Dr. Frances Boykin knew from a young age that her future was in data science. With unfaltering determination, she’s been working in the data science field for over 20 years. Now, it’s her personal mission to help others do the same at the data science and coding bootcamp Lighthouse. Learn how Dr. Boykin’s teaching reaches all her students within the Lighthouse Data Science & Analytics bootcamp regardless of their prior experience, plus her thoughts on the one field that bootcamp graduates should consider applying to now.
You got into Data Science before it was really a career path – how did you know that you wanted to get into data?
Data has been a part of my life since I was 13 years old. In the 1980s, my father was in the Army, so my family lived on the Army base wherever he was stationed. As an eighth grader on base, I was given the Army Services Vocational Aptitude Battery (ASVAB), a skill assessment test, and the top field in my test results was Data Science. I took it very seriously, learned how to type that year, and took a data entry class. I even worked on base in the computer room using keypunch machines. Then in high school, a female teacher told me that I needed to leave the computer science class to make room for more boys to be able to take it. I went home crying, and my father told me I needed to do something about it. I saw a sale for a $100 computer and with a lot of determination, I was able to buy one before they sold out. That’s how I continued teaching myself computer skills after I got kicked out of the class. I went to East Carolina University for a Computer Science degree, but dropped out in my Junior year because my then husband did not support me finishing school. I then took a job in the Engineering Department of the City of Rocky Mount North Carolina. With a new marriage came a push to finish my degree and I went back to school at North Carolina Wesleyan College where I received my Bachelors of Science in Computer Information Systems. With my new degree in hand I moved to Atlanta where I quickly found work at Hewlett Packard and later at a local utilities company. In the late 1990s I ended up at Nextel (formally Dial Call) and later Motorola and Verizon (formally GTE Mobilnet) which launched my career in the telecommunication industry and data science. By the early 2000s I was working for Bellsouth where I first applied data to marketing. I have continued to work in Marketing data science through the mergers and acquisitions of Bellsouth, Cingular, and now AT&T.
Why are you motivated to teach Data Science, and why at Lighthouse in particular?
I’ve taught computer science as a side gig for several organizations beginning as far back as the early 1990s. First I taught at at Edgecombe Community College where I worked to reskill workers at Sara Lee and Black and Decker. Then I taught at Georgia Piedmont Technical College where I still teach as an adjunct. I love teaching. It's an innate thing for me. I especially love teaching older adult learners.
I was motivated to teach at Lighthouse because I really believe in their philosophy. The Lighthouse philosophy is all about helping people for the sake of helping them, and that’s something I strongly relate to. It's about helping people get to where they want to go.
Have you noticed any difference in teaching at a bootcamp like Lighthouse versus teaching in a traditional classroom?
Yes, there is definitely a difference. In a traditional college classroom, the curriculum is regimented and you are not able to go with the flow of your student's needs. In a bootcamp classroom, I’m able to stop and take a poll to ask if the direction of the class is working for everyone. If not, I pivot. I just taught a six-week workshop that was supposed to be all Python based; however, at the beginning of the 3rd week I took a poll and found that everyone wanted to learn about R as well. So I covered both Python and R, compared them, and taught when to use each. For the last two weeks, we did a project in Python and the exact same project in R. You can't do that in a traditional education setting.
What is the Data Science & Analytics Intensive curriculum like at Lighthouse? What kinds of projects do students work on?
If you are looking for entry into Data Science, we provide you with the training to get there. The one question we hear a lot is, "how do I apply Data Science to what I do?" so we make sure to address how to take what you learn in the curriculum and immediately apply it. In the curriculum, we cover a few weeks of Python, R, and a little bit of SQL, but more importantly we talk about how to apply it to your day-to-day. We cover algorithms and market basket analysis. We do a little bit of statistics but not much; we only cover what’s really needed to leverage algorithms and Data Science concepts. As for projects, I make sure that the projects fall in line with what each student will do next in their career or education. I provide data sets that students can choose from and together we move the project from there. We use these projects to help students create a portfolio that they can use in job interviews, which is so important.
How many hours a week do you expect your students to commit to the part-time Data Analytics class?
Take the amount of time that you spend in class and double it. That's the amount you will be committing to your work outside of the classroom. So, if you spend 6 hours in class, you will want to spend 12 hours working outside of class. That is reasonable for a part-time program in data science.
How do you assess student progress? How do you help if someone is falling behind?
We don’t currently have tests as part of the bootcamp curriculum, instead we use projects as a means to test a student’s progress. I try my best to provide resources along with my own knowledge in an effort to help struggling students stick with the program and ultimately get the most of the program.
I check in with all of my students, but I check in on any students that are struggling even more often. I try to pair students up, too. If there is a person who is quite a bit ahead in my class, I leverage their knowledge by asking them to help the students who are falling behind. The advanced student feels great because they aren’t bored, and the struggling student is able to get peer support. When I do this, I make sure I give the student that is excelling in the class extra knowledge so they continue to grow as well. I try my best to provide everything I know of to help struggling students stick around and get what they need, but every student needs to keep in mind that to get their money's worth, they need to totally invest in their learning.
Do you think there is an ideal student for this Data Science bootcamp?
The ideal student is someone who is adventurous and invested in themselves. You can't build that for someone. You can only provide them with every resource you have available, but ultimately, it's up to them. It doesn’t matter what your background is, as long as you are someone who wants to learn data science, you will be a great student.
Do you have a Lighthouse student success story that you would love to share?
Someone recently attended a Lighthouse Data Science workshop with zero background in data science. She was a mature learner who was pivoting from a previous career. She had to go out and buy a laptop because she didn't have a computer at the start of the workshop. She was worried about whether she could actually get anything from the program and she also had fears about learning a new skillset, but we got her past all of that. By the end of six weeks, she learned enough of Python to present some of her solutions to class. She also pinpointed that she wanted to focus her Data Science career in Health Information Systems.
Do you recommend any resources or meetups that are available for beginners who want to start their career in Data Science?
Absolutely! I love LinkedIn. I push my students to create a LinkedIn profile, manage it, and use the groups on LinkedIn to become active. They also need to attend conferences. Atlanta Tech Village offers plenty of events and other opportunities that are great for anyone interested in tech.
What is your advice to bootcamp graduates who are looking to get into a Data Science right now? Do you think there are any "recession-proof" fields they should focus their job search on?
Data science is in its infancy in the health field, and they need data science professionals desperately. Go that route. In the medical field, they require you to have biology or a medical background, but it doesn't have to be a Nurse or Doctor. You can be a Medical Transcriptionist. Anything that gives you the knowledge of the lingo used in the healthcare field will allow you to leverage that.
Also keep in mind that with Data Science, you learn foundations and then leverage them in whatever field you go into. My own personal motto comes from the Steven Segal movie, “Under Siege: Dark Territory.” In the movie, the bad guy says, “Chance favors the prepared mind,” and I have never forgotten that. For me, it means that we should use knowledge to prepare us for the next phase in life whatever that might be. We might not always know exactly what is coming next, but we can pay attention and keep learning. Eventually, you will see which direction life is taking and be that much more prepared.