UCLA Extension

March 2018 Digital Tech Newsletter

Spotlight: New Data Science Practicum

This project-based Data Science Practicum provides students with the opportunity to gain real-world experience working with our industry partners. Each practicum cohort is sponsored by a company or organization. This collaboration allows students to work with partner companies/organizations to gain analytics experience and reconcile mathematical theory with business practice. Student groups — supervised by a UCLA Extension practicum instructor — work with the practicum company/organization to identify, define, scope, and analyze a business problem. Students will work in groups to solve real-world data analysis problems and communicate their results. Innovation and clarity of presentation will be key elements of evaluation.

It is assumed that students participating in this practicum have a thorough knowledge of basic machine learning concepts (classification, clustering, regression, dimensionality reduction, etc.) and are proficient in R or Python. Students will be working on a real-world data science project from Day 1 of this Data Science Practicum. Very little time will be spent on lectures or introducing new machine learning concepts or explaining basic constructs of programming languages.

For the Spring 2018 cohort, students accepted into the practicum will be working on a real-world project to collect/scrape big data in real-time for all the regions in the U.S. and other countries, such as China. The data will be cleaned, standardized, and properly aggregated, measured, managed to become real-time indicators of various economic activities at the local and national levels. In countries like China, economic statistics are not available in real-time, available with significant delay, or not trustworthy. This project will focus on how to turn the collected big data into useful indicators to be comparable to the official economic statistics issued by government agencies, in retrospect. The indicators will be similar to GDP, payroll employment, housing prices, etc.

For students without previous experience in data science, we recommend completing our Data Science specialization. The Data Science specialization can be completed in as little as 10 weeks in our 10-Week Data Science Camp. 

The Spring 2018 Practicum will run from April 2 – June 9, 2018
Meeting schedule:

Mondays, 6:30 pm – 9:30 pm
Wednesdays, 6:30 pm – 9:30 pm
Saturdays, 10 am – 1 pm

Please click here for more information or to enroll in the practicum.

Instructor Interview:

This month we interviewed Eric Kellener. He is a professional management consultant and has been teaching with us for the last year.

UCLAx: Please tell us about yourself and how you got to where you currently are in your career?

Erik: I’ve had the good fortune to know what area I was interested in from an early age. I was one of those kids working with computers since I was 11 years old. I continued the path and studied Computer Science in both Undergraduate and Graduate school. To date, I’ve spent the first 1/3 of my career writing software, another 1/3 in building and leading engineering teams, and the recent 1/3 focusing on developing the next generation of great technology leaders.

 

UCLAx: Is there anything you are currently working on that you would like to share with us?

Erik: For the past 6 years, I’ve been building a consulting practice focused on helping companies scale their teams and organizations through the lens of technology leadership. I generally serve as a consulting CTO, a business coach, mentor and target team and leadership development. http://www.kellener.com

 

UCLAx: Could you tell us about your course “Introduction to SQL” and what students can expect to take away from it?

Erik: This is a fairly new experience for me, especially as an online-course instructor. When designing the content, I honestly struggled on how to effectively measure a student’s grasp of the curriculum (e.g. quizzes and tests) with an online format. After speaking with number of colleagues, I landed on an approach that is heavily weighted on solving real-world, practical problems, as opposed to measuring their accuracy of technical structures and syntax (Google and Stackoverflow are great for that). In other words, examples and problems would be framed as “You have been asked by the Human Resources team to develop an employee report that shows […]; write a solution to accomplish this.“  I think of these problems as mazes which have many successful paths to the exit.

 

UCLAX: What advice can you give to our students trying to break into the Database Management field?

Erik:

  • Get practical experience as soon as possible. Build a database backend for a friend’s website. Volunteer to help out your IT team in building an asset-tracking system. The more you keep close to the domain, the quicker you’ll gain momentum in your learning.
  • Don’t specialize early on. Learn about the tools and technologies available and used by the industry. Familiarize yourself with the database technology landscape, from MongoDB, to MySQL, to Oracle, to Neo4j. When working with my clients on hiring, I almost always recommend they hire generalists with a high capacity to learn and adapt.
  • Find someone who can be a mentor. Pair with someone who has the skills or experiences you want to develop — this applies to most things in life.

 

Spring Course Preview:

We are now offering a great new course for Data Science students!

Data Science Using SAS

Data Science using SAS is a unique and focused class to better prepare you for high-demand Data Science Analyst level positions. After completing this class, students will be able to analyze data in order to answer critical business questions. Students will also be able to apply data cleaning techniques to ensure integrity.

The core topics covered in this class include SAS Enterprise Guide, Base, and Advanced Certification exam preparation, as well as SQL for data manipulation and data cleaning. These are all essential topics across all big data industries. There are also advanced topics on data and visual analysis and clinical data, and CDISC standards for the pharmaceutical and medical industries.

This is a fast-paced class and requires some computer programming experience in any language, or knowledge of SAS programming. You will be expected to participate in class discussions and question and answer sessions. Your class exercises will be written in SAS, a powerful statistical programing language used across all industries.

Spring offering: #361096

4/28 – 5/27 This class will meet in person on 4 Saturdays for 6 hours each day. In addition, there will be 9 hours of online office hours for student exercises on 3 Sundays.

 

News:

-Spring Quarter begins the week of April 2, 2018.

-The deadline for Applications for the Coding Bootcamp Scholarship has been extended to March 21, 2018. Follow the link for more information: https://ucla.box.com/s/juh3eqm33eclxbmcucv3pxii376xpbww

-You can follow us on Facebook @UCLAxDigitalTech or connect with us on LinkedIn @UCLAx Digital Technology.

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