TDWI Certificate Track

Prerequisite: None

Course Outline

Data science has been called "the sexiest job of the 21st century" and with good reason—the size and breadth of our data is growing exponentially, making our ability to understand that data more and more challenging.

You may have heard that data scientists spend 80 percent of their time sourcing, cleaning, and preparing data. While this may be an exaggeration (or not!)—data preparation is certainly a large and important part of data science and predictive analytics. Algorithms are more than black boxes to run; no single algorithms is always "best". Each algorithm has strengths and weaknesses that should be understood so that analysts can improve on their accuracy. Ultimately, the models have to be turned into actionable decisions. Determining how to use the predictions from models require planning from start to finish by analysts and business stakeholders.

TDWI's Data Science Bootcamp lays the groundwork for your journey to become a data scientist. This three-day intensive learning experience covers all the aspects of data science—from its impact on your organization to the role of the data scientist. You'll learn essential data science skills directly from our expert instructor. From targeting a business challenge to preparing data to building analytic models and interpreting results to delivering insights to the business, this Bootcamp provides end-to-end coverage of what it takes to succeed as a data scientist.

Your Team Will Learn

• An overview of data science
• How to define project objectives
• Considerations for data collect and integration
• How to prepare data for analysis, including data cleaning and feature creation
• Key algorithms for building supervised and unsupervised learning models
• How to deploy predictive models

Geared To

• Anyone who is getting started in data science and has some experience with data, whether in Excel, databases, BI, or statistics. This includes BI and analytics professionals and managers that are exploring the broader world of data science. Nontechnical professionals are welcome as well to learn the terminology and key principles in data science. Intermediate to advanced professional data scientists will find some parts of this session to be a review for them, but will also benefit from specific practical tips that go beyond standard textbook summaries of data science.