How This Developer Upskilled His Career with Berkeley Data Analytics Boot Camp

Patrick was a mechanical engineer before he pivoted into software development. When Patrick chose to upskill by learning data analytics, he enrolled at Berkeley Data Analytics Boot Camp, offered in collaboration with edX, for their live online classes and career services. Their curriculum and career coaches lived up to his expectations, equipping Patrick with the relevant data skills he needed to advance his tech career. Learn how Patrick is using his new data analytics skills now on the job as a full-time Software Developer at SandTech Solutions!

You’ve been working as a software developer for a few years — how did you initially launch your career in tech? 

I have a master's degree in Mechanical Engineering, and after grad school, I was working for a mechanical subcontractor. I realized mechanical engineering wasn't a good fit for me, so when I heard about the critical need for software development skills right now, I pivoted into software development. I had enjoyed my software classes at college, and I decided I might be a better fit for computer lab work than field work. 

To begin my career change into software development, I enrolled in two, different software development bootcamps at Udacity, where I learned Python and JavaScript. When the pandemic hit, I wanted to continue expanding my skill set before landing my first tech job. Looking at the Berkeley Data Analytics Boot Camp curriculum, I saw that there was a lot of overlap between software development and data analytics, so I thought the data analytics boot camp was an ideal choice.

How does mechanical engineering translate into software engineering?

Mechanical engineering is more focused on math and physics. There is a lot of math in computer science, but it's more discrete math and there isn't a lot of physics. The two do overlap, though! In my mechanical engineering college courses, we worked with some programming languages, like MATLAB, matrix laboratory, which helps with some of the more math-heavy subjects like machine learning. We had to take linear algebra, calculus, and the background classes that you need to know for some of the artificial intelligence or machine learning classes.

I chose to learn data analytics at a boot camp in order to boost my skills without taking too much time. With the data analytics boot camp, I was able to build on skills I already had while elevating myself within the field. I considered self-teaching, but I found it hard to get started with projects. While boot camps do cost more, they offer the guidance, scheduled curriculum, and examples of projects that enabled me to learn more effectively than self-teaching. 

There are so many data analytics bootcamps now – why did you choose Berkeley Data Analytics Boot Camp?

Having gone through other boot camps, I was familiar with what to expect but I didn't find myself prepared enough to work in the field. While they gave me experience with projects, I lacked the interview skills and depth that I found at the Berkeley Data Analytics Boot Camp. They have great, ongoing career support for their alumni to ensure graduates are consistently getting work. When I was looking for a data analytics boot camp, I needed that career security. 

Was it important to you that this boot camp was affiliated with Berkeley?

It was important to me that it was associated with UC Berkeley. I felt I needed the clout that comes with a top-tier academic institution to help get my foot in the door for interviews. My two instructors were from Trilogy (not from Berkeley). One of my instructors had worked at Amazon and came from a computer science background at a university. The other instructor was self-taught.

Note: Boot camp instructors are hired through 2U, but first must be thoroughly vetted by the university.

What were your career goals when enrolling at Berkeley Data Analytics Boot Camp?

Even though I went to a data analytics bootcamp, I actually enrolled to be a better software developer. There's a lot of overlap with Python and JavaScript in web development with web pages and servers. Before the boot camp, I had built a few data projects on the side. I wasn’t sure if I would use data analytics skills directly for work, but I figured it would help with how I approach projects and develop code.

What was the boot camp application process like? 

There was a quick multiple-choice quiz on some basics about languages, what they do and how they work. They let you Google answers if you need to. You could probably start as a total beginner and pass this assessment, but I don't know that it's advised.

Once I was accepted, there was some pre-work, and it involved getting familiar with some of the course topics and the syllabus. 2U advised us to get a computer for the class that met certain requirements, but they were flexible on that.

What was a typical day or week like in the data analytics boot camp? 

A typical week was a lot of work! They have different levels of how much work you need to do to pass versus get extra credit. Classes were four hours long and met three days a week. During the classes, we worked with our instructor through examples. 

They gave us notebooks to work on our homework, which we had substantial amounts of every week. Our instructors expected a pretty quick turnaround on homework, but they offered a lot of help setting up our assignments with good starter code. The starter code was able to be used on other projects and I'm even using it today on projects I'm working on. 

Since this is a part-time boot camp, does that mean students can do the boot camp while working a job?

I think it would be difficult to work and do the boot camp. You can definitely do it, but it would be a challenge.

Note: The boot camp’s part-time program is designed for people working full-time, but it is  rigorous. Students should expect to put in 30+ hours each week.

Did the teaching style match your learning style?

I found this boot camp to be a lot more interactive than other programs, with a lot more instruction time because we were in class for 12 hours a week. I was supported by my instructors and a TA. I had the opportunity to ask questions during class for clarification, and tutors were available outside of class to help with homework.

What did the boot camp curriculum cover? 

The curriculum included data analytics packages and languages, like Python, JavaScript, and SQL. About 80% of the main project focused on data analysis and data visualization, where we did exploratory data analysis, made reports or data dashboards using web tools like HTML, CSS, and specific packages within JavaScript, like Plotly, D3, or Leaflet for maps. 

We did data analysis and data processing using Pandas and SQL. We used packages like NumPy, Matplotlib and Pandas to do data analysis and cleaning, and then SQL for storing it in