AI for Leaders: Leveraging Data Analytics for Business

TGS-2020502020

NUS Business School

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Objectives

Through this programme, participants will: - Develop the skills and knowledge needed to leverage big data analytics, machine learning and AI capabilities to drive innovation and gain a competitive and sustainable edge in your business. - Learn about the latest ideas and techniques in big data, machine learning and analytics and discover how to apply them to real-world business challenges. - Understand how to interpret and trust the data that goes into your analytics, and learn how to make informed, data-driven decisions. - Gain the knowledge and tools to build a data-driven culture across your organisation, and learn how to effectively communicate the value of data analytics to stakeholders at all levels. The programme focuses on: Big Data Analytics: Explore the technologies, policies, and analytics methods that are essential for leveraging big data, machine learning and AI capabilities to drive innovation and gain a competitive edge. Actionable Intelligence in Business: Learn optimisation and visualisation techniques and discover how to engage stakeholders and turn data into actionable insights. Machine Learning and Business Applications: Get hands-on experience with machine learning techniques and learn how to apply them to solve real-world business challenges. Disruptive Innovation: Explore how to create new opportunities in mature markets using big data analytics, machine learning and AI capabilities. Distilling Value from Analytics: Develop a strategy roadmap, understand privacy implications, and learn how to avoid common traps and myths in data analytics. Change Management: Understand the role of data analytics, machine learning, and their applications in driving change within organisations. Examples and Cases: Explore real-world examples of how data analytics and machine learning can be applied to risk management, HR analytics, legal analytics, revenue management, consumer and retail analytics, and more.



Who Should Attend

Leaders and senior managers from any industry, who are interested in building analytics and AI capabilities to drive change within their organisation




Entry Requirements

Managerial-level and above. No prior experience in big data, machine learning and analytics required.




Class Schedule




Lesson Delivery

Classroom Facilitated Training




Full Fees (before GST)

S$5990.00




Nett Fees payable after SSG Funding



International Participant Singapore Citizen 39 years old or younger Singapore Citizen 40 years or older eligible for MCES 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
SSG Funding *
Eligible for Claim Period 1 Jul 2021 to 30 June 2024
- 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
9% GST on Nett Programme Fee S$539.10 S$161.73 S$161.73 S$161.73 S$161.73
Total Nett Programme Fee Payable, Incl. GST S$6529.10 S$1958.73 S$1958.73 S$1958.73 S$1958.73
Less Additional Funding if Eligible Under Various Scheme - - S$1198.00 - S$1198.00
Total Nett Programme Fee, Incl. GST, after additional funding from the various funding schemes S$6529.10 S$1958.73 S$760.73 S$1958.73 S$760.73
*   Learners must pass all assessment components to be eligible for SSG funding.
** Please note that all external funding for courses is limited in duration and subject to availability.

*** Please note that the mode of delivery is subject to change in light of the COVID-19 situation. Courses marked ‘online’ may have compulsory face-to-face sessions such as laboratory or hands-on components and details should be sought from the schools or departments before learners register for them.

Upcoming Course Dates
27/05/2024

Delivery Mode**
Face-to-Face

Course Code
NUSEE-LBDA

Funding Type
SSG Funding
Eligible for SkillsFuture Credit (SFC)
Alumni eVoucher (L3)
Alumni eVoucher (R&G)

Type
Short Course

Stacks/ Bundles to
NA

Audit/Graded
Nil

Area of Interest
Business & Management
AI & Machine Learning