NUS EXECUTIVE EDUCATION

Leading with Big Data Analytics & Machine Learning

Call Advisor: Monica Taneja +65 6516 8340

Email Advisor:

Duration: 5 Days

Next Run: 03 Sep - 07 Sep 2018 - Apply Now

Venue: Mochtar Riady Building, Lvl 5

Fees: SGD 5,990 (excl. GST) | 6,409 (incl. GST)

Overview

Harness the Potential of Big Data and Machine Learning Strategy

The convergence of big data and machine learning with technologies such as cloud services, sensors, ubiquitous computing, mobile devices and the Internet of Things has created vast new opportunities for business. Analytics has become a competitive and sustainable advantage for many organisations. To harness the benefits of big data and machine learning, however, business leaders face the pressing challenge of not only acquiring the right technologies and talent to analyse and interpret the data, but also to weave a data-centric mindset into the organisation’s structure and cultural fabric.

This five-day programme empowers you with the skills and confidence to tackle data-driven opportunities and accelerate data-analysis transformation in your organisation. Through lectures, case studies and discussions, you will gain real-world insights on various applications of big data analytics and machine learning, and how they can be used to fuel better decision-making within the context of your own organisation.

Leading with Big Data Analytics photo

Dates and Fees

Dates Venue Fees Excl. GST (SGD) With GST (SGD) Registration
Dates 1
03 Sep - 07 Sep 2018 Mochtar Riady Building, Lvl 5, 15 Kent Ridge Dr, Singapore 119245 5,990 6,409 Apply Now
Dates 2
03 Dec - 07 Dec 2018 Mochtar Riady Building, Lvl 5, 15 Kent Ridge Dr, Singapore 119245 5,990 6,409 Apply Now
Dates 3
04 Mar - 08 Mar 2019 Mochtar Riady Building, Lvl 5, 15 Kent Ridge Dr, Singapore 119245 5,990 6,409

NUS Accommodation Package

Participants can choose to complete their experience with the NUS Accommodation Package, which offers a conducive and convenient campus accommodation option at subsidised rates. To take advantage, select (with Accommodation Package) when applying for a programme.

  • Where: Stay at NUS Kent Vale Serviced Residences (1-bedroom apartments)
  • 6-night Stay: Check in on Sunday before the programme; check out on Saturday after the programme
  • Fees (Subject to GST): Course Fees + Accommodation = SGD 6,890

As accommodation places are limited and granted on a first-come, first-served basis, participants are advised to apply and make payment early to reserve their places.

Application Deadline

  • Participants are strongly advised to apply at least 2 months in advance
  • Applications received after the deadline will be considered based on space availability
SkillsFuture Series (SSG) Funding Scheme for Singapore Citizens or Permanent Resident (PR)

This programme is eligible for subsidies under the SkillsFuture Series. Singaporeans or PR can enjoy up to 70% or more subsidies.
Click here to find out the details.

You may take this programme as part of the Certificate of Excellence in Global Business .

Leading with Big Data Analytics & Machine Learning Programme

PROGRAMME:

Leading with Big Data Analytics & Machine Learning Programme

 

International Participants

Singapore Citizens

Singapore PRs

(2)Enhanced Training Support for SMEs

21 to 39 years old

(1)40 years old or older

(3)Eligible for WTS

>21 years old

Full Programme Fee

$5,990.00

$5,990.00

$5,990.00

$5,990.00

$5,990.00

$5,990.00

Less: SSG Grant Amount (70%)

$0.00

$4,193.00

$4,193.00

$4,193.00

$4,193.00

$4,193.00

Nett Programme Fee

$5,990.00

$1,797.00

$1,797.00

$1,797.00

$1,797.00

$1,797.00

7% GST on Nett Programme Fee

$419.30

$125.79

$125.79

$125.79

$125.79

$125.79

Total Nett Programme Fee Payable, Including GST

$6,409.30

$1,922.79

$1,922.79

$1,922.79

$1,922.79

$1,922.79

Less Additional Funding if Eligible Under Various Schemes

$0.00

$0.00

$1,198.00

$1,497.50

$0.00

$1,198.00

Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes

$6,409.30

$1,922.79

$724.79

$425.29

$1,922.79

$724.79

Skillsfuture credit (max $500)

