A global insurance giant solves advanced machine learning skills gaps with regional office training:

A forward-looking insurer decided to invest in the knowledge of their data science team covering talents across regional offices (including Singapore, HK and India) and ran an advanced, intensive training program to close the skills gaps for machine learning model workflows. Xccelerate successfully analysed client needs, built customised curriculum and projects, delivered the entire program and boasted powerful deployment results all within just 7 days end-to-end. Xccelerate devised a practical, highly customised curriculum that focused on the design, deployment and evaluation of Python, popular libraries and cutting-edge machine learning models that can be effectively applied across structured, semi-structured and unstructured data sets. The well-structured curriculum accelerated the company’s learning objectives around data science workflow stages, data preparation, feature engineering and model evaluation and metrics. Using hands on exercises and custom-built projects, the team practiced rapid data mining, recommender systems and sequencing with machine learning best practices in the insurance industry to overcome common challenges in deployment they were facing. The training was successful and relevant for the company’s AI Center of Excellence consisting of data analysts, data scientists and machine learning engineers across different levels of Python knowledge. Xccelerate addressed critical skills gaps to empower the team to further capitalize on useful insights in automation (Robotics Process Automation), customer centric decision-making and business process. The program also covered machine learning model application in insurance with projects and case studies covering insurance advisory and customer service, transaction and claims processing, fraud prevention and new product and pricing exploration.