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3-Day Instructor-Led Course | HRDF Claimable!

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Deep Learning Course Overview

Deep Learning is the fastest-growing field in Machine Learning and highly crucial for Artificial Intelligence, using many-layered Deep Neural Networks (DNNs) to make sense of data and enable many practical machine assists. This course introduces students to Deep Learning as a subject within advanced Artificial Intelligence and provides several real-life problem sets that can be solved using Deep Learning neural networks.

Learning Objectives:

Understand the intuition behind Artificial Neural Networks • Understand the intuition behind Convolutional Neural Networks • Apply Artificial Neural Networks in practice • Apply Convolutional Neural Networks in practice • Understand the intuition behind Recurrent Neural Networks • Apply Recurrent Neural Networks in practice

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 knowledge in basic high-school mathematics

Required Software: Anaconda for Python (version 3.x) Optionally Sublime Text

Course Outline

WHAT YOU’LL LEARN: DAILY SCHEDULE

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

Day 2

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

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 RNN’s?
Vanishing Gradient problem
LSTMs
Practical intuition
LSTM variations

Getting the python libraries
Constructing RNN
Using the stock prediction dataset
Predicting stock price

Evaluating the RNN
Improving the RNN
Tuning the RNN

Participants will be asked to build the RNNfrom the previous exercise
Participants will be asked to improve the accuracy of their RNN

Day 3

Word representation
Word embeddings
Word2Vec
Sentiment Classification

Picking the next word or sentence
Beam Search
What is an Attention Model?
Speech Recognition
Trigger Word Detection
Working with Advanced NLP Models - GPT - 3

Participants will be asked to use attention-based sequence models and evaluate their effectiveness
Participants will be asked to improve the accuracy of their attention-based models

Getting the Python libraries
Constructing the DQN
Working with OpenAI Gym
Optimising a DQN

What is reinforcement learning?
K-Armed Bandit Problem - exploration / exploitation trade-off
Markov Processes
Policies and value functions
Dynamic programming
Q learning and Deep Q learning

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

Evaluating the DQN
Improving the DQN
Tuning the DQN

“

“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

FAQ

YOUR QUESTIONS, ANSWERED.

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.