Overview
| Reference No | CRS-Q-0033517-ICT |
|---|---|
| Part of | Graduate Certificate in Business Analytics Practice, Graduate Certificate in Management of Business Analytics Project |
| Duration | 3 days |
| Course Time | 9.00am - 5.00pm |
| Enquiry |
Please contact Ms. Jeryn LIN at tel: 66017926 or email |
Data-driven decisions perform significantly better according to a study led by the MIT Centre for Digital Business. One barrier to data-driven decision making is the shortage of experienced talent in analytics.
Data modelling and engineering is the role of data scientists or data analysts, business leaders and managers have a critical role to play at the beginning and at end of the process, framing the problems and analysing the results to provide the recommendations for sound decision making. These managers’ equally need to know and understand data science, combining it with their knowledge of the business and the business needs, to address challenges faced by the organisation.
When presented with analytics output, business decision makers commonly have the following questions and uncertainties. It is necessary for the end consumers of data analytics to know how to discern good analytics work from a poor one.Upcoming Classes
Duration: 3 Weeks
When: Aug 15
Duration: 3 Weeks
When: Sep 26
Live Session Schedule
| 15 Aug to 2 Sep 2022 | |
|---|---|
| Session 1 | Friday, 26 Aug 2022, 9:00am to 11:00am |
| Session 2 | Friday, 2 Sep 2022, 9:00am to 11:00am |
| 26 Sep to 14 Oct 2022 | |
|---|---|
| Session 1 | Friday, 7 Oct 2022, 9:00am to 11:00am |
| Session 2 | Friday, 14 Oct 2022, 9:00am to 11:00am |
Notes: All sessions are in Singapore Time SGT.
Key Takeaways
- Ask the right questions to evaluate model goodness and validity
- Interpret common model outcomes and applications
- Understand the benefits and risks of applying particular analytical outcomes
- Understand the difference between various discipline areas such as statistics, machine learning, and operations research
- Understand competencies required of a data driven project
- Do a quick evaluation of a project given the organisation data and analytics maturity level
- Make recommendations for a project to succeed in the above context
Who Should Attend
Structure
- An overview on data and analytics process and life cycle
- Reliability and validity check for data analytics model
- Common model results interpretation and application
- Different schools of modelling techniques
- Strategy for data-driven projects
Fees & Funding
| Learners |
Course Fee |
7% GST on course fee |
Total course fee payable, including GST |
|
Participants who are Singaporeans / PRs / based in Singapore (SGD) |
SGD300 |
SGD 21 |
SGD321 |
|
Participants living overseas (USD) |
USD250 |
NA |
USD250 |
- All fees and subsidies are valid for 2022 only.
- All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
- SME fees are applicable only to participants who are sponsored by small and medium enterprises.
- Unemployed participants are required to declare their status upon course application, and false declaration of information will invalidate subsidy & enrolment.
Instructors
Course Manager
Mr. Nirmal Raja PALAPARTHIPrincipal Lecturer & Consultant, Data Science Practice
Certificate
The ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course.
Preparing For Your Course
NUS-ISS Course Registration Terms and Conditions
NUS-ISS and Learner’s Commitment and Responsibilities
WIFI Access
WIFI access will be made available. User ID and password will be provided in the participant’s kit.
Venue
We are now located at 3 campuses as our main campus ISS @25 HMKT undergoes renovation. Click HERE for directions.
In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.
Course Confirmation
All classes are subject to confirmation and ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.
General Enquiry
Please feel free to write to isstraining@nus.edu.sg if you have any enquiry or feedback.
