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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.

Registration End Date:

Mon, 30 Aug, 04:45 PM

  • when

  • Event Start:
    Wed, 25 Aug, 04:45 PM

    Event Finish:
    Mon, 30 Aug, 04:45 PM
  • event price

  • Member: $250.00
  • Member-Concessional: $250.00
  • Non-Member: $450.00

  • * Your price may vary on registration depending on your membership type.

The aim of the ACS Masterclass: Deep Learning Essentials is to provide ICT professionals with actionable skills around Deep Learning. <br><br>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. <br><b>One year of coding (any language) experience is a prerequisite. </b><br><br>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).<br><br>AI is transforming many industries and the latest <a href="" target="_blank">Digital Pulse</a> and the <a href="" target="_blank">Technology Impacts On The Australian Workforce</a> reports ranked Deep Learning as one of the top required skills in the ICT industry in the coming years. <br><br>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. <br>All workshops will be delivered by our professional expert facilitator, <a href="" target="_blank">Sachin Abeywardana</a>, Senior Machine Learning Engineer at Canva.<br><br>Don&#39;t miss the opportunity to learn from his extensive experience as a facilitator and as an engineer in the ultimate Australian start-up, Canva. <br> <img alt="Sachin" src=";oid=00D90000000o5NE&amp;lastMod=1620039769000"></img><br><u><b>Breakdown of the course:</b></u><br><br><i><b>Session 1 - Wed 28 July:</b></i><br>Introduction to Deep Learning <ul><li>Theory: Stochastic gradient descent</li><li>Demo: Financial News Sentiment Classification</li><li>Theory: Deep Neural Nets/ Feed-Forward Networks</li><li>Demo: Fitting to toy problem</li></ul> <i><b>Session 2 - Wed 4 August:</b></i><br>Introduction to Convolutional Neural Nets: <ul><li>Theory: More activation functions (softmax)</li><li>Demo: MNIST classification</li><li>Theory: Intro to CNNs</li><li>Demo: MNIST with CNN + MaxPool</li><li>Time permitting: Theory: Batch Norm + Dropout + Strides</li></ul> <i><b>Session 3 - Wed 11 August:</b></i><br>Introduction to Embeddings <ul><li>Demo: Word Embeddings (skip-gram)</li><li>Practical: Word Embeddings (Continuous Bag of Words)</li></ul> <i><b>Session 4 - Wed 18 August:</b></i><br>Recurrent Neural Nets <ul><li>Theory: RNNs + LSTMs</li><li>Demo: Fake News Classifier</li><li>Practical: Financial News Sentiment Classification</li><li>Time permitting: Theory: Stacking RNNs</li></ul> <u><b>Please allow up to 1 week for CPD hours to be allocated to your membership profile.</b></u><br><br>The price of the course includes the 4 sessions

Contact Details

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Emerging technology monitoring (EMRG) -> Level 4


Sachin Abeywardana

Sachin Abeywardana

Sachin Abeywardana undertook a PhD in Bayesian Machine learning and has since worked as a data scientist/ machine learning engineer. Sachin is currently working on a program to integrate deep learning over traditional statistical methods for a sports betting company.

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ACS Masterclass: Deep Learning Essentials Series

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  • ACS reserves the right to change the program at any time. Every effort will be made to ensure a program of equivalent standard and members are updated with changes.
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