Data Analytics Begins With Me



Course Reference No: CRS-N-0046106

Courses_Calendar_83x95

Course Objectives

Basic Data Analytics taught with a simple but powerful graphical user interface (“GUI”) drag-and-drop tool targeted at business analysts requiring more sophisticated capabilities than what a spreadsheet can offer.

Understanding and using data is increasingly an important part of an executive function. Whether you are a business analyst, customer service officer, physiotherapist, procurement officer or HR executive – the ability to understand where potential data is coming from, and to properly collect, clean, and then analyse it, will be an important and critical skill.

This course provides the participant with the knowledge and skills to participate in the organisation’s data analytics process without any coding requirements.

We will cover basic concepts of data analysis, processing of data, and visualisation of raw data and processed data to gain insights, followed by building simple models for classification and prediction.

The participant will also learn to use the free and open source data analytics tool – Orange – a powerful and popular Python-based data analytics tool. Orange has a point-click-drag-and-drop GUI, no programming is required.

At the end of the course, participants would be able to:

  • Understand the data analytics end-to-end workflow
  • Identify where the potential sources of data can come from
  • Use a GUI-based analytics tool to process, clean and prepare data for analysis
  • Perform basic analysis such as classification and predictions
  • Select the most appropriate analytics model to use for a specific task

Outline

  • Painting the big picture – Big Data and Data Analytics
  • The Data Analytics Process
  • Introduction to Machine Learning
  • A Primer on Artificial Intelligence
  • Introduction to Statistical Concepts
  • Hands-on
    • Data Cleaning Concepts/Techniques
    • Analytics with Orange Workshop
    • Exploratory Data Analysis and Linear Regression-Predicting HDB Prices
  • Logistic Regression-Predicting HDB Prices

Tools

Orange

Pre-requisites

Experienced with using Excel in manipulating data, charting and basic analysis. No programming experience required.

Who Should Attend

Business Analysts, Customer Service Managers, Physiotherapists, Procurement Officers, HR Executives and any professionals, managers and executives.

Mode of Training

Online Workshop using Zoom

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 and Machine Learning. 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 University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Vision, Data Science, and IoT.

He has taught the Data Science courses, including Data Mining, Advanced Data Mining, AI, and Neural Networks since 2008 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, ELearning, and E-Learning for workplaces since 2007.

Dr. Monajemi was the data science advisor of MSC (Mobarakeh Steel Complex,the largest in the country). Moreover, he has registered three patents and 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 analysis of the effectiveness of research projects in enterprises, and data mining to extract the common patterns among the unsuccessful BSc students. He is experienced in different subdomains of data science from theory to practice, including data mining and pattern recognition.
Speaker

Dr Ben Lee

Dr Ben Lee is a Senior lecturer in Data Analytics and Visualization with the School of Continuing and Lifelong Education (SCALE) at NUS. 

He has over 30 years’ experience in IT and information management.  His career roles span CIO, Director of IT services, Strategy and Planning, Project management, Applications development, Systems engineering, Data management and IT outsourcing.  Business and Industry experiences include electronic business development, implementation of business process re-engineering and functional support for Finance, HR, Manufacturing, Retail and mergers/acquisitions in Oil and Gas. 

He has been actively involved in data and information management since 2000 and has successfully implemented global projects covering data warehouses, management information systems, data analytics and e-business systems.  In those projects, Ben had applied data analytics to improve resource management and sales profitability with better understanding of customers, products and services. 

Ben has been teaching information & data management and business analytics classes since 2016. He holds a Doctorate in Business Administration from the University of Western Australia. He also has Masters in Business Research and Physics and a Bachelors in Law. He has a strong interest and passion for data analytics, visualization and e-business. 
Speaker

Dr Julian Lin

Dr. Julian Lin is a Senior Lecturer in Cybersecurity and Data Analytics with School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS).  He is a Certified Information Systems Security Professional (CISSP) and has a dozen other IT certifications. Recently, Julian was ranked 6th in the Microsoft Data Science Capstone Competition. He has been conducting text-analytics research since 2010 and teaching  visualization since 2007. 

During his IT consultancy career, he oversaw the application and infrastructure projects in Amoseas,  Mannesmann Dematic Colby (Sydney), Alcatel (Sydney), and the University of New South Wales (UNSW) Faculty of Commerce and Economics. Julian has taught programming and data management for business at UNSW.  At NUS, he had mentored student software development projects and taught visual communications, designing new media content, and research methods. He was given a  teaching award for visualization class and research award for user acceptance research in NUS. 

