Time: 9:00 AM to 6:00 PM
Venue: DoubleTree by Hilton Hotel San Francisco Airport
**Please note the registration will be closed 2 days (48 Hours) prior to the date of the seminar.
The seminar will begin with an over view of data science and many the steps required for collecting, cleaning, organizing and deriving information out of data. The steps are common to all of the tools and will form the foundation for analyzing, comparing and utilizing the tools used in the remainder of the seminar: R, pandas and Deedle.Topics covered in the foundation are:
This seminar will then proceed into demonstrations and hands on experience using R Studio, pandas in Enthought Canopy, and Deedle in Visual Studio. Each of the topics covered in the data science overview will be demonstrated with each tool, including hands on installation and experimentation through several exercises. By the end of these three sessions (R, pandas and Deedle) the participant will be able to create their own data science environments in any of the tools and have the knowledge of how to proceed with performing the core concepts in each environment, as well as be able to determine which tools are best for their needs.
Data Science is becoming the must-have skill in technology and business. But do you know what it is, why it is important, and how it differs from business intelligence and big data? Do you know that there are very useful open source tools on multiple platforms that allow you to perform data science? That you can leverage your existing Python or .NET programming skills, or use other domain specific languages such as R?
Data science is deep knowledge discovery through the interactive exploration of data. This discipline often involves using mathematic and algorithmic techniques to solve some of the most analytically complex business problems, leveraging troves of raw information to figure out hidden insight that lies beneath the surface. It centers on evidence-based analytical rigor and building robust decision capabilities.
Data science matters because it enables companies to operate and strategize more intelligently. It is all about adding substantial enterprise value by learning from data.
Most who start to learn Data Science turn to domain specific languages such as R. If you know even a little about Python, there is a well-established Python library "pandas": The Python Data Analysis Library. And on the .NET platform, there is the open source Deedle library for exploratory data analysis in F# and C#, which was created by quants at BlueMountain Capital.
R for data science
Data sciences with Deedle
|1||2 Attendees||10% off|
|2||3 to 6 Attendees||20% off|
|3||7 to 10 Attendees||25% off|
|4||10+ Attendees||30% off|
To avail the above group discounts, all the participants should register by making a single payment
Call our representative TODAY on 1800 447 9407 to have your seats confirmed!
Michael Heydt is an independent consultant, educator and trainer with nearly thirty 30 years of professional software development experience, during which time he has focused on agile software design and implementation using advanced technologies in multiple verticals including media, finance, energy and healthcare. He holds a MS in Mathematics and Computer Science from Drexel University, and a Masters of Technology Management from the University of Pennsylvania School of Engineering and Wharton Business School.
His studies have focused on technology management, software engineering, entrepreneurship, information retrieval, data sciences, and computational finance. Since 2005 he has specialized in building energy and financial trading systems for major investment banks on Wall Street and several global energy trading companies, utilizing .NET, C#, WPF, TPL, DataFlow, Python, R, Mono, iOS, Android, and many others tools too numerous to list.
His current interests are creating seamless applications using desktop, mobile and wearable technologies, and which utilize high concurrency, high availability, real-time data analytics, augmented and virtual reality, cloud services, messaging, computer vision, natural user interfaces, and software defined networks. He is the author of numerous technology articles, papers and books, is a common speaker at .NET users groups and various mobile and cloud conferences, and regularly delivers webinars on advanced technologies.