Brian Sletten is a liberal arts-educated software engineer with a focus on forward-leaning technologies. His experience has spanned many industries including retail, banking, online games, defense, finance, hospitality and health care. He has a B.S. in Computer Science from the College of William and Mary and lives in Auburn, CA. He focuses on web architecture, resource-oriented computing, social networking, the Semantic Web, data science, 3D graphics, visualization, scalable systems, security consulting and other technologies of the late 20th and early 21st Centuries. He is also a rabid reader, devoted foodie and has excellent taste in music. If pressed, he might tell you about his International Pop Recording career.
This course will introduce you to the various skills that go into data science, provide practical walkthroughs of relevant languages and tools and lay down a study plan for moving forward in this field.
As there is a rush to hire data scientists these days, there is a coincident rush to update resumes to include the term “Data Scientist”. Unfortunately, like most types of science, it is less a single topic and more a multi-disciplinary way of thinking, inquiring and communicating.
You won’t become a data scientist over night, but you can learn to be one in time. Individuals do not need to know everything about the field, but teams should be composed of individuals who collectively do.
We will cover:
- Data Science as a field
- Basic statistics and numerical methods for dealing with data
- Doing Data Analysis in Spreadsheets
- The R programming language, its environment and online ecosystem
- R’s visualization packages
- Interacting and visualizing data with D3.js
- Interacting with Big Data environments in R
- Interacting with Linked Data in R
If you’re not terrified, you’re not paying attention.
Publishing information as webs of data does not require us to just give it away. We have a series of tools and techniques for managing identity, authentication, authorization and encryption so we only share content with those we trust.
Before we tackle Web Security, however, we need to figure out what we mean by Security. We will pull from the worlds of Security Engineering and Software Security to lay the foundation for technical approaches to protecting our web resources.
Encryption is a powerful tool for privacy. At least that is what we’re meant to think.
If you consider encryption to be a black box of magic, you should probably attend this talk.
If you think encryption will protect your secrets, you should probably attend this talk.
If you have (or haven’t) been following the news, you should probably attend this talk.
The truth is, encryption can be an effective way of making it harder for people to steal your secrets. But it isn’t magical, it isn’t fool proof and, depending on how you are using it, may be completely useless. It is a hard topic that we’ll only touch the surface on, but there are very few topics that are more crucial for our industry and profession to understand better than encryption. You don’t have to understand the math (although that will help), but you do have to understand what it will and won’t do for you*.
*and how implementations of it may have been intentionally compromised
