LEADING WITH BIG DATA ANALYTICS & MACHINE LEARNING



Overview

School NUS BUSINESS SCHOOL
Department BIZ DEAN'S OFFICE/MBA OFFICE
Code BIZ-LBDA
Funding Type SSG Funded
Stackable To An Academic Qualification? Not applicable
Name of Full Academic Qualification Not Applicable
Category Business & Management
Course Type SHORT COURSE
Can be done on AUDIT basis? No



Objectives

Objectives: 1. For leaders to discover how big data, analytics, machine learning can help their business to accelerate innovation and achieve a competitive and sustainable edge; 2. For leaders to be exposed to some of the most recent ideas and techniques in big data, machine learning and analytics; 3. For leaders to understand, interpret and trust the data that goes into their analytics to make business-critical decisions; 4. For leaders to learn how to build a data-driven culture across their organisations; Through the programme, participants will be equipped with the understanding and skills to: a) Identify analytics opportunities, i.e. how to use, leverage and apply analytics results in business decisions; b) Recognise and implement ways to integrate Big Data from external and internal sources for more useful results; c) Learn from examples of how new technologies and data analytics can enable business model innovations, and identify opportunties for innovation in their organisation; d) Assess and prioritise different big data initiatives, and understand the steps needed to design a data project; e) Use big data to enhance design, manufacturing and supply chain management performance; f) Identify opportunities to apply machine learning to business problems; g) Look at, interpret and use data analytics to think of new ways to do current business.




Outline

- 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.




Who Should Attend

Leaders and senior Managers from any industry, who are interested in building analytics capabilities to drive change within their organisation: E.g. C-level, MD, Directors, SVPs, EVPs, General Mgr.




Entry Requirements

• Managerial-level and above; • Have at least 10 years of working experience.




Class Schedule

Please click here



Lecture Sessions

AM/PM




Lesson Delivery

a) Facilitated Learning - 25 hrs; b) Pre-readings, self-study - 5 hrs; c) Group work & presentation - 5.5 hrs; d) Assessment - 30 minutes.




Calendar

Not Available




Full Fees (before GST)

S$5990.00




Fees and Fundings

International Participant Singapore Citizen 39 years old or younger Singapore Citizen 40 years or older eligible for MCES Singapore Citizen eligible for WTS Singaporean PRs Enhanced Training Support for SMEs
Full Programme Fee S$5990.00 S$5990.00 S$5990.00 S$5990.00 S$5990.00 S$5990.00
SkillsFuture Funding Eligible for Claim Period (19 Oct 2017 to 30 Sep 2020) - (S$4193.00) (S$4193.00) (S$4193.00) (S$4193.00) (S$4193.00)
Nett Programme Fee S$5990.00 S$1797.00 S$1797.00 S$1797.00 S$1797.00 S$1797.00
7% GST on Nett Programme Fee S$419.30 S$125.79 S$125.79 S$125.79 S$125.79 S$125.79
Total Nett Programme Fee Payable, Incl. GST S$6409.30 S$1922.79 S$1922.79 S$1922.79 S$1922.79 S$1922.79
Less Additional Funding if Eligible Under Various Scheme - - (S$1198.00) (S$1497.50) - (S$1198.00)
Total Nett Programme Fee, Incl. GST, after additional funding from the various funding schemes S$6409.30 S$1922.79 S$724.79 S$425.29 S$1922.79 S$724.79



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