Julian obtained a PhD degree in Information Systems from NUS.  He was a recipient of two scholarships from the Overseas Chinese Association in Taiwan while pursuing his Bachelor degree and another scholarship while pursuing a Master degree in Australia.
Speaker

Dr Edmund Low

Dr Edmund Low is a lecturer with the University Scholars Programme (USP) at the National University of Singapore. He teaches courses on engineering, statistical methods, data science and analytics. He currently heads the quantitative reasoning domain, and is also director of the Quantitative Reasoning Centre, at USP. He has organised / co-organised programming workshops and data hackathon for students. As an educator, Edmund has received both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. He has more than 13 years of academic and professional experience in the use of computational modelling and data-driven tools, applying them to solve problems in public health, water resource management and air quality in buildings. Edmund holds a PhD in Environmental Engineering from Yale University.

Speaker

Dr Guo Lei

Dr Guo Lei is an active educator and researcher in data science, behavioural study and design thinking, with extensive experience in delivering practice-based learning programmes and applied research projects with successful results.

Starting her career in Singapore as a marketing practitioner, Dr Guo worked across manufacturing, entertainment and education industries. She was the Chief Representative in China for a Singapore listed company. She was also responsible for setting up Shanghai Office and promoting executive education programmes for NUS Business School in Greater China market.

With the aspiration of bridging the gap between research and practice, Dr Guo pursued her PhD in the UK, where she worked on large-scale research projects with Cambridge University Service Alliance, BAE Systems and China Mobile.

Dr Guo returned to Singapore and joined NUS as a faculty member in 2011. She has particular experience in tackling complex challenges through applied research and education. She was the Principal Investigator for a series of research projects to inform better public transport policy decisions. She consults local and overseas corporate clients on data analytics, user experience design and service innovation. Dr Guo teaches executive programmes of Data Analytics and Design Thinking at NUS. She has a passion for engaging and inspiring working professionals at all levels by applying the theory to real world business applications.

Dr Guo holds a PhD in Marketing from University of Exeter, an MBA from University of Adelaide and a BA in Literature from Beijing Normal University.

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

01 Sep 2020
06 Oct 2020(Online)
12 Nov 2020(Online)
14 Dec 2020 (Online)

DURATION

1 Day
9.00am to 5.30pm

VENUE

National University of Singapore
University Town

Fees & Fundings

International Participants

S$909.50

Incl. GST

Singapore Citizens (39 yrs old or younger)  or Singapore PRs

S$272.85

Incl. GST

Singapore Citizens
(40 yrs or older)

S$102.85

Incl. GST

Enhanced Training Support for SMEs

S$102.85

Incl. GST

International
Participant
Singapore Citizen1
39 years old or younger
Singapore Citizen1
40 years or older eligible for MCES2
Singapore PRs Enhanced Training
Support for SMEs3
Full Programme Fee S$850.00 S$850.00  S$850.00  S$850.00  S$850.00
SkillsFuture Funding
Eligible for Claim Period
(19 Oct 17 to 30 Sep 2020)
- (S$595.00) (S$595.00)   (S$595.00)  (S$595.00)
Nett Programme Fee S$850.00  S$255.00 S$255.00  S$255.00  S$255.00
7% GST on Nett
Programme Fee
S$59.50 S$17.85 S$17.85  S$17.85  S$17.85
Total Nett Programme
Fee Payable, Incl. GST
S$909.50 S$272.85 S$272.85   S$272.85  S$272.85
Less Additional Funding if
Eligible Under Various Scheme
- - (S$170.00) - (S$170.00)
Total Nett Programme Fee, Incl. GST,
after additional funding from the various funding schemes
S$909.50 S$272.85 S$102.85 S$272.85 S$102.85

  1. All self-sponsored Singaporeans aged 25 and above can use their $500 SkillsFuture Credit to pay for the programme. Visit http://www.skillsfuture.sg/credit to select the programme. 
  2. Mid-Career Enhanced Subsidy (MCES) - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the programme fee. 
  3. Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the programme fee. For more information, visit http://www.ssg.gov.sg/programmes-and-initiatives/training/enhanced-training-support-for-smes.html?_ga=2.154478072.1748789781.1519700056-512306731.1519700056
  4. Eligible organisations (excluding government entities) may apply for the absentee payroll funding via SkillsConnect at www.skillsconnect.gov.sg for Singaporean/permanent resident participants attending the programme during working hours. The absentee payroll funding is computed at 80% of hourly basic salary capped at $4.50 per hour or $7.50 per hour for SME. For more information, visit https://www.skillsconnect.gov.sg/sop/portal/e-Services/For%20Employers/AbsenteePayroll.jsp
  5. Eligible individuals may apply for training allowance capped at $6/hr under the WSS scheme, visit- https://www.wsg.gov.sg/programmes-and-initiatives/workfare-skills-support-scheme-individuals.html for more information on WSS.
  6. NTUC Training Fund (SEPs) – All self-employed (i.e. freelancers and sole-proprietors-with-no-employee) Singaporeans and Permanent Residents are eligible to apply for the NTUC Training Fund (SEPs) from NTUC’s Employment and Employability Institute (e2i). Click here for more information.
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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07 August 2020