Predictive analytics were first put to use at a large scale in the banking industry. “Quants” were predicting future stock prices based off of patterns deciphered by parsing through historical records of the behavior of the stocks. In today’s world, predictive analytics are ubiquitous in not only the banking industry, but also healthcare, business, and politics amongst many others.
In this course, we will build tools to learn from data organized from real-life events to make predictions about what the future might hold. We will utilize tools in feature extraction, machine learning and deep learning to make inferences about the very world that we live in.
Building a data science tool belt to learn from and make predictions about real-life data.
This course is about streamlining the thought process used by data scientists and utilizing methodologies of data science to build real tools that could be applied in a number of industries. By the end of this course, you will be able to collect, organize, and learn from data generated in today’s world and catalyze a new way of thinking about problem solving.
Each class will be an engaging, interactive session where we build tools together to make predictions about our data. The classes will be focused on actually building the predictive tools; however, each class will have supplementary lecture notes that describe the methodologies in further detail and extra programming tasks if anyone wants extra practice.
This course begins on Monday March 21 at 6pm and will meet every Mon + Wed from 6pm-9pm for three weeks.
This course will be held at Spark Baltimore:
8 Market Place Suite 300
Baltimore, MD 21202
We have an information session scheduled for 6pm on Wednesday, March 16 at Spark Baltimore where you can meet the instructor, check out the space, and learn a little more about what will be covered in the course. You can register for the information session here. If you cannot attend the info session, please don’t hesitate to send any questions to: email@example.com
Please note: seats are limited for this course.
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