“Aim to provide the fundamentals to build strong data science team”
Date: 17 – 19 May 2018
Place: BPR KS Office
Typically, the data collected in banks are so complex that it is beyond the ability of any traditional data software tool to manage it. As banks compete to gain a competitive advantage, the need for managing big data and analytics becomes more relevant.
With its increased accuracy and efficiency, banks are starting to realize the value of Big Data and are slowly adapting to this new change. Which includes applying Data Science to accommodate their needs.
One of the challenges in adapting data science comes when the company is required to build a quality team of data scientists to handle the data and analytics. Choosing the right members for the team can be difficult. The demand is high, but the pool of available talent is rather limited.
Building a strong data science team could be a challenging task and people should manage their expectations up front. Mainly, because the field is so new and many companies are still trying to learn exactly what a good data scientist should offer.
Emphasizing the basics and fundamentals of data science tools in order to develop a well-maintained database by using R programming toolkits and applying machine learning model.
- Ability to utilize data science tools for data cleansing and machine learning purposes
- Using R to prepare data for data processing
- Develop a machine learning model for product recommendation to customers
Relevant Courses: Data Science Fundamentals and Machine Learning