Introduction to Deep Learning with NVIDIA GPUs: Certification by iTrain Malaysia
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Introduction to Deep Learning with NVIDIA GPUs

3-Day Instructor-Led Course | HRDF Claimable!

In Partnership With

Deep Learning Course Overview

Organizations are using deep learning and AI at every stage of growth, from start-ups to Fortune 500s. Deep learning, the fastest growing field in AI, is empowering immense progress in all kinds of emerging markets and will be instrumental in ways we haven’t even imagined. Today’s advanced deep neural networks use algorithms, big data, and the computational power of the GPU to change this dynamic. Machines are now able to learn at the speed, accuracy and scale that are driving true artificial intelligence and AI Computing. Learn the latest techniques on how to design, train, and deploy neural network-powered machine learning in your applications. You’ll explore widely used open- source frameworks and NVIDIA’s latest GPU-accelerated deep learning platforms.

Learning Outcomes:

Introduction to Deep Learning (DL) • Getting Started with Deep Learning • Approaches to Object Detection using DIGITS • Deep Learning for Image Segmentation • Deep Learning Network Deployment • Medical Image Segmentation using DIGITS • Introduction to Deep Learning with R and MXNET • Introduction to RNNs • Signal Processing using DIGITS • Deep Learning with Electronic Health Record

Who Should Attend & Prerequisites:

Who Should Attend: Anyone interested to learn more about Deep Learning, or kickstart a career as a Data Scientist. This includes Students, Data Analysts, Developers, Business Owners, Engineers, Product Architects, Entrepreneurs or any individual who wishes to leverage on powerful Deep Learning tools to add value, wherever they are.

Prerequisites: Students must have technical knowledge in R and Python, understand basic Data Science, Machine Learning and AI algorithms, familiarity with basic programming fundamentals such as functions and variables


Course Outline


Day 1

  • Deep Learning as a branch of AI
  • Neural networks and their history and relationship to neurons
  • Creating a neural network in Python

  • Understanding the neuron and neuroscience
  • The activation function (utility function or loss function)
  • How do NN’s work?
  • How do NN’s learn?
  • Gradient descent
  • Stochastic Gradient descent
  • Backpropagation

  • Getting the python libraries
  • Constructing ANN
  • Using the bank customer churn dataset
  • Predicting if customer will leave or not

  • Evaluating the ANN
  • Improving the ANN
  • Tuning the ANN

  • Participants will be asked to build the ANN from the previous exercise
  • Participants will be asked to improve the accuracy of their ANN

  • What are CNN’s?
  • Convolution operation
  • ReLU Layer
  • Pooling
  • Flattening
  • Full Connection
  • Softmax and Cross-entropy

  • Getting the python libraries
  • Constructing a CNN
  • Using the Image classification dataset
  • Predicting the class of an image

Day 2

  • Evaluating the CNN
  • Improving the CNN
  • Tuning the CNN

  • Participants will be asked to build the CNN from the previous exercise
  • Participants will be asked to improve the accuracy of their CNN

  • What are FCN’s?
  • Vanishing Gradient problem
  • LSTMs
  • Practical intuition
  • LSTM variations

  • Getting the python libraries
  • Constructing FCN
  • Using the stock prediction dataset
  • Predicting stock price

  • Evaluating the FCN
  • Improving the FCN
  • Tuning the FCN

  • Participants will be asked to build the FCN from the previous exercise
  • Participants will be asked to improve the accuracy of their FCN

Day 3

Duration: 8 Hours
Certification: Upon successful completion of this workshop, you will receive NVIDIA DLI Certification to prove subject matter competency and support professional career growth
Tools, libraries and frameworks: Caffe, DIGITS

Components Description
  • Course Overview
  • Getting Started with Deep Learning
Introduction to Deep Learning, situations in which it is useful, key terminology, industry trends, and challenges.
Components Description
  • The biological inspiration for Deep Neural Networks (DNNs)
  • Training DNNs with Big Data
Hands-on exercise: Training neural networks to perform image classification by harnessing the three main ingredients of deep learning: Deep Neural Networks, Big Data, and the GPU
Components Description
  • Deploying DNN Models
Hands-on exercise: Deployment of trained neural networks from their training environment into real applications
Components Description
  • Optimizing DNN Performance
  • Incorporating Object Detection
Hands-on exercise: Neural Network performance optimization and applying DNNs to object detection
Components Description
  • Summary of Key Learnings
Review of concepts and practical takeaways.
Components Description
  • Assessment Project: Train and Deploy a Deep Neural Network
Validate your learning by applying the Deep Learning application development workflow (load dataset, train and deploy model) to a new problem.
Components Description
  • Workshop Survey
  • Setting up your own GPU enabled-environment
  • Additional project ideas
Learn how to set up your GPU-enabled environment to begin work on your own projects. Get additional project ideas along with resources to get started with NVIDIA AMI on the cloud, NVIDIA-Docker and the NVIDIA DIGITS container.

“Everything about the course was great. Thanks!”

Mohd Izzudin bin Razali, Universiti Teknologi Malaysia

“Good and clear introduction to the basic operation of neural networks.”

Hoo Wan Hong, TMAS

“The trainer is very good, he knows deeply about the subject and topics and answered our questions well.”

Nur Shafiranisa binti Shaharum, Universiti Putra Malaysia



Participants will receive a Beginner Level Certificate from NVIDIA Deep Learning Institute upon completion of the 3-day programme, inclusive of participation in the 1-day NVIDIA Deep Learning Lab workshop.

You bet it is! Our Certification Body for this course is iTrain Asia Pte Ltd, the region’s top Certifications Tech Provider headquartered in Singapore, with branch offices in Malaysia and Indonesia.

This is a 3-day course at an instructor-led training centre.

Yes, participants should bring their own laptops to class as they will not be provided with one.

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