In this meetup, you will get an introduction to the main tools and ideas in the data scientist’s toolkit. This presentation gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components highlighted; the first is a conceptual introduction to the ideas behind turning data into actionable knowledge, the second is a practical introduction to the tools that are used like version control, markdown, git, GitHub, R, and RStudio.
Learn the fundamental terminology and processes in data science
Discover the technology landscape that has helped fuel the data explosion
Unlock the hidden value in the vast amounts of data
Who should attend
New graduates wanting to work as data scientists
Professionals in any role, across any sector (marketing, healthcare, finance)
Anyone currently working with data
Anyone who recognizes that data skills are in high demand
People wishing to learn how to maximize their use of data
A basic understanding of programming/computing and statistics is recommended.
Meet your Speaker
Henri Dwyer is a data scientist at Dataiku New York. He is the first US employee, working on all sides of the business including sales, Hadoop, and infrastructure setup, analytics projects, hiring and building teams. He has completed several customer data science projects in healthcare, transportation, and marketing.
About our Sponsors
Galvanize is an education company that blends the lines between learning and working. We believe in creating easy access for anyone who has the drive and determination to jump into the tech world, especially in entrepreneurship, engineering, and data science. Our campuses are home to students, startups, investors, mentors, and other people who are engaged and excited to level up their skills. To learn more about Galvanize, visit galvanize.com.
Dataiku created Data Science Studio (DSS). DSS is a software platform that aggregates all the steps and big data tools necessary to get from raw data to running and maintaining data-driven applications. Thanks to its visual and interactive workspace, it is accessible to both Data Scientists and Business Analysts and significantly shortens the load-prepare-test-deploy cycles required to create data-driven applications.