SMU ACADEMY

PROFESSIONAL

Copyright © 2020 Singapore Management University. All Rights Reserved.

OVERVIEW

With more than half the world’s data being generated in the decade, its availability becomes both a boon and bane as we are confronted with large datasets that can hardly

This programme explores ways to handle Big Data with Dask through parallelisation and distributed computing. Participants will get to leverage their understanding of Numpy and Pandas and utilise corresponding methods and functions provided by the Dask package to handle big data.

TOPICS / STRUCTURE

• Learn to process large big datasets using parallel and distributed computing with Dask

• Use Dask Dataframes to capture large amounts of data in tabular form

• Learn to provide Amazon Web Services (AWS) EC2 Virtual Machines for Distributed Computing with Dask

LEARNING OBJECTIVES

• Visualise large datasets using Datashader

• Use the Dask-ML API to perform Linear Regression on a big dataset

Understanding Big Data with Cloud ComputingAdvanced Certificate in Applied Data Analytics

Registration

For enquiries, please contact Gilbert at gilbertong@smu.edu.sg

Programme Schedule

Each module is conducted over 2 weekday evenings and 1 full Saturday

TRAINER PROFILE

Ian holds a Master of Science in Management Science & Engineering from Stanford University and a Bachelor of Arts in Mathematics & Economics from the University of California, Berkeley. His love for programming began when he dived into the study of Optimisation Algorithms and Machine Learning as a graduate student at Stanford. As a quant risk manager at Barclays, Ian got to further sharpen his craft programming risk engines and

numerical library (FORTRAN).

As founder of SG Code Campus, Ian has designed and taught comprehensive curricula in Python and JavaScript, as well as Data Science and Machine Learning to more advanced students. Apart from teaching advanced topics in computer science to senior

can better teach and engage our learners through a variety of modalities as well as technologies.

Ian Choo

Founder, SG Code Campus

Cheng Wei Lee

Senior Data Scientist and Instructor, SG Code Campus

Cheng Wei holds a Master of Science in Statistics from Imperial College London. He is an avid Machine Learning practitioner. As a former Data Scientist at PwC, he applied his expertise to building smart applications in areas as diverse as health care, language

multiple technology stack development such as Microsoft SQL server, Matlab and Google Cloud Platform (GCP), to name a few.

As a principal instructor and developer at SG Code Campus, Cheng Wei has designed and taught comprehensive curricula in Python, C++ and JavaScript. He also developed and taught Machine

Fee

SGD1712.00 incl. GST As low as SGD193.60 incl. GST (for Singapore Citizens / PRs) after maximum funding

Who Should Attend

• Data science professionals seeking to apply Python to data problems e.g. business intelligence analysts, data engineers

• Managers looking into costs and performance hurdles in predictive modelling

• Anyone with an interest in learning about the advanced data analysis techniques and applying it in practice

• Experience in Python programming (equivalent to that attained in

in Python Programming programme) is essential.

Ian holds a Master of Science in Management Science & Engineering from Stanford University and a Bachelor of Arts in Applied Mathematics & Economics from the University of California, Berkeley. His love for computing began when he dived into the study of Computational Engineering and Machine Learning over three years as a graduate student at Stanford. After graduating, he took on a role as a quant risk manager at Barclays Investment Bank, where he got to further sharpen his craft data-munging reams of financial data, programming risk engines and coding up financial models in Python, R, VB.NET and the NAG numerical library (FORTRAN).

As the founder of SG Code Campus, Ian has designed and taught curricula in Web and Mobile programming, Cloud Computing, Data Science and Machine Learning to a variety of audiences including kids, youths, Polytechnic, University students, as well as working professionals. He often spends his days figuring out how SG Code Campus can better teach and engage a plurality of learners through a different teaching approaches and course formats.