When will I have access to the lectures and assignments?

You will have access to your onboarding course and all available self-paced content for this Certificate immediately after you enroll and pay. Once the first course officially begins, you’ll be able to ask questions to the teaching team, get feedback on your projects, and work with other peers on group assignments.

Will the certificate be issued by IIT Guwahati?

Yes! The certificate will be directly issued by the Indian Institute of Technology, Guwahati. View the sample certificate here!

What will I get if I pay for this programme?

You will get access to all Certificate courses. You will also get feedback from the teaching team on your projects. You’ll be working with an elite network of peers towards your goals.

Can I take this programme for free?

No. The Certificate is available only to learners who have paid for the programme.

What is the refund policy?

You will have 2 weeks after the start of the first course session to secure a refund.

Is financial assistance available?

Financial assistance is not available at this time for Certificates.

When are the enrolments opening?‎

Enrolments are now open. Last date to enrol is 21st December 2022.

What are the available payment modes?‎

Applicants from India can pay using debit or credit card, net banking, or through EMI. Applicants from outside of India, can pay through debit or credit cards and Paypal.

Certificate

Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality

Master deep learning methods and their application to computer vision and extended reality (XR). Learn from the expert faculty at the Indian Institute of Technology Guwahati, one of the leading engineering institutions in India.

Enrolments will open soon.

6 months

~ 6-8 hours per week

$1,500 / INR 1,12,500

100% Online

Live sessions with faculty & recorded classes.

Gain expertise in deep learning to build and deploy XR applications

Gain the IIT advantage

Learn from faculty & experts at one of India’s top-ranked engineering institutions. Earn a PG Certificate issued directly by IIT Guwahati.

Develop expertise in deep learning techniques and applications

Learn to design, develop, and deploy augmented and virtual reality systems using the Unity game engine and SDKs for VR and AR applications on desktop/ mobile platforms. Watch the faculty webinar to learn more.

Project-based learning experience

Effective learning with a practitioner’s curriculum including capstone projects, use cases and hands-on online labs. Get direct, real-time engagement and actionable feedback from the IITG faculty.

Descripción del programa

Master key deep learning and machine learning concepts and develop the skills needed to become an expert in deep learning modelling and its application to computer vision and extended reality.

Contexto requerido

A bachelor's degree along with a basic understanding of coding (C/C++), algorithms and high-school level mathematics is required to complete this programme.

Students in their third year of graduation may also enrol in this programme.

Habilidades que obtendrás

XR SDKs
Unity Engine
XR Application Development
Deep Learning
Encoder-Decoder model
Generative adversarial network (GAN)
Extended Reality
TensorFlow/Keras

Sumario

In this programme, you will first build a strong foundation in deep learning, computer vision, and extended reality. You will then learn to develop and deploy full-fledged deep learning-based models and applications.

As you advance through the programme, you’ll learn how to:

Navigate deep learning and machine learning models.
Build basic and advanced deep learning models such as MLP, Encoder-Decoder, GAN, and more..
Build deep learning based applications from scratch using Python and other software that includes Unity game engine and XR SDKs.

Working professionals, as well as undergraduates and postgraduate students, looking to specialise in the fields of deep learning, computer vision, and extended reality will find this programme useful.

This 6-month programme features 6 courses and 6 projects

Curso 1 de 6

Neural Network with TensorFlow/Keras

Qué aprenderás

Introduction to machine learning
Introduction to neural network
Building neural network using Tensorflow and Keras
TensorFlow and Keras programming

Proyecto(s)

Develop feed-forward, neural network-based classifiers with TensorFlow and Keras

In this project, you will build a classifier and a regression model by understanding and evaluating parameters, the effect of different activation functions and lost functions, the effect of hidden layers, and different evaluation methods.

Sumario

In this course, you will be introduced to the field of machine learning and neural networks. You will learn about feed-forward neural network/multi-layer perceptrons and implement MLP in TensorFlow and Keras for deep learning applications.