Not applicable

$500.00

$500.00

$425.29

Not applicable

Not applicable

Balance payable, after payment by SkillsFuture Credit

$6,409.30

$1,422.79

$224.79

$0.00

$1,922.79

$724.79

1 For more information about the SkillsFuture Mid-career Enhanced Subsidy, click here.
2 For more information about the Enhanced Training Support for Small & Medium Enterprises (SMEs) Scheme, click here
3 For more information about the Workfare Training Support (WTS) scheme, click here.

*Terms and Conditions

  • ​Participants are required to complete at least 75% attendance as part of the course requirement.
  • Participants are required to complete all quizzes, surveys and feedbacks related to the course.
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Core Focus

    • Big data analytics: Technologies, policies, analytics methods
    • Big data and actionable intelligence in business: Optimisation and visualisation techniques, engaging stakeholders
    • Tech dive: Machine learning and business applications
    • Disruptive innovation: Creating new opportunities in mature markets
    • Distilling value from analytics: Developing a strategy roadmap, privacy implications, traps and myths
    • Change management: The role of data analytics, machine learning and its applications
    • Examples and cases: Risk management, HR analytics, legal analytics, consumer and retail analytics

Key Benefits

Key Benefits

  • Discover how big data and analytics can help your business accelerate innovation and achieve a competitive and sustainable edge
  • Be exposed to some of the most recent ideas and techniques in big data, machine learning and analytics
  • Learn to understand, interpret and trust the data that goes into your analytics to make business-critical decisions
  • Learn to build a data-driven culture across your organisation

Who Should Attend

Leaders and senior managers interested in building analytics capabilities to drive change within their organisation, including:

  • C-level executives
  • Senior managers in finance, marketing, supply chain, human resources or strategy

Although no prior experience in big data, machine learning and analytics is required, participants are encouraged to complete the set of pre-readings provided to prepare for the course.

Testimonials

  • Very useful in helping to clarify big data concepts, and what will be needed when I need to use and analyse big data.

    Alyssa Chen, Taiwan
    Manager
    Global Mall

    The course provided good insights into big data and data analytics, a good understanding of it is important for charting the future of companies and organizations. The quality of teaching was good and I enjoyed and benefitted from the interactions with other participants.

    Lim Neo Chian, Singapore
    Chairman
    Agri-Food & Veterinary Authority of Singapore

    I have thoroughly enjoyed attending programme on Learning with Big Data Analytic and Machine Learning. While it enhanced my knowledge on big data analytic, it also gave good insights on how it can be implemented in my business and how data is only going to grow bigger. I also enjoyed my stay at NUS campus which gave me a feeling of ‘Back to School’.

    Suresh Sodani, India
    President & Unit Head - Chemical Division, Nagda
    Grasim Industries, Aditya Birla

  • Prof Jussi Keppo and others have designed this brilliant programme to give everyone an introduction to the world of data and analytics. It also is a great way for senior leaders to understand their possible journey into effectively using data for decision making. I would recommend this programme to senior professionals and to data scientists to help them appreciate and communicate with each other.

    Kailash Nagdev, UAE
    CEO - MENA and South Asia
    Yougov

    It is a good programme for the ambitious and entrepreneurial leaders as we can learn the use of technology and software to provide added value for our organisation as well as the use of big data analytics to develop knowledge about the future of our customers' demand.

    Dian Kurniasarie, Indonesia
    Head of Research and Business Development Division
    Indonesia Central Securities Depository (KSEI)

    I have read numerous articles and books on data analytics, but it was still a different learning experience to hear experts in this field teaching us how big data analytics can improve the way we do our businesses, and we learn new insights from other participants as well.

    Mylene D. Sybingco, Philippines
    Vice President, Project Management
    Authentic American Apparel, Inc.

