The University of New Mexico's Continuing Education hosts a Five-Day Data Science Bootcamp scheduled for Oct. 7 through 11 where experienced data experts will help participants build a strong foundation of theoretical concepts on data science and big data engineering, while teaching how to apply them to challenging datasets.
According to the recruiting site Glassdoor, data scientist is the number-one job in America for 2019 for the fourth consecutive year. This bootcamp will teach the necessary programming statistics, machine learning and data science concepts to set attendees up for success.
The Continuing Education Department breaks down this bootcamp into different categories including Fundamentals, Machine Learning, Evaluation and Parameter Tuning, Big Data and Streaming Analytics and the Kaggle Competition.
The bootcamp will emphasize fundamentals of data exploration, visualization, feature engineering, quality acquisition and sampling.
In regard to machine learning, the curriculum covers a wide array of classification, regression, recommendation and unsupervised learned techniques. It will emphasize both the solid understanding of algorithms and their correct usage.
Teaching evaluation and parameter tuning involves a combination of lecture, discussion and hands-on labs that will ensure users have the ability to choose the right metrics for building a robust predictive model.
During the big data and streaming analytics portion of the camp, attendees will Hadoop cluster in the cloud and run Hive queries. They will also learn to build message queues and process data in real-time. Additionally, attendees will build an Internet of Things application.
Additionally, all attendees compete in an in-class Kaggle competition. Attendees start with simple predictive models on day 2 culminating in models that perform clever feature engineering with a lot of parameter tuning. Winners are announced last day of the bootcamp.
The program is open to everyone and all skill levels are welcome.
For more information and registration details, visit Data Science Bootcamp.