Meet Joseph Kambourakis, Data Science Immersive Instructor at GA Boston
How would you define data science in two sentences?
What do you love about data science?
I love being able to answer questions with numbers as opposed to guesses. I worked on a car telematics problem that helped identify problem drivers based on actual behavior and not past driving history.
What’s an example of what data science can and should accomplish in real life?
Data science can be applied in so many different companies and aspects of life. It allows you to process huge amounts of data to get answers that you could never achieve by hand. It also lets you find patterns in data to understand the underlying behavior of a system.
Why should someone learn essential data science your field’s essential skills at GA?
The Data Science Immersive is a great course for gaining real skills that reflect what companies need, such as Python and machine learning. The course is taught with tools data scientists really use and love. Our competitive advantage comes from having great community involvement, strong relationships with local businesses, and instructors with great experience teaching and working in the field.
Please describe exceptional strengths in GA’s curriculum, teaching style, and community.
Our curriculum is very fresh. The community is so nice, and I love all the peripheral events that occur on campus, such as game night and paint night.
What does a superstar data science student look like?
A superstar student is someone who explores on their own after class once they finish the assignments. The desire and curiosity to learn are what’s most important.
Why did the opportunity to teach at GA appeal to you?
I really appreciated how involved GA was in the local data community here in Boston. The team hosts meetups all the time and promotes the use of open-source technologies.
How would you describe your teaching philosophy?
I like to whiteboard a lot and get students talking. Students learn better from diagrams and speaking to one another than from a slide deck or straight lecture.
How do you help struggling students break through to meet or go beyond their minimum GA course requirements?
I am always happy to code up another example to help reinforce the topics. I had a student working on a project that covered material we hadn’t seen yet in the course, so I stayed late one day to deliver a personal lecture to him.
How do you push high-achieving students to go beyond the minimum GA course requirements?
I encourage them to self-study new topics and attend local meetups of cutting-edge concepts.
What are some free resources and tools a student can use to stay up to speed with data science? What is the best way to get practical, real-world experience in the field?
DataCamp and Big Data University both have great free resources. I also recommend attending meetups and hackathons.