to develop real-world computer vision applications.

The DataMites Certified Computer Vision Expert Training is open to individuals who are interested in gaining expertise in computer vision, a subfield of deep learning. This training is suitable for students, working professionals, researchers, and anyone looking to enhance their skills and knowledge in computer vision using deep learning techniques.

The DataMites Certified Computer Vision Expert Course is designed to provide expertise in computer vision, a subfield of deep learning. Participants learn to apply deep learning algorithms to tasks such as image classification, object detection, and facial recognition.

There are compelling reasons to choose DataMites for Certified Computer Vision Expert Training Online, including global accreditation, a large student community, a comprehensive learning approach with self-study materials and live sessions, globally recognized certification, and internship opportunities.

The Certified Computer Vision Expert Course at DataMites varies based on the chosen course and training mode. 

  • USA: USD 296 to USD 660
  • India: INR 18,348 to INR 44,000
  • UK: GBP 276 to GBP 700

The Flexi-Pass option allows you to attend DataMites training sessions for a duration of 3 months, providing added support and guidance to enhance your learning experience.

Yes, upon completing the Certified Computer Vision Expert Courses at DataMites, you will be awarded the prestigious IABAC® certification, which holds global recognition and adds value to your professional profile.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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