BIG DATA ANALYTICS BOOTCAMP FOR BUSINESS PROFESSIONALS
Disruptive innovation is set to change the course of our lives in the 21st century. Learn how you can harness the power of technology in the data analytics arena to make better sense of the World and how you can increase the competitive edge of your organisation.
Covering both theoretical concepts grounded in sound fundamentals and hands-on practical with applications and case studies, this 2-day boot-camp addresses a wide variety of business issues and how better business decisions can be made through the lens of data analytics.
This programme is designed for Professionals who may not have the prior knowledge but are keen to learn the ropes of analytics application in business world. Those with relevant past training will find that this course offers refreshing insights and useful practical applications.
- Design and formulate the use of relevant analytical methodologies to formulate a big data solution in addressing organisational challenges
- Learn and apply the 7-Step Big Data Analytics framework in big data project management
- Plan, execute and implement big data analytics solution to make effective business decisions
- Assess and evaluate analytical model performance in addressing business objective(s)
- Describe best practices of big data analytics and analytical pitfalls to avoid
- Introduction to Big Data Analytics and Business Analytics
- Data Driven Decision Making Made Simple
- Data Mining for Game-Changing Business Insights
- Big Data Techniques and Technology
- Predictive Analytics for Today’s Managers
- Harnessing the Power of Analytics for the business of tomorrow
- Case Studies and Applications of Big Data Analytics: How Managers can apply data analytics
- Taking advantage of Best Practices and Avoidance of Pitfalls in applying Big Data Analytics
- Strategy formulation
Who should attend?
(Level 3) New Managers
(Level 4) Managers
Mr Ng Jinsheng joined IBM SPSS in 2008 as an Executive in Training and Consulting after his graduation from the National University of Singapore (NUS) with a Degree in Statistics and Applied Probability. During his stay in IBM SPSS, he has trained hundreds of participants from the public service and private sector in statistical and data mining concepts, tools and applications in solving business problems. He has also led consulting projects and worked with C-level executives in addressing pressing business issues during which he received many praises and testimonies. During his working with IBM SPSS, Mr Ng also completed his Masters of Science in Knowledge Management [M.Sc(KM)] from the Nanyang Technological University (NTU) and graduated one of the top in his cohort with a Dean’s List award in academic excellence. He later joined SAS Institute as an Education Specialist in the Training department, and thereafter as a Senior Associate in professional Consulting services, where he won the “Excellence in Service” Award for founding and championing the inaugural Inter-Varsity Analytics Competition in 2014 (Singapore).
He is currently a founding member of his consultancy and lectures and trains at TertiaryI nstitutions in Singapore in the area of business statistics, data mining and big data analytics, and develops analytics courses for undergraduate programme sin Singapore. Professionally recognised by the Project Management Institute (PMI) as a Certified Associate in Project Management (CAPM), Mr Ng is also an IBM Business Analytics Certified Specialist in IBM SPSS Modeler (Professional)and IBM SPSS Statistics, as well as SAS Certified Predictive Modeler using SAS Enterprise Miner and SAS Certified Business Analyst using SAS 9: Regression and Modeling.
|Programme Fee||Amount (including 7% GST)||Remarks|
|Member Total Fee||$2,140.00||-|
|Non-Member Total Fee||$2,568.00||-|
|Early Bird Discount||10%||
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Early Bird Discount
Terms and Conditions
Programme Executive In Charge :Grace Tan
Telephone Number :62489414
Email : firstname.lastname@example.org
Non-members are welcome to sign up for SIM membership to enjoy the discounted rate.
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