Certificate in Deep Learning with Python

Deep learning with python is a new superpower which will let you build AI systems that just weren’t possible a few years ago. It’s time to utilize intelligent automation to help your business grow, keep organized, and stay on top of the competition. Getting certifications to make you a preferable candidate for the job as well as increases your importance. They help in showing your commitment towards your aim and dedication towards your work and organization.

To stand out in the crowd you need to have somewhat different skills than others just like these certifications. Certifications surely help you to stand out from the crowd and improve your chances to get ahead of others. Let us get into details of these certifications.

Roles and Responsibilities

A Certificate in Deep Learning with Python makes you responsible for enabling numerous exciting applications in speech recognition, music synthesis, machine translation, natural language understanding, and many others. AI is transforming multiple industries.

Why to take this certification?

Deep Learning is currently enabling numerous exciting applications in speech recognition, music synthesis, machine translation, natural language understanding, and many others. AI is transforming multiple industries. After finishing this course, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.

Intended Audience

Job seekers looking for employment in various IT companies, PSUs or MNCs. Certification in Deep learning with Python framework benefits Data Science professionals, students and professionals across various Industries. IT companies, MNCs, Consultancies hire Pytorch professionals for Data Science related opportunities. Companies employing Data Science include Capgemini, JP Morgan Chase, TCS, Wipro, Zensar, Accenture, Infor etc.

Benefits of Certification

Government certification
Certification valid for life
Lifelong e-learning access
Free Practice Tests
Get tagged as ‘Vskills Certified’ On Monsterindia.com
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Certificate in Deep Learning with Python

Certification Process

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.

Content Outline

This certification has the following objectives –

Module 1

UNDERSTANDING DEEP LEARNING

The Course Overview
A Brief History of Deep Learning
Deep Learning Today
Tools, Requirements, and Setup

BUILDING THE BASIC BLOCKS OF MACHINE LEARNING

Exploring Supervised Learning
Representational Learning and Feature Engineering
Linear Regression
The Perceptron

DIVING INTO DEEP NEURAL NETWORKS

Feedforward Networks
Backpropagation
Neural Networks from Scratch
Overfitting and Regularization

DISCOVERING CONVOLUTIONAL NEURAL NETWORKS (CNNS)

Understanding CNNs
Implementing a CNN
Deep CNNs

USING CNNS TO SOLVE INCREASINGLY COMPLEX TASKS

Very Deep CNNs
Batch Normalization
Fine-Tuning

LEARNING ABOUT DETECTION AND SEGMENTATION

Semantic Segmentation
Fully Convolutional Networks

EXPLORING RECURRENT NEURAL NETWORKS

Recurrent Neural Networks
LSTM and Advancements

OBJECT DETECTION USING CNNS

Building a CNN to Detect General Images
Training and Deploying on a Cluster

MOVING FORWARD WITH DEEP LEARNING AND AI

Comparison of DL Frameworks
Exciting Areas for Upcoming Research

Module 2

GETTING STARTED WITH DEEP LEARNING

The Course Overview
Fundamentals of Neural Networks
Training Deep Neural Networks
Using Forward Propagation, Backprop, and SGD
Logistic Regression with a Neural Network Mindset
Convolutional Neural Network Handwriting Recognition

DEEP MODELS WITH MXNET AND TENSORFLOW

Working with MxNet and Gluon
Defining and Training Neural Networks in MxNet/Gluon
Working with TensorFlow and Keras
Defining and Training Neural Networks in Keras/TensorFlow
Comparing the Two Frameworks
Mini Project – CIFAR Classification

IMPROVING DEEP NEURAL NETWORKS

Weight Initialization for Deep Networks
Regularization and Dropout
Normalizing and Vanishing/Exploding Gradients
Mini Project – SIGNS Dataset

OPTIMIZATION ALGORITHMS

Understanding Stochastic Gradient Descent
Adaptive Learning Algorithms – RMSProp and Adam
Mini Project – Language Modeling

HYPERPARAMETER TUNING

Hyperparameters
Tuning Hyperparameters – Grid Search
Tuning Hyperparameters – Random Search
Mini Project -Music Synthesis

Preparation Guide for Certificate in Deep Learning with Python

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 Python 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 –

UNDERSTANDING DEEP LEARNING
BUILDING THE BASIC BLOCKS OF MACHINE LEARNING
DIVING INTO DEEP NEURAL NETWORKS
DISCOVERING CONVOLUTIONAL NEURAL NETWORKS (CNNS)
USING CNNS TO SOLVE INCREASINGLY COMPLEX TASKS
LEARNING ABOUT DETECTION AND SEGMENTATION
EXPLORING RECURRENT NEURAL NETWORKS
OBJECT DETECTION USING CNNS
MOVING FORWARD WITH DEEP LEARNING AND AI
GETTING STARTED WITH DEEP LEARNING
DEEP MODELS WITH MXNET AND TENSORFLOW
IMPROVING DEEP NEURAL NETWORKS
OPTIMIZATION ALGORITHMS
HYPERPARAMETER TUNING

Refer – Certificate in Deep Learning with Python 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 Python
Deep Learning With Python

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 Python 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!