Data Science with Python - For the Busy Professional (6 sessions)

Data Science with Python - a Guided Approach for the Busy Professional (6 sessions) 

Get current with the latest toolstack.   This course provides a smooth intro to the most popular language for Data Science, Python.  We'll start with the logistics of installing and using the compute and graphics stack.  A dual approach, we'll be teaching you Python programming and Data Science concepts (the foundation for Machine and Deep Learning).  Each session will be a combination of recent theory and current practice.  Topics include Supervised and Unsupervised Learning, Hidden Layers, Hyperparameters, Hessians, and more.   We'll draw inspiration and motivation from real-world case studies.

Who is this course for?

If you've been away from code or tech for a few years you've missed a lot of excitement.   Data Science and Machine Learning are the drivers.  Engineers, Technical Managers, Programmers, Analysts, Scientists, Financiers, Executives and Career Changers alike will benefit from this small class hands-on introduction to the future.  This course is ideal for the busy professional looking for high quality local learning experience.

Prerequisites

No programming experience necessary. (Python, Linux, and Jupyter will be taught in a Just-In-Time style). Comfort with high school mathematics.  (We'll provide elementary geometry, probability, statistics, and calculus as needed).   There will be special breakout sessions available to students with advanced skills.  Curiosity and a drive to acquire up-to-date skills.  If you're wanting to explore explore the field of Data Science in a student friendly yet professional setting this course is for you.

 Format

The course will be delivered in person on six (6) Tuesday evenings from 6:00 – 9:00 PM on November 7 through December 19, excluding November 28.  Specifically, the course dates are:  November 7, November 14, November 21, December 5, December 12, and December 19.   (A make-up class may be available for students not available to attend the November 21 course.)   Online and office hours will also be available.  Textbooks will be provided. 

Your Course Designer and Instructor - Nathan Kohn ('en zyme')

'en' has taught computer programming, mathematics,  and the science of data at the university level for a decade, and continues to explore and share insights about data science, machine learning, and deep learning.  His professional experience includes Meteorology (NOAA/NCAR), Telecomm (Lucent/Verizon), Biotech (BUSM/khmer), Manufacturing(Rockwell), Aviation (Raytheon) and of course, Software, everywhere.  

A frequent speaker, 'en' has presented at PyCon, SciPy, PyData, PyCon Canada, and JupyterCon. En is a principal at Ad Hoc and Nimble [a data science consultancy] and at 40th Parallel Python.  He has been a co-organizer of Boston Python is currently leader of the Deep Learning Study Group (BRIIA),  the organizer of the Pleasantly Pythonic Meetup (Pleasanton), and can often be found mentoring anywhere in the Tri-Valley where coffee is available.  On a side note, en recently co-founded the Pleasanton Jazz Society.

About BRIIA

BRIIA (http://briia.io) is San Ramon's only collaboration community for entrepreneurs and data scientists.  Through our accelerator program, co-working community, events, mentor network, corporate sponsors and in partnership with the community, we are fostering an ecosystem of entrepreneurship and innovation in the TriValley.    

Questions?  

For more information, or a copy of the syllabus, please contact Melissa at melissa@briia.io or at 510-508-0763.