Curso 2 de 6

Fundamentals of Deep Learning

Qué aprenderás

Recurrent neural networks and their variants
Convolutional neural networks
Encoder-Decoder model
Applications and implementations

Proyecto(s)

Develop a face recognition system from optical images using different deep CNN models

In this project, you will develop a face recognition system from images with different deep CNN models, evaluate various parameter tuning and optimization techniques, and perform comparative analysis of different models.

Sumario

In this course, you will learn three neural network models— RNN/LSTM, CNN, and Encoder-Decoder—which are the building blocks of various deep learning models, followed by their implementation in TensorFlow for various applications like representation, classification, and regression.

Curso 3 de 6

Deep Learning - Advanced

Qué aprenderás

Attentions in neural network
Generative adversarial network (GAN) and N-shot learning
Transfer learning and multi-tasks learning
Applications and implementations

Proyecto(s)

Develop a face recognition system from optical images using different attention-based deep CNN models

In this project, you will develop a face recognition system from images with different attention-based deep CNN models.

Sumario

In this course, you will learn various advanced deep learning models such as attention, generative adversarial network (GAN), N-shot learning, multi-tasks learning and transfer learning in detail, followed by the implementation of these models with various real-world use cases.

Curso 4 de 6

Introduction to Extended Reality (XR)

Qué aprenderás

Human sensory organs and XR
XR hardware
Interaction in XR
XR software

Proyecto(s)

Setting up of an XR (AR/VR/MR) system development environment

In this project, you will apply hardware and software concepts taught in the course and choose one combination of hardware and software to set up a development environment for XR systems. Additionally, you will also write a small demo program to demonstrate the setup.

Sumario

In this course, you will be introduced to the field of extended reality, which includes virtual reality, augmented reality and mixed reality. You will learn about the field of XR and how human sensory organs play an important role in the development of successful XR systems. You will also get an in-depth introduction to XR hardware and software and the various methods of interaction with XR environments.

Curso 5 de 6

XR Foundation

Qué aprenderás

Interactive XR system development life-cycle
Foundation of computer graphics
Foundation of computer vision
Deep learning and XR

Proyecto(s)

Design and specification document for an XR system (VR/AR/MR)

In this assignment, you will create the design and specification document for an XR system.

Sumario

In this course, you will gain an in-depth understanding of the XR system development process. You will first learn about the stages to build XR systems. You will then be introduced to fundamentals of computer graphics and computer vision for better understanding of the working of an XR system. Finally, you will get to know about the use of deep learning in the development of XR systems.

Curso 6 de 6

Design & Implementation of AR/VR Systems

Qué aprenderás

Introduction to the Unity engine
VR and AR SDKs
VR app development with Unity
AR app development with Unity
Build and deploy simple AR systems

Proyecto(s)

App development for AR and VR

In this project, you will write code to build and deploy your own AR and VR apps developed with Unity engine and the SDKs taught throughout the course.

Sumario

In this course, you will learn about the Unity engine in detail along with two SDKs - one for VR system development and the other for AR system development. You will also learn to test and deploy the systems on desktops, laptops, and mobile platforms.

Instructores

Preguntas Frecuentes

If you need further assistance, please email pgc_dlcvxr@iitg.ac.in with any questions.

Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality

Enrolments will open soon.

6 months

$1,500 / INR 1,12,500

100% Online

Gain expertise in deep learning to build and deploy XR applications

Gain the IIT advantage

Develop expertise in deep learning techniques and applications

Project-based learning experience

Descripción del programa

Contexto requerido

Habilidades que obtendrás

Sumario

This 6-month programme features 6 courses and 6 projects

Instructores

Preguntas Frecuentes

When will I have access to the lectures and assignments? ‎

Will the certificate be issued by IIT Guwahati?‎

What will I get if I pay for this programme? ‎

Can I take this programme for free? ‎

What is the refund policy? ‎

Is financial assistance available?‎

When are the enrolments opening?‎ ‎

What are the available payment modes?‎‎

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