Certified Computer Vision Expert Course

BY
DataMites

Explore deep learning techniques for CNN constructions and image processing, and master computer vision’s practical applications with the Couse.

Mode

Online

Duration

4 Months

Fees

₹ 18795 22000

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom +1 more
Mode of Delivery Video and Text Based

Course overview

DataMites’ Certified Computer Vision Expert Course online is an in-depth curriculum about using data techniques for CNN construction and image processing. Curated by analytics/data science experts, this is an industry-aligned programme accredited by the International Association of Business Analytics Certification (IABAC). Through this training, you’ll learn state-of-art computer vision techniques while undertaking hands-on projects.

The Certified Computer Vision Expert Course syllabus touches upon various computer vision topics. It also showcases the concept’s practical applications into tasks involving vision, such as image processing and object tracking. Datamites also has a dedicated placement team, who will train you to become employment-ready.

Moreover, the Certified Computer Vision Expert Course by Datamites offers flexible learning options. You can choose from the in-person classroom training, live instructor-led virtual classes, or the blended learning model (live mentoring + self-learning). All three provide the IABAC global certification upon completion. Depending on your course option, you can also get job and internship assistance. 

The highlights

  • Placement assistance team (PAT)
  • Career guidance by expert counsellors
  • Industry-expert trainers
  • Globally recognised certification by IABAC
  • 5 case studies
  • No mandatory prerequisites
  • Real-world projects
  • 3 learning options
  • Job + internship assistance
  • 1 client project
  • 10 capstones
  • Comprehensive study material 
  • Career mentoring sessions
  • 24x7 learner support

Program offerings

  • Career mentorship
  • Expert guidance
  • Specialised syllabus
  • Iabac’s global certification
  • Flexible learning modes
  • Capstones and case studies
  • Industry-aligned curriculum
  • Placement assistance

Course and certificate fees

Fees information
₹ 18,795  ₹22,000
  • There are three training options - Live Virtual, Blended Learning, and Classroom.
  • The Certified Computer Vision Expert Course fees differ, depending on which training option you choose. 

Certified Computer Vision Expert Course fee structure

Training Option

Fees in INR

Discounted Fee

Live Virtual

Rs.40,000

Rs.33,495

Blended Learning

Rs.22,000

Rs.18,795

Classroom

Rs.44,000

Rs.32,445
certificate availability

Yes

certificate providing authority

IABAC

Who it is for

The Certified Computer Vision Expert Course by Datamites is for individuals belonging to the computer vision domain. Freshers with computer vision knowledge are also ideal. 

Eligibility criteria

There are no hard-and-fast prerequisites for joining. However, it’s recommended that you first complete the ‘Certified Deep Learning Expert’ programme and know Deep Learning to join the Certified Computer Vision Expert Course training. 

To earn the Certified Computer Vision Expert Course certificate, you must complete the entire curriculum, submit all the projects, case studies, and capstones, and clear the examination. 

What you will learn

Knowledge of artificial intelligence Knowledge of numpy

Once you complete Datamites’ Certified Computer Vision Expert Course, you’ll be well-versed in the following concepts: -

  • Deep learning techniques for image processing and CNN (Convolutional Neural Networks)  construction
  • Practical applications for vision-related tasks, like image processing, object tracking, etc. 
  • AI fundamentals
  • AI data strategy, issues, ethics, concerns, challenges, adoption, and use cases
  • TensorFlow and its basics
  • TF 2.X
  • Tensorflow 2.X - Keras
  • Feed-forward algorithms
  • Neural networks’ structure
  • Backpropagations
  • Convolutional Neural Networks (CNNs)
  • Using NumPy to build neural networks from scratch
  • CNN's with Keras
  • Style transfers
  • CNN’s transfer learning
  • ResNet modelling
  • Flowers dataset with TF 2.X
  • Using CNN models to examine X-rays 

The syllabus

Introduction to Artificial Intelligence (AI)

AI Data Strategy

  • Data lake
  • Four stages of integrating and building data lakes with technology architectures
  • Foundation of AI data

AI Ethics, Issues, and Concerns

  • Concerns and Issues around AI
  • AI and bias
  • Ethical concerns and AI
  • AI: Bias, trust, and ethics

AI Challenges, Use cases, and Adoption

  • Lessons and pitfalls from the industry
  • Challenges of AI implementation
  • Future with AI
  • Use cases from top AI implementations
  • The journey for successful AI adoption

TensorFlow Introduction

  • Tensor + Flow = TensorFlow
  • Introduction to TensorFlow 2.X
  • Basis vectors and components
  • Functional and sequential APIs

TensorFlow Basic Concepts

  • Tensor degree/rank
  • Creating a Tensor
  • A Tensor’s shape
  • Usability-related changes
  • Create Flow for Tensor operations
  • Performance-related changes

Installation and Basic Operations in TF 2.X

  • Anaconda distribution installation
  • TensorFlow 2.X installation and setup
  • Databricks
  • Colab - Google’s free powerful lab
  • TensorFlow V2.X vs TensorFlow V1.X
  • TF 2.0 basic syntax
  • TensorFlow architecture

TF 2.0 Eager Mode

  • Placeholders and variables
  • TensorFlow graphs
  • Control statements and operations
  • TF 2.0 Autograph TF.Function
  • TensorFlow Platform’s application
  • TF 2.0 Eager execution mode

TensorFlow 2.X - Keras

  • Using Keras modules for NN modeling
  • In-built Keras in TensorFlow 2.X
  • Keras package introduction

Structure of Neural Networks

  • Introduction to perceptron
  • Neural networks - inspired by the human brain
  • Perceptrons - training
  • Binary classifications using perceptron
  • Working of a neuron
  • Multiclass classifications using perceptrons

Neural Network - Core Concepts

  • Hyperparameters and parameters of neural networks
  • Outputs and inputs of a neural network
  • Learning the Dimensions Weight Matrices
  • Information flow in neural networks - between 2 layers
  • Activation functions

Feed Forward Algorithm

  • Vectorised feed-forward implementations
  • Feed-forward algorithms
  • Understanding vectorised feed-forward implementations
  • The complexity of the loss function
  • What does training a network mean? 
  • Updating the biases and weights
  • Comprehension - training a neural network

Backpropagation

  • Batch in backpropagation
  • Sigmoid backpropagation
  • Regularisation
  • Training in batches
  • Batch normalisations

Building Neural Network from Scratch Using NumPy

  • Setups and imports
  • Creating feed-forward modules
  • Defining network variables
  • Creating backpropagation modules
  • Predictions using the network model
  • Integrating all modules for a complete neural network

Convolutional Neural Networks (CNNs) Introduction

  • Image processing basics
  • Introduction to CNNs
  • Understanding convolutions
  • Padding and stride
  • Understanding Mammals Eye perception
  • Important formulas
  • Feature maps
  • Putting the components together
  • Weights of a CNN
  • Pooling

CNNs with Keras - Tf 2.X

  • Comprehension - Vgg16 Architecture
  • Building CNNs in Keras - MNIST
  • Overview of the CNN Architectures
  • CIFAR-10 classifications with Python
  • Vggnet and Alexnet
  • Residual net
  • Googlenet

Transfer Learning in CNN

  • Use cases of transfer learning
  • Introduction to transfer learning
  • Practical implementations of transfer learning
  • Transfer learning with pre-trained CNNs
  • An analysis of deep learning models
  • Transfer learning in Python

Style Transfer

  • Gram matrix and style loss
  • Introduction to style transfer
  • Style transfer notebook
  • Loss function
  • Object detection

Flowers Dataset with Tf 2.X

  • Data preprocessing: shape, form, and size
  • Examining the Flowers dataset
  • Data preprocessing: augmentation
  • Data preprocessing: normalisation
  • Data preprocessing: practice exercise solutions

Resnet Modeling

  • Building the network
  • Resnet: improvements and original architecture
  • Hyperparameter tuning
  • Ablation experiments
  • Evaluating and training the model

Examining X-ray with CNN Model

  • CXR network building
  • CXR data preprocessing - augmentation
  • Examining X-ray images

Admission details

  • Visit the Certified Computer Vision Expert Course webpage.
  • Scroll down to the “Certified Computer Vision Expert Course training cost” section and check the learning options and their prices.
  • Select a preferable one and choose its ‘Enquire Now’ button. 
  • Fill out the on-screen details and tap the ‘Enquire Now’ option.
  • Datamites will reach out to you about your programme inquiry. 

Filling the form

To join the Certified Computer Vision Expert Course by Datamites, you must submit an enquiry request. For this, you must provide your full name, active email address, and contact number. You can also fill in your company name, if applicable. 

How it helps

Apart from the extensive syllabus and learning materials, there are various Certified Computer Vision Expert Course benefits to enjoy. Datamites offers a dedicated placement team, along with expert counsellors’ career guidance, enabling you to master the required qualities to become job-ready. 

Moreover, the Certified Computer Vision Expert Course certificate is a widely recognised accreditation by the IABAC. Thus, you’ll be able to seek higher pay and coveted roles in numerous organisations. 

FAQs

Do I have to pay for the examination separately?

No. The exam fee is part of the programme fee you pay.

What study material will be given to me?

Datamites will provide you with cheat sheets, videos, data sets, and extensive material on new letters, job updates, and job interviews. 

Who are the trainers?

The Certified Computer Vision Expert Course trainers are industry experts and PhDs, who are elite faculty members from reputed universities.

Is career guidance available?

Datamites offers career mentoring sessions by their expert counsellors. 

How are the ‘Classroom’ and ‘Live Virtual’ modes different?

While both the modes offer similar facilities like the IABAC certificate and 200 learning hours, each has its exclusive features. For example, the Classroom mode offers Cloud Lab access, whereas the Live Virtual mode offers 80-hour live training online.

Trending Courses

Popular Courses

Popular Platforms

Learn more about the Courses

Download the Careers360 App on your Android phone

Regular exam updates, QnA, Predictors, College Applications & E-books now on your Mobile

Careers360 App
150M+ Students
30,000+ Colleges
500+ Exams
1500+ E-books