Applications Programming Certificate
This 32-unit certificate program is designed to provide training in developing software applications. Students who complete this certificate will be able to develop software applications based on user requirements specifications. Students will learn to develop software code in high-level languages such as C#, Java, and others. They will be able to test, debug and execute their programs on a variety of computer platforms and operating systems. Emphasis is given to the use of object-oriented methodology in developing software applications. This program meets I-20/F1 Visa requirements and is VA approved.
- Java Programming I
- Website Development with Adobe Software, Photoshop, Dreamweaver, and Animate
- Introduction to SQL
- Programming in C# For Visual Studio .NET Platform I
- Programming in C# For Visual Studio .NET Platform II
- Three elective courses
This month we interviewed our newest instructor, Joshua Cook. Joshua has a Master’s in Computer Science from Georgia Institute of Technology and a Master’s in Education from UCLA. We are really excited to have him join our Digital Technology team.
UCLA Extension: Please tell us about yourself and how you got to where you currently are in your career?
Joshua: I have been in academia on one side of the desk or the other for most of my life. I love teaching and learning (and often learn more as a teacher then I do as a student). One of the things that really excites me about data science and machine learning is that it is so research oriented even when being applied to a real-world application.
I have been programming since I was a kid. I got my first computer, a Commodore Vic 20, in 1982! I really started my transition into data science, though, when I was teaching high school. I learned to code in Perl and wrote test generation software to use in my class. When I stopped teaching high school, I went back to school and got a degree in applied math. At this time, the data science boom was already underway so I was able to take a lot of classes in numerical python and scientific computing. About the same time, I discovered Jupyter notebooks. After school, I worked for a variety of startups and was able to develop a handful of machine learning models that are still in production. Last year, I returned to the classroom, this time as a data science instructor at General Assembly in Santa Monica.
All of that brings me to teaching the Data Science Intensive here at UCLA Extension. As a Bruin, I am very excited to be returning to UCLA as an instructor and hope to grow my data science practice by helping students begin and develop their own.
UCLA Extension: Is there anything you are currently working on that you would like to share with us?
Joshua: Last year, I published my first book, Docker for Data Science (Apress, 2017, https://www.apress.com/us/book/9781484230114). I really enjoyed the writing process and digging into a topic to develop a deeper discussion. I am currently working on my second book, Introduction to Linear Algebra with Python. I am excited to be working on this, not only because I really enjoy the writing process, but also because I have a great passion for the subject of linear algebra and especially its applications in machine learning and data science.
UCLA Extension: What excites you about this field?
Joshua: I love the combination of theory and practice that is data science. I love being able to dig deeper into the theory of a particular method, but that there is always a practical application to what I am learning in the end.
I also love the power of the techniques we are applying. Lately, I have been working with a technique called latent semantic analysis (LSA). LSA is a natural language processing technique that allows you to find hidden patterns in a large body of text information. For example, you could use this technique on all the tweets sent from the UCLA campus last week and start to develop an understanding of what Bruins were talking about. I just think it is so cool that you can apply mathematical modeling to something as open and unstructured as text data and learn things that are useful and understandable even to someone without an expertise in the field!
UCLA Extension: What advice can you give to our students trying to break into the data science field?
Joshua: Three things:
1) Stay curious and keep learning. This is a field defined by change. The ability to adapt can be almost as important as learning to understand the different models.
2) Never underestimate the linear model. With all of the fancy talk about neural networks and boosted decision trees, remember that regression is still incredibly useful and powerful.
3) There is always an open door for the passionate and motivated, but it might not look like what you expect it to. What I mean by this is, don’t hold out for what you think is the perfect data science job. Get your foot in the door and let your passion and enthusiasm for data science carry you to where you want to be.
Spring Course Preview:
HTML and CSS
Spring enrollment will open on February 5. Spring quarter beings the week of April 2, 2018.
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