Meet Angie Huetteman, a Data Analytics Tutor at CareerFoundry’s new self-paced, online Data Analytics Program. Angie tells us how CareerFoundry tutors and mentors support their self-paced students, the types of students who are most successful in data analytics, and her advice for finding your niche within the data analytics industry.
How did you learn Data Analytics?
I’ve been working in data analytics for close to a decade now and I’m self-taught! I was thrown into data analytics while working at a digital agency. I could see that data analytics was something our clients needed, so I ran with it. I learned everything from the ground up and every few weeks, I hosted a "Lunch and Learn" to teach my coworkers Excel, Powerpoint, or data points, etc. So it felt natural transitioning over to becoming a tutor at CareerFoundry. I enjoy getting my hands dirty with data, so in addition to mentoring at CareerFoundry, I also help companies create strategies for digital marketing, social media, analytics, and improvements.
As a self-taught data analyst, do you think it’s possible to learn data analytics at a bootcamp?
The bootcamp model is amazing! Bootcamp students are changing careers and investing in themselves. They take it more seriously than a high school student who's just going to school because they have to. Bootcamp students are eager to learn and get a job in the field once they finish the course.
What does it mean to be a Tutor at CareerFoundry?
The tutor is primarily the point person for students as they're going through the course. If students have any questions about the material or any of the tasks, I'm the person they reach out to. I’m also their cheerleader!
What is the difference between CareerFoundry Tutors and CareerFoundry Mentors?
CareerFoundry has a great support system in place for students: there are tutors (my role), and mentors, who act more as career advisors and give practical advice to students. As a tutor, I review weekly tasks while the mentor reviews a student’s final projects. The mentor gives job advice to students, while my role as a tutor is to make sure students have all the necessary skills and techniques down so that they are job-ready.
How do you communicate with your students?
We have a Slack channel where students can interact with one another, their mentors, and their tutors. I evaluate my students’ tasks and give them the feedback they need to make their assignment perfect or give them a pat on the back once they reach that level. I talk to each student about three times per week. Some students are more eager while others that have more responsibilities on their plate and so they take it a bit slower. All CareerFoundry students have the flexibility to work at their own pace.
What’s your teaching style?
Everyone learns a bit differently, so the team that oversees tutors and mentors offers us teaching resources with different ways students can learn the material. These resources show us what teaching methods worked in the past and techniques we can use to help our students now.
What does the Data Analytics curriculum look like? Which languages and technologies are you teaching?
The first part of the curriculum is a simple introductory course on how to analyze data and an overview of using Excel. In the intro course, students analyze video game data from some of the most successful video games of all time. They'll look at how sales differ based on geographic regions, platforms, publishers, or genré. Each exercise takes them a bit deeper into analyzing that video game data set toward their final project.
Then there's the immersion course, built off of six different achievements with ten exercises each. At the beginning of the immersion course, students are analyzing Influenza data. They'll see how Influenza has spread in the past geographically and put together a plan to utilize healthcare staff as best as possible. The immersion course takes about 6-10 months to complete. The curriculum gets into analyzing data, visualizing data using Tableau, SQL, Python, and working with big data.
How do you assess student progress? What do you do if someone is falling behind?
Every task that a student turns in gets graded by a tutor, like me. We have rubrics that show what an approved submission looks like and what would need more work. Everything is structured and the students have a clear expectation of what they need to do to get an approved task.
It takes students five to six hours per week to do all the assignments. That said, students work at their own pace, so if there's a student I haven't seen in awhile, I'll reach out to them. They might be struggling with the curriculum or with something in their personal life, so I try to keep them motivated to complete the course. Sometimes we reach out via an email, sometimes we communicate via the platform or Slack. If it is an issue with the course, we can usually address it.
What kinds of challenges could someone run into while learning data analytics?
Learning all the tools and programming languages! Excel is the standard for data analysis, but as you go deeper, there's Tableau and Power BI for visualizations, and Python and SQL for data mining and advanced database analysis. Learning all of those things can easily become challenging for a beginner.
How will the Data Analytics course stay up-to-date?
CareerFoundry’s Data Analytics course is the newest one. With the ever-changing field of data analytics, we know there is always room for us to improve it. I take feedback from the students who are going through the program and CareerFoundry makes continual improvements. The curriculum team makes sure to pay attention to updates on tools and platforms.
When I began my career in data analytics, big data wasn't even a thing. Now analysts are faced with massive amounts of data and the struggle becomes managing all of it while determining what data is useful and what isn't. I expect data analytics to continue to evolve in this manner as more and more of our lives become digitized, but also see limitations as privacy over one's data becomes more of a priority.
Is there a certain type of student who does well in Data Analytics?
Generally, you need to be a curious person to be a good data analyst. You need to want to know why numbers are the way they are, why things change, and look for what happened to be able to explain an event. A natural curiosity will serve you well in data.
I recently had a student complete her Intro to Data Analysis course and she was a true gem. She has a background in education and was eager to break into a new field. CareerFoundry was the perfect spot for her. She completed the course at near-record speed and her drive to succeed was something that I won't forget. She put so much of herself into getting a new career, and I have no doubt she's destined to secure a job in data analysis before long.
Could a complete beginner enroll in the Data Analytics bootcamp and go on to get a job? What kinds of jobs can CareerFoundry Data Analytics graduates get?
There's no prerequisite necessary! The curriculum is written so that someone with as little as a high school diploma could jump in and understand things. The intro course does a great job of giving an overview of data analytics and Excel. Even if you've never looked at a spreadsheet or analyzed data, things will make sense and you can be successful.
CareerFoundry also has a whole career department that helps students get jobs. 96% of eligible CareerFoundry students who complete a course get a job in the field! Graduates can go on to become financial analysts, marketing analysts, business analysts — It really depends on a student’s interests. Others may want to keep developing their skills and get into data scientist roles. Every industry has data that needs to be analyzed, it's just a matter of finding the right job for the industry that interests you.
What’s your advice for Data Analysis bootcampers?
It's important to choose a specialty. You can work in marketing, financial analysis, political analysis, automotive data, and so much more. Once you have your basic data analysis skills, practice those within your industry or niche. Narrow in on your interests. It will help you feel comfortable dealing with the types of data that you want to work with.