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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Deep Learning - Part 2 certification course covers a comprehensive curriculum that includes an intersection of Deep Learning and Generative Modeling, Restricted Boltzmann Machines, Markov Chains and Gibbs Sampling for training RBMs. The students gain hands-on training from expert professionals in the industry. This course provides from basic to in-depth discussion on the subject.

The Deep Learning - Part 2 certification by NPTEL course duration is 8 weeks and deep learning is the prerequisite for this course. This course benefits the students to equipped with the necessary skills and knowledge to excel in the deep learning field. The course can be obtained by BE/BTech/ME/MTech/MS/PhD students.

Also Read: Online Deep Learning Courses & Certifications

The Highlights

8 Weeks to Complete
IIT Completion Certification
Elective Online Course
For UG/PG/PhD

Programme Offerings

Books
video lectures
Transcripts
Hands-on Learning
assignments

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	IIT Madras

Eligibility Criteria

Academic Qualifications

The Deep Learning - Part 2 certification course is eligible for BE/BTech/ME/MTech/MS/PhD students.

What you will learn

After completing the Deep Learning - Part 2 certification syllabus, the students will explore directed graphical models, Markov networks, joint distributions for classification and sampling, and latent variables. They will also gain in-depth knowledge in variational autoencoders, autoregressive models, GANs, restricted Boltzmann Machines, and unsupervised learning.

When the students have completed the Deep Learning - Part 2 training, they will also explore various principles and strategies explained by industry experts and implement them in real-world projects. Students will gain hands-on training experience which can be applied by various companies such as Google, Microsoft, Amazon, Adobe, and IBM.

Who it is for

Robotics EngineerData ScientistMachine Learning EngineerDeep Learning EngineerArtificial Intelligence Engineer

The Deep Learning - Part 2 online course is designed for aspiring computer science and engineering students looking to enhance their skills and knowledge. This course can also be beneficial for:

Admission Details

To register for the Deep Learning - Part 2 classes, follow these steps:

Step 1: Click the link below:

https://nptel.ac.in/courses/106106201

Step 2: Students can “Login In” with the “Log In button” available on the top right side of the page and create a separate account or “Log In with Microsoft or Google Account.”

Step 3: After filling out the details in the form submit and join the course.

The Syllabus

A brief introduction to Directed Graphical Models

A brief introduction to Markov Networks, Using joint distributions for classication and sampling, Latent variables

Restricted Boltzmann Machines, Unsupervised Learning, Motivation for Sampling, Markov Chains, Gibbs Sampling for training RBMs, and Contrastive Divergence for training RBMs

Variational Autoencoders, Autoregressive models, GANs

IIT Madras Frequently Asked Questions (FAQ's)

1: What are the eligibility requirements for the Deep Learning - Part 2 online course?

The only prerequisite for this certification course is the deep learning knowledge and skills that the students must have to obtain the course.

2: How long does it take to complete the Deep Learning - Part 2 training?

It takes 8 weeks of duration to complete this course. The students can access the online study material available on the official website to gain in-depth knowledge.

3: What are the industries applicable to the Deep Learning - Part 2 online course?

The companies or industries that apply to this certification course are Google, Microsoft, Amazon, Adobe, and IBM.

4: Can I pursue a Deep Learning - Part 2 certification course if I have a study background in engineering?

Yes, engineering background students are also eligible for this course. The intended audience for this course is BE/BTech/ME/MTech/MS/PhD students.

5: What is the Deep Learning - Part 2 certification syllabus?

The certification course covers various topics such as Directed Graphical Models, Markov Networks, Markov Chains, Gibbs Sampling for training RBMs, Variational Autoencoders, Autoregressive models, and GANs.