Workshop

ACS Masterclass: Deep Learning Essentials Series

This four-part series will take place across a four-week period, with each session running on a Wednesday for 2 hours. This hands-on course will involve interactive activities and outcome-based learning with a different topic addressed each session. The program must be purchased as a whole, and registrations are not available for individual sessions. These events are aimed at professionals who are looking to develop and acquire deep learning skills.

Virtual
CPD Hours: 8
Skills Level: Emerging technology monitoring (EMRG) -> Level 4

About this event

The aim of the ACS Masterclass: Deep Learning Essentials is to provide ICT professionals with actionable skills around Deep Learning. 

This thorough 4-week course is a foundational program that will take you through the essentials of deep learning and prepare you to participate in the development of leading-edge AI technology. 
One year of coding (any language) experience is a prerequisite. 

In the 4 sessions, you will go over both theories and demos of the main aspects of deep learning, including Convolutional Neutral Nets (CNNs), Embeddings, and Recurring Neutrals Nets (RNNs).

AI is transforming many industries and the latest Digital Pulse and the Technology Impacts On The Australian Workforce reports ranked Deep Learning as one of the top required skills in the ICT industry in the coming years. 

The ACS Masterclass: Deep Learning Essentials Series provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career. 
All workshops will be delivered by our professional expert facilitator, Sachin Abeywardana, Senior Machine Learning Engineer at Canva.

Don't miss the opportunity to learn from his extensive experience as a facilitator and as an engineer in the ultimate Australian start-up, Canva. 
 Sachin
Breakdown of the course:

Session 1 - Wed 28 July:
Introduction to Deep Learning
  • Theory: Stochastic gradient descent
  • Demo: Financial News Sentiment Classification
  • Theory: Deep Neural Nets/ Feed-Forward Networks
  • Demo: Fitting to toy problem
Session 2 - Wed 4 August:
Introduction to Convolutional Neural Nets:
  • Theory: More activation functions (softmax)
  • Demo: MNIST classification
  • Theory: Intro to CNNs
  • Demo: MNIST with CNN + MaxPool
  • Time permitting: Theory: Batch Norm + Dropout + Strides
Session 3 - Wed 11 August:
Introduction to Embeddings
  • Demo: Word Embeddings (skip-gram)
  • Practical: Word Embeddings (Continuous Bag of Words)
Session 4 - Wed 18 August:
Recurrent Neural Nets
  • Theory: RNNs + LSTMs
  • Demo: Fake News Classifier
  • Practical: Financial News Sentiment Classification
  • Time permitting: Theory: Stacking RNNs
Please allow up to 1 week for CPD hours to be allocated to your membership profile.

The price of the course includes the 4 sessions

Speakers

Facilitator
Sachin Abeywardana
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