  • This is a fantastic programme with a lot of expert insights shared. The lecturers are extremely knowledgeable and helpful. A great thing about this program is that it bridges the participants' possible lack of prior knowledge in this field with bite sized, digestible content that can be taken away with relative ease.

    Kieran Leong, Singapore
    Head of Sales
    UOB Bank

    It provides very good information surrounding the topic from a varied group of experienced professionals, including both Academic and Industrial. I am quite impressed with the background of the faculties and speakers as they clearly came from very renowned institutions, or they were leaders in their fields of expertise.

    Heng Miao Ling, Singapore
    Customer Solutions Director
    Satair Pte Ltd

    Good for professional and senior leadership team that needs a quick view of global/regional operations that are too cumbersome for typical spreadsheets.

    Cheryl Ong, Singapore
    Associate Director, Talent Acquisition Ernst & Young Solutions LLP

  • Suitable for emerging or early adopters of data analytics. The programme provides quick and rich insights on big data analytics. Big data is not just about having more data. It is about harnessing the right big data to answer your key strategic business questions! Thank you!

    Nancy Tan, Singapore
    Director, Academic Affairs
    Ngee Ann Polytechnic

    Come with an open mind to appreciate how big data can help navigate your company.

    Cheang Chee Kit, Singapore
    Vice President
    PSA International

Faculty

Programme Director
Jussi Keppo

Jussi Keppo

Associate Professor and Co-Director of Business Analytics Center

» View CV

Jussi teaches risk management and analytics courses, and directs analytics executive education programmes at NUS Business School. He is also Co-Director of NUS Business Analytics Center. Previously, he taught at the University of Michigan. He has several publications in the top-tier journals such as Journal of Economic Theory, Review of Economic Studies, Management Science, Operations Research, and Journal of Business on topics such as investment analysis, banking regulation, learning, and strategic incentives. His research has been featured also in numerous business and popular publications, including the Wall Street Journal and Fortune.His research has been supported by several Asian, European, and US agencies such as the National Science Foundation. He serves on the editorial boards of Mathematics of Operations Research, Journal of Risk, Production and Operations Management, and Journal of Energy Markets. He has consulted several start-ups, Fortune 100 companies, and financial institutions.

Other Teaching Faculty
Teo Chung Piaw

Teo Chung Piaw

Provost Chair Professor and Head, Decision Sciences

» View CV

Chung Piaw is Provost Chair Professor and Head of Decision Sciences at NUS Business School. Prior to his current appointments, he was Acting Deputy Dean, Vice Dean of the Research and PhD Programme, as well as Chair of the PhD Committee in the School. He was an Eschbach Scholar in Northwestern University, Professor in Sungkyunkwan Graduate School of Business, and a Distinguished Visiting Professor in Yuan Ze University. His research interests lie in service and manufacturing flexibility, discrete optimisation, ports container operations, matching and exchange, and healthcare management. He is currently an area editor for Operations and Supply Chains, and associate editor of Management Science (Optimisation). He has also served on several international committees, such as the Chair of the George Nicholson Student Paper Competition (INFORMS, USA), member of the IMPACT Prize Committee (INFORMS, USA), Fudan Prize Committee on Outstanding Contribution to Management (China), and the Hong Kong PhD Fellowship Scheme Selection Panel.

Tuan Q. Phan

Tuan Q. Phan

Assistant Professor, Information Systems, School of Computing

» View CV

Tuan is an Assistant Professor in the Department of Information Systems at NUS School of Computing. He has a Doctor of Business Administration from Harvard Business School in Marketing, and a Bachelor of Science from MIT in Computer Science and Electrical Engineering, with concentrations in Business and Economics. Prior to his graduate studies, he started a company providing 3D computer graphics for mobile devices. He has extensive consulting experience with firms dealing with big data issues in advertising, media, e-commerce and retail. His research brings together social sciences, computer science, and statistics to investigate social networks, social media, big data, product diffusion, word-of-mouth, and web and mobile commerce.

NUS Business School
Mochtar Riady Building, Level 5
15 Kent Ridge Drive, Singapore 119245

Email: 
Phone: +65 6516 7872

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