Creating a Data Science Culture

Creating a Data Science Culture

Video Training

Get expert advice and best practices for various stages of your career in the field of data. Whether you are new to data science, an experienced practitioner, or an executive hiring for data science teams, this Learning Path will give you valuable insights into creating a culture and business model that makes the most of this emerging field. Upon completion, you’ll be able to successfully navigate the data science interview process, organize a data science team, and create a data governance program that is based on your particular business model.

Below are the video training courses included in this Learning Path.

1

Cracking the Data Science Interview

Presented by Jonathan Dinu and Katie Kent 2 hours 56 minutes

“Wanted: Data Scientist.” You’ve learned the concepts, you’ve seen the six-figure salary estimates, and now you really want the job. But there’s a hurdle in the way: the job interview. Can you get one? And, once you land one, will you ace it or blow it? In this step of your Learning Path, you’ll view a series of mock interviews (a software engineering technical interview, data science theory interview, and applied data science interview) that explains the concepts and social and behavioral aspects necessary to successfully navigate your interview. At the end of this course, you’ll be thoroughly well versed in the nuances, misconceptions, and realities of the data science job hiring process.

2

Building Data Science Teams

Presented by Paco Nathan 2 hours 26 minutes

Imagine cooking a stew with a single ingredient or growing a country garden with a single type of flower. One-dimensional efforts like these yield bland and boring results. Now imagine staffing a data science team with only PhDs in machine learning. In spite of the impressive pedigree, the result would be similar: bland, boring, and, possibly worse, ineffective. But, if not just data people, then who? In this course, data scientist Paco Nathan answers that and other questions on how to build a data science team. Cited in 2015 as one of the “Top 30 People in Big Data and Analytics” by Innovation Enterprise, Nathan offers insider tips gleaned from his 30+ years in technology.

3

Building a Data Science Culture

4 hours 34 minutes

This step of your Learning Path features a collection of presentations from Strata + Hadoop World conferences. You’ll explore several key components of building a data science culture, including practical advice for building a data science team, how to balance the roles of data science, engineering, and product-design, what designers and data scientists can learn from each other to improve their visualizations, and much more. You’ll touch on the critical components of data-based decision-making as you learn to develop a business model that incorporates data. By the end of this course, you’ll understand the role of data in early stages of design and innovation as well as the art and science of systemizing and coordinating human and machine-based contributions.

4

Data Governance

Presented by John Adler 3 hours 40 minutes

In this course, data management expert John Adler leads you through the maze of data governance issues facing companies today—security breaches, regulatory agencies, in-house turf battles over who controls the data, monetizing data, and more. In this fast-paced discussion of how to plan for, implement, and run a successful data governance program, you’ll get an overview of the ways data has been managed in the past and how the smart companies do it now. Along with an introduction to the operational frameworks used in data governance, Adler describes the roles of the Chief Data Officer and the Data Steward, outlines a set of commonly used policies and standards, and shows you how to build the business case for a data governance program.