26 – 29 March 2018
Hotel Jen Tanglin Singapore

Post-Conference Workshop | 29 March 2018, Thursday

Workshop C: Nurture, Reskill and Upskill Your Existing Manpower To Enhance The Effectiveness Of Machine Learning Applications

9:00 am - 12:00 pm Workshop C: Nurture, Reskill and Upskill Your Existing Manpower To Enhance The Effectiveness Of Machine Learning Applications

Raymond Au, Head, Allianz Asia Lab (Data Science, Innovation),Allianz
No doubt, technology, data science, machine learning etc will change the nature of current jobs, but that doesn’t mean there will be no jobs. People will continue to play a very important role in putting data into context with machine learning application.
 

This workshop will guide participants on best strategies and practices in re-skilling and upskilling your existing manpower to boost competencies in translating data into actionable insights.
 

Learning outcomes:
  • Identifying areas for machine learning deployment and re-allocate talent for value-added work
  • Equipping your team with appropriate domain knowledge
  • Assessing the impact of machine learning  on the future workforce
  • Taking a proactive approach to nurture, reskill, upskill your existing workforce 
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Raymond Au

Head, Allianz Asia Lab (Data Science, Innovation)
Allianz

12:00 pm - 1:00 pm Lunch

Workshop D: Building An Effective and Coherent Data Platform for Machine Learning

1:00 pm - 4:00 pm Workshop D: Building An Effective and Coherent Data Platform for Machine Learning

In a digital world today, data has become our most-valued commodity and applying machine learning in real-world scenarios is a challenging task. The main focus of the database community has been on creating systems and abstractions for effective training of machine learning models on large datasets.

This workshop will guide participants in creating an effective data platform that is beneficial and user-friendly for businesses to access and apply.
 

Learning Outcomes:
  • Developing a comprehensive man-machine framework for machine learning data processing
  • Designing platform with scalability, agility and security in mind
  • Evaluating criteria for data storage
  • Overcoming constraints of machine by “outsmart-ing” them