UCLA Extension

June 2018 Digital Tech Newsletter

Spotlight: New programs

The certificate is a 4-course (16-unit) program that provides training and education for those who would like to pursue a career in data science. Courses cover data development and management, machine learning and natural language processing, exploratory data analysis, statistical models, data visualization, and inference. Additionally, the program includes hands-on training in real-life data science problems.

This program is available in standard or intensive formats. For more information, click here.

Grads of this certificate program will be granted UCLA alumni status. Many of our certificates, including Data Science, qualify for employer reimbursement. Please check with your employer.

 

The Python for Data Engineers specialization provides training and education for those who would like to specialize in big data analytics. Courses cover Python as a data analysis programming language, numerical computing, data analysis, unstructured data, statistical modeling, and data visualization. Additionally, the specialization includes hands-on training in design, analysis, and implementation of data-driven analytical strategy and tools to support business decision-making. This program has three required courses (12 academic units). For more information, click here.

 

Instructor Interview:

Vera Kalinichenko is one of our new Data Science instructors and is a professional in the field. We are very excited to have her join our team!

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

Vera: I was born in a small town in the west of Ukraine. I participated in national mathematical competitions while I was in high school. I have graduated from VZMS (http://math-vzms.org/) which was an old USSR-style mathematics school for high school students. I was accepted into Kiev State University named after T. Shevchenko and spent two years there studying pure mathematics. In 1997 I came to the United States.

I went to UCLA for my undergraduate and graduate work. After UCLA, I worked for many years as a software engineer, building software for finance companies to trade bonds, options, and currencies. During 2012, when Big Data started to rise, I switched to the field of data science and have been doing data science since. Currently, I work as Principal Data Scientist at Atom Tickets, LLC. My personal goal is a constant search for knowledge since life is a puzzle.

 

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

Vera: Currently, I am working on a customer movie list personalization for Atom Tickets and a variety of others projects; from basic model tuning to experimentation with neural nets and deep-learning libraries from TensorFlow. I love opening a probability graduate book or any mathematics textbook and reading a few pages for inspiration. I strongly believe that discrete mathematics, combinatorics positively influence your creativity and help build elegant and simple models.

 

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

Vera: My course is about developing a strong foundation in data science, familiarizing my students with data exploratory analysis, illustrating to my students the practical overview of several commonly used models in a wide range of fields. Data Science applications range from retail to finance, the medical field to engineering. I would like to prepare my students for their professional career as a data scientist/data analyst.

 

UCLAx: What advice can you give to our students trying to break into the data science field?

Vera: Mostly my students will not build gradient descent models from scratch at their workplaces, since there are so many libraries already written and available for use, and there is no need to reinvent the wheel. However, I strongly believe that it is very important to understand the main concepts behind the most commonly used models. What really lies behind the models are basic optimization techniques. It is important to develop an intuition of how to build a model and know what techniques work in what use case. It really makes sense to spend time and develop that foundation if you are serious about data science. I think data science is a combination of art and science, that uses key ideas from mathematics, statistics, machine learning, and physics, so it is useful to review the basic statistics and linear algebra concepts, then just keep building on that foundation.

There is so much information available nowadays, you just need to allocate time and use books and lectures, read blogs and start developing code, and practice modeling. I think if a person wants to learn something, now is the best time to be living and achieving it. There is so much quality information available, you should use it as learning opportunity. The only commodities we need are time and perseverance.

 

Summer Course Preview:

Introduction to Data Science

This course introduces students to the evolving domain of data science and to the food-chain of knowledge domains involved in its application. Students learn a wide range of challenges, questions, and problems that data science helps address in different domains, including social sciences, finance, health and fitness, and entertainment. The course addresses the key knowledge domains in data science, including data development and management, machine learning and natural language processing, statistical analysis, data visualization, and inference. The course also provides an exposure to some of the technologies involved in the application of data science, including Hadoop, NoSQL, and Python Programming language. The course includes case studies that require students to work on real-life data science problems.

Summer offerings: in-person, online, or in a hybrid format. 

 

Instructor Interview from Product Management:

Roy Firestone is the Sr. Director of Product for the global ad tech firm OpenX and teaches the course Tactical Product Management: Build it, Launch it, Grow it

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

Roy: I started computer programming at age 8 on one of the first home computers, the TRS-80 from Radio Shack. Computer information systems was a natural fit in undergrad. My first job was with Accenture in the technology practice in D.C., where I traveled around the world implementing software and training local staff in places like Rio de Janeiro, Bangkok, and Taipei. Through media companies like USA TODAY, I grew into advertising technology roles. My client-facing focus led to a career in product management, where I speak two languages: business and technology.

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

Roy: In my current role as Sr. Director of Product for the global ad tech firm OpenX, I am growing our digital video business by entering new markets like Connected TV.

UCLAx: Could you tell us about your course “Tactical Product Management: Build it, Launch it, Grow it,” and what students can expect to take away from it?

Roy: Tactical product management teaches how to shepherd digital products through the software development process. Product management roles and tasks differ from software engineering but are closely correlated. The objective is to make products successful through a combination of business and technical skills. It’s this unique combination of talents that define product management.

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

Roy: When trying to break into Product Management, it’s important to focus on accomplishments that align with this dynamic and exciting field. If you haven’t had a product role yet, revisit your resume and view it through a product lens. What turned you on to the product in the first place?  Were you a power user who helped design and launch a new system?  Were you the go-to resource for figuring out complex tech solutions?  Be ready to tell stories that are relevant to product management. If you are transitioning from software engineering, try using less engineering jargon and acronyms and highlight your experience using language from the product life cycle.

 

News:

-June 21st SBi-Lab Meet-up: Data Science and Entrepreneurship, for more information please email us at DT@uclaextension.edu

-Summer Quarter will begin on June 25th. You can enroll now!

image_print
Comments are closed.