- Understand that modern manufacturing is no longer just about finding ways to operate faster while reducing expenses; it is also about doing so in a data-driven and intelligent way.- Using cloud and data analytics, vast quantities of data generated can be processed and translated into actionable insights to diagnose problems and identify opportunities for improvement.- Learn that with machine learning, highly intelligent systems can assist the workforce in optimising processes, predicting equipment failures and changes in demand patterns. At their best, these intelligent systems can also autonomously make decisions and respond to changing internal and external business needs.- Internship goal is to “Improve the yield efficiency campaign over campaign”, to “improve cost of goods”, and to “make Jurong site the best New Product Introduction (NPI) site in the manufacturingsupply chain”.- Assist and support the data scientists and work within the Data Analytics team to structure and manage historical operational data in a way that will help solve pharmaceutical manufacturing problems.- Help with compiling findings and recommendations into reports.- Acquire knowledge on the interconnectivity across operational, engineering and quality functions to deliver the new technology solution for improving processes and product quality attributes.- Immerse in the site activities and understand how compliance to the Key Performance Indicators (KPIs) is critical to the site.

Predictive analytics with R, Python, Tableau.RPA Bot, UIPath for field detection and email notifications with Edge.

Child Protective Service wants to transform data management from paper/manual data tracking to using e-system.- supporting behavioural change within the team in data updating and management- consolidate data in system- monitor that the team is compliant in updating data management process- extract data and draft presentation on trends analysis- checks to ensure that data update is accurate

Leader of chatbot project, introduced R Programming and Data Visualization and Exploratory Analysisto the company.