Certificate in Deep Learning with TensorFlow

Presently, every IT enthusiast wants to excel as deep learning field is fetching high salaries and is expected to grow at a faster pace in future. Deep Learning with TensorFlow uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation on large volumes of data in order to make decisions about high dimensional data. There are many companies which trust google cloud or other companies for smarter business solutions and functionalities.

The industry is growing at a very fast pace and becoming all the more difficult to predict. But, together with technological changes and advancement, there is an ever-rising competition. Indeed you have to put a ton of extra efforts in order to grab the spotlight. So let’s look into details of for getting into this field and available learning resources to prepare you better.

Roles and Responsibilities

Certificate in Deep Learning with TensorFlow will enable you to design and train your deep learning models and scale them out for larger datasets and complex neural network architectures on multiple GPUs using Google Cloud ML Engine.

Why to take this certification?

In this certification course, You will learn how to design and train your deep learning models and scale them out for larger datasets and complex neural network architectures on multiple GPUs using Google Cloud ML Engine.

You’ll also learn distributed techniques such as how parallelism and distribution work using low-level TensorFlow and high-level TensorFlow APIs and Keras.

Intended Audience

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

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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Course Outline

this exam has following objectives –

Module 1

INSTALLATION

The Course Overview
Installation

KERAS INTRODUCTION

Introduction
Keras Backends
Design and Compile a Model
Model Training, Evaluation, and Prediction
Training with Data Augmentation
Training with Transfer Learning and Data Augmentation

SCALING DEEP LEARNING USING KERAS AND TENSORFLOW

Introduction to TensorFlow
Introduction to TensorBoard
Types of Parallelism in Deep Learning – Synchronous and Asynchronous
Distributed TensorFlow
Configuring Keras to use TensorFlow for Distributed Problems

TRAINING, TUNING, AND SERVING OUR MODEL IN THE CLOUD

Introduction
Introduction to Google Cloud Machine Learning Engine
Datasets, Feature Columns, and Estimators
Representing Data in TensorFlow
Quick Dive into TensorFlow Estimators
Creating Data Input Pipelines
Setting Up Our Estimator
Packaging Our Model
Training with Google Cloud ML Engine
Hyperparameter Tuning in the Cloud
Deploying Our Model for Prediction
Creating Our Prediction API
Wrapping Up
Course Summary

Module 2

SETTING UP THE DEEP LEARNING PLAYGROUND

The Course Overview
TensorFlow for Building Deep Learning Models
Basic Syntaxes, Function Optimization, Variables, and Placeholders
TensorBoard for Visualization

TRAINING DEEP FEED-FORWARD NEURAL NETWORKS WITH TENSORFLOW

Start by Loading the Imported Dataset
Building the Layers of the Neural Network in TensorFlow
Optimizing the Softmax Cross Entropy Function
Using DNN Predicting Whether Breast Cancer Cells Are Benign or Not

APPLYING CNN ON TWO REAL DATASETS

Importing the Two Datasets Using TensorFlow and Sklearn API
Writing the TensorFlow Code to Add Convolutional and Pooling Layers
Using tf.train.AdamOptimizer API to Optimize CNN
Implementing CNN to Create a Face Recognition System

EXERCISE RNN TO SOLVE TWO TIME SERIES PROBLEMS

Understanding the RNN and the Need for LSTM
Implementing RNN
Monthly Riverflow Prediction of Turtle River in Ontario
Implement LSTM Project to Predict Decimal Number of Given Binary Representation

USING AUTOENCODERS TO EFFICIENTLY REPRESENT DATA

Encoder and Decoder for Efficient Data Representation
TensorFlow Code Using Linear Autoencoder to Perform PCA on a 4D Dataset
Using Stacked Autoencoders for Representation on MNIST Dataset
Build a Deep Autoencoder to Reduce Latent Space of LFW Face Dataset

GENERATIVE ADVERSARIAL NETWORKS FOR CREATING SYNTHETIC DATASET

Generative Adversarial Networks for Creating Synthetic Dataset
Downloading and Setting Up the (Microsoft Research Asia) Geolife Project Dataset
Coding the Generator and Discriminator Using TensorFlow
Training GANs to Create Synthetic GPS Based Trajectories

Preparatory Guide for Certificate in Deep Learning with TensorFlow

There are unlimited resources for preparation that you can use. Cracking this exam can be difficult for the first time. But with the right set of resources and hard work you can ace the exam in one go. So, you should be very careful while choosing the resources. Make sure to pick the apt resources out of the unlimited resources available, as they will determine how well will you pass the exam. Let us look at some resources that can be beneficial –

Certificate in Deep Learning with TensorFlow 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. Exam objectives let you define the framework for preparation and the path that has to be followed in order to pass with flying colors. Knowing about the objectives of the exam is very important as the whole exam is going to revolve around the objectives. This exam revolves around following objectives –

INSTALLATION
KERAS INTRODUCTION
SCALING DEEP LEARNING USING KERAS AND TENSORFLOW
TRAINING, TUNING, AND SERVING OUR MODEL IN THE CLOUD
SETTING UP THE DEEP LEARNING PLAYGROUND
TRAINING DEEP FEED-FORWARD NEURAL NETWORKS WITH TENSORFLOW
APPLYING CNN ON TWO REAL DATASETS
EXERCISE RNN TO SOLVE TWO TIME SERIES PROBLEMS
USING AUTOENCODERS TO EFFICIENTLY REPRESENT DATA
GENERATIVE ADVERSARIAL NETWORKS FOR CREATING SYNTHETIC DATASET

Refer – Certificate in Deep Learning with TensorFlow Professional Brochure

Step 2 – Hitting the books

You can choose books that are comfortable for your reading habits and which you understand well. Books are the best-valued resources and first resource that comes to our mind when we think of preparing for any exam. You can find multiple books online or can refer to libraries and bookstores. There are even fantastic books online that can be very useful in preparation. Some books that you can refer to are

Deep Learning With Tensorflow by Giancario Zaccone and Md. Rezaul Karim
Tensorflow For Deep Learning by Bharath Ramsundar & Reza Bosaigh Zadeh

Step 3 – E-Learning and Study Materials

These online classes and instructor-led courses are one of the most interactive ways of preparing the exam. Learning for the exam can be fun if you have the 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. They are prepared by the experts of the subject matter and are reliable enough. Many reliable sites provide with very nice instructors and excellent content for the preparation. As we all are habitual of classroom teaching, these classes can serve as a close substitute with the advantage of attending the class anywhere.

Step 4 – Evaluate yourself with Practice Tests

Your practice is an important determiner of how well you pass the exam. Take as many practice tests and test series as you can. They will help you in determining the level of your preparation, identify your loopholes and identify the weak portions you need to work more upon. There are so many reliable educational sites that provide with amazing content and help you in achieving excellence. Try a free practice test now!