Certificate in Deep Learning with PyTorch

Certifications are one way to prove to skill and expertise in front of your superiors. Certificate in Deep Learning with PyTorch can help you getting the spotlight among other employees. The concept of survival of fittest has started ruling the corporate sector so, now you have to prove your excellence to secure your position.

PyTorch is grabbing the attention of all data science professionals due to its ease of use over other libraries and its use of dynamic computation graphs. Like Python, PyTorch has a clean and simple API, which makes building neural networks faster and easier. Certifications also help to prove your dedication and commitment towards your aim and profession. IT sector has never ceased to offer jobs to people who fulfil the requirements. And certified professionals have never ceased to be in demand. The more certificates you have, the more you will be preferred by the companies.

Roles and Responsibilities

A person with Certificate in Deep Learning with PyTorch is responsible for accomplishing useful tasks using Convolutional Neural Networks to process spatial data such as images and using Recurrent Neural Networks to process sequential data such as texts.

Why to take this certification?

In this course, you will learn how to accomplish useful tasks using Convolutional Neural Networks to process spatial data such as images and using Recurrent Neural Networks to process sequential data such as texts.

By the end of this course, you will be able to use PyTorch proficiently in your real-world projects.

Intended Audience

Job seekers looking for employment in IT companies, IT departments of PSUs or MNCs, will find the certification of great help. Certification in Deep learning with Pytorch framework benefits Data Science professionals, students and professionals.

How It Works

Select Certification & Register
Receive a.) Online e Learning Access (LMS) b.) Hard copy – study material
Take exam online anywhere, anytime
Get certified & Increase Employability

Test Details

Duration: 60 minutes
No. of questions: 50
Maximum marks: 50, Passing marks: 25 (50%).
There is NO negative marking in this module.
Online exam.

Benefits of Certification

Government certification
Certification valid for life
Lifelong e-learning access
Free Practice Tests
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Content Details

This exam has following objectives –

Module 1

GETTING STARTED WITH PYTORCH

The Course Overview
Introduction to PyTorch
Installing PyTorch on Linux and Windows
Installing CUDA
Introduction to Tensors and Variables
Working with PyTorch and NumPy
Working with PyTorch and GPU
Handling Datasets in PyTorch
Deep Learning Using PyTorch

TRAINING YOUR FIRST NEURAL NETWORK

Building a Simple Neural Network
Loss Functions in PyTorch
Optimizers in PyTorch
Training the Neural Network
Saving and Loading a Trained Neural Network
Training the Neural Network on a GPU

COMPUTER VISION – CNN FOR DIGITS RECOGNITION

Computer Vision Motivation
Convolutional Neural Networks
The Convolution Operation
Concepts – Strides, Padding, and Pooling
Loading and Using MNIST Dataset
Building the Model
Training and Testing

SEQUENCE MODELS – RNN FOR TEXT GENERATION

Sequence Models Motivation
Word Embedding
Recurrent Neural Networks
Building a Text Generation Model in PyTorch
Training and Testing

AUTOENCODER – DENOISING IMAGES

Autoencoders Motivation
How Autoencoders Work
Types of Autoencoders
Building Denoising Autoencoder Using PyTorch
Training and Testing

REINFORCEMENT LEARNING – BALANCE CARTPOLE USING DQN

Reinforcement Learning Motivation
Reinforcement Learning Concepts
DQN, Experience Replay
The OpenAI Gym Environment
Building the Cartpole Agent Using DQN
Training and Testing

Module 2

FIRST STOP: A QUICK INTRODUCTION TO PYTORCH

The Course Overview
What Makes PyTorch Special?
Installing PyTorch

SLEEPING UNDER THE STARS: IT’S A BIRD…IT’S A PLANE…IT’S A CNN?

Problem: Detect a Specific Type of Object in an Image
Quick Win: Using a Pretrained AlexNet Model for Beaver Detection
Getting and Preparing Image Data
Building, Training, and Testing Your Model
Using Your Model to Detect Beavers and What’s Next?

GOING ABROAD: LANGUAGE DETECTION FOR FUN AND PROFIT WITH RNN

Problem: Recognize the Language of a Specific Text
Understanding and Preparing Language Data
Building, Training, and Testing Your Model for Language Detection
Using Your Model to Detect Languages and What’s Next?

MAKING FRIENDS: LOST IN TRANSLATION WITH LSTM

Problem: Translate a Specific Text from One Language to Another
Understanding and Preparing Dataset for Language Translation
Building, Training, and Testing Your Models for Language Translation
Using Your Models for Language Translation

GETTING SOME CULTURE: BECOMING A DEEP NEURAL PICASSO WITH DNN

Problem: Extract Key Style Features from One Image and Use It on Another One
Preparing Images for Style Transfer
Building and Training Style Transfer Model

Preparation Guide for Certificate in Deep Learning with PyTorch

There are numerous resources that can be used for preparation. But cracking the certification becomes difficult when the set of resources chosen is not apt. You should be very careful while choosing the resources as they will determine actually how well you will pass the exam. let us have a look at handful of resources.

Certificate in Deep Learning with PyTorch study guide

Step 1 – Review the Exam Objectives

The first and foremost thing before you start preparing is to get well versed with the objectives of the exam. Knowing in detail about the exam objectives will let you understand the way through which you will prepare for the exam and then help to pass that with the flying colors. The exam revolves around the following objectives –

GETTING STARTED WITH PYTORCH
TRAINING YOUR FIRST NEURAL NETWORK
COMPUTER VISION – CNN FOR DIGITS RECOGNITION
SEQUENCE MODELS – RNN FOR TEXT GENERATION
AUTOENCODER – DENOISING IMAGES
REINFORCEMENT LEARNING – BALANCE CARTPOLE USING DQN
FIRST STOP: A QUICK INTRODUCTION TO PYTORCH
SLEEPING UNDER THE STARS: IT’S A BIRD…IT’S A PLANE…IT’S A CNN?
GOING ABROAD: LANGUAGE DETECTION FOR FUN AND PROFIT WITH RNN
MAKING FRIENDS: LOST IN TRANSLATION WITH LSTM
GETTING SOME CULTURE: BECOMING A DEEP NEURAL PICASSO WITH DNN

Refer – Certificate in Deep Learning with PyTorch brochure

Step 2 – Hitting the books

You can refer to as many books as you want and can get them from bookstores or libraries. Books are the most valuable and reliable source for collecting the information relating to the theoretical concepts of the syllabus. Make sure that the books you select has all the necessary concepts that will be asked in the exam. also, the book should offer maximum practice exercises that will help to understand better and learn the things for a long time. Some books that you can refer are –

Deep Learning With Pytorch
Pytorch Deep Learning Hands-on

Step 3 – E-Learning and Study Materials

Learning for the exam can be fun if you have right set of resources matching your way of studying. Vskills offers you its E-Learning Study Material to supplement your learning experience and exam preparation. This online learning material is available for lifetime and is updated regularly. You can also get the hardcopy for this material, so, you can prefer either way in which you are comfortable.

Refer – Certificate in Deep Learning with PyTorch Sample Chapter

Step 4 – Evaluate yourself with Practice Tests

Practices makes a man perfect. You can also find the problems you are facing in your strategy. We all are quite well versed with this saying and also with the truth in this. Practice papers and test series help you in identifying the loopholes in the preparation. Practicing as much as you can will help in identifying various parts of the syllabus that need more attention and that are fully prepared. This is the best way to know your level of preparation. Start practicing now!