Date: March 12, 2018 - March 14, 2018
Time: 9:00 AM - 5:00 PM
Venue: Valero Grand Suites, Makati
Learn the techniques that will move your organization to advanced analytics maturity.
In 2018, there is a myriad of data sources streaming into the modern organization. Text, spatial and unstructured data sources present challenges to the companies seeking to understand customer and organizational needs with greater speed and accuracy. The discovery and extraction of useful patterns in business data is enabled via techniques such as natural language processing, geospatial analysis and segmentation methods. In this course, you will learn the methods that data scientists use to discover trends and relationships that add value, advantage and impact to business decision making.
Taught using a variety of open source and cloud technologies, the course teaches techniques for handling, manipulating and analyzing high volume (millions of rows), high dimension (thousands of variables) business data. Real world projects from the DataSeer analytics consulting team are extensively used to illustrate how each model is used in the real world.
This course is suitable for managers who want a better understanding of the machine learning and statistical models that can be used to aid business decision making. The course is also aimed at data scientists in training who seek to sharpen their data science skillset.
Early bird discount! 3k PHP off for those who pay before March 9, 2018.
Need more info or ready to enroll? Click here https://dataseer.com/
–Instructor: Carl Calub – Data Scientist—
Carl Calub is a Data Scientist and Instructor at DataSeer. He has developed and used quantitative models for various applications such as strategy formulation, campaign tactical support, policy implementation design, and impact evaluation. Apart from his work in banking, financial risk management, and telecommunications, he has also applied his skills in a variety of fields; including education, disaster risk management, medicine, and sports. He was formerly a Data Scientist working on big data projects for the PLDT group.