Data Science & Artificial Intelligence for Senior Executives

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Overview

Data is the new oil. Understanding how data and machine learning is allowing organisations to understand customers and how the revival of artificial intelligence with techniques like deep learning are rapidly changing the competitive landscape and ecosystem is key to remaining relevant.

In this programme, the instructors will share their experiences in building cloud, big data and analytics companies and projects over the last two decades.

You will gain insights into how an organisation’s data can be ingested by leveraging current best practices and why leading data companies such as Google, Facebook are created and/or depending on open source tools such as Hadoop, Spark, R, and Python.

During this course, there will be opportunities to explore and discuss and remove the myth and hype around big data, data analytics, machine learning and artificial intelligence.

Outline

  • Overview of Big Data Analytics, Data Science, Machine Learning and Artificial Intelligence
  • The data analytics process, challenges and applications
  • Building your data analytics/science and engineering team

Key Benefits

At the end of the course, participants would be able to:
  • Understand the current state of the art of big data infrastructure and analytics
  • Understand whether to buy or rent data infrastructure
  • Take away a blueprint on how to build a data science team and project in order to pivot the company towards becoming a data-centric organisation.

Pre-requisites

None

Who Should Attend

CXO, Business Unit Heads, Senior Manager

Mode of Training

On-campus or Online (Live)

Speaker

Dr. Amirhassan Monajemi

 

Dr. Amirhassan Monajemi is a Senior Lecturer in AI and Data Science with the School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS). Before joining the NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science. He was born in 1968 in Isfahan, Iran. He studied towards BSc and MSc in Computer Engineering at Isfahan University of Technology (IUT), and Shiraz University respectively. He got his PhD in computer engineering, pattern recognition and image processing, from the University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Learning, Machine Vision, IoT, Data Science, and their applications.

He has taught the artificial intelligence courses, including AI, Advanced AI, Expert Systems, Decision Support Systems, Neural Networks, and Cognitive Science since 2005 at both undergraduate and postgraduate levels. He was awarded the best university teacher of the province in 2012. He also has studied Learning Management Systems, E-Learning, and E-Learning for workplaces since 2007.

Dr. Monajemi has registered a few patents in the fields of AI, Machine Vision, and Signal Processing applications, including an AI and machine vision-based driver drowsiness detection system and a low power consuming spherical robot. He also has published more than a hundred research papers in peer-reviewed, indexed journals and international conferences (IEEE, Elsevier, Springer, and so on), and supervised several Data Science, IoT, and AI industrial projects in various scales, including Isfahan intelligent traffic system delivery and testing, and red light runners detection. He is experienced in different sub-domains of Artificial Intelligence and Machine Learning, from theory to practice, including Deep Learning, Logic, and Optimization.

Speaker

Mr. Koo Ping Shung

 

Mr. Koo Ping Shung is an experienced Data Scientist with more than 13 years of relevant experience. He is also currently a Adjunct Senior Faculty with the Singapore University of Social Sciences (SUSS) and a SAS Trainer as well. To date, he has conducted over 1,600 man-hours of data science training. He is also the mentor to the trainees accepted into the IMDA-SAS BIA Programme for 5 intakes.

Ping Shung was a guest lecturer at NUS Institute of Systems Science and previously held an adjunct position in School of Information Systems, Singapore Management University.

Prior to this, he was the Analytics Practicum Manager of the Master of IT in Business (Analytics) at the Singapore Management University School of Information Systems. He managed the industrial relationships through projects and attachments. He often advised companies on the type of data analytics projects they can work on with their data and is a co-supervisor for many Masters students on their data analytics capstone projects. He was an instructor for the DBS Graduate Associate Programme for 3 years, teaching over 200 Graduate Associates on data analytics and received positive ratings. He has also trained professionals from various companies on data analytics and the use of SAS software.

Ping Shung was a facilitator for the IDA Data Science MOOC programme for 2 cohorts (over 300 professionals) and participated in Singapore's first Data Literacy Bootcamp which was co-organised by the IDA Singapore and The World Bank.

Ping Shung through his career has gathered much experience on statistical modeling, from working in the banks, supervising Masters students and doing education research. His data analytics experience range from a wide variety of business functions and industries, gathered from talking to companies or working on data analytics projects.

His strong passion in data analytics and data science can be seen through his involvement in data analytics interest groups, being a Co-founder of DataScience.Sg and former Working Committee Chairman of SAS User Group Singapore and Data Ambassador for one of the DataKind SG project. He also read widely on the different topics related to data science and artificial intelligence, keeping himself up-to-date with their development.

His research interest lies in how data science can help organisations and businesses to be more efficient and effective.

Ping Shung holds an MBA from University of Adelaide. He obtained his bachelor degree in Economics from National University of Singapore, with a minor in Computational Finance.

DATE

TBC

DURATION

0.5 Day
9.00am to 1.00pm

VENUE

National University of Singapore
University Town

All Participants

S$588.50

Incl. GST

NTUC members enjoy 50% of the unfunded course fee support for up to $250 each year for courses supported under UTAP (Union Training Assistance Programme). Terms and Conditions apply. Please visit http://skillsupgrade.ntuc.org.sg
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Registration will close 5 working days prior to programme commencement date 
 
18 November 2020