- What is artificial intelligence?
- Evolution of human intelligence
- Why artificial intelligence now?
- History of Artificial Intelligence
- Areas of artificial intelligence
- AI terminologies
- AI vs Machine learning vs Data science
Online
4 Months
₹ 17,323 24,000
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
- 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 |
Live Virtual | Rs.28,598 |
Blended Learning | Rs.17,323 |
Classroom | Rs.28,598 |
certificate availability
certificate providing authority
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
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
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.
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.
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
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
No. The exam fee is part of the programme fee you pay.
Datamites will provide you with cheat sheets, videos, data sets, and extensive material on new letters, job updates, and job interviews.
The Certified Computer Vision Expert Course trainers are industry experts and PhDs, who are elite faculty members from reputed universities.
Datamites offers career mentoring sessions by their expert counsellors.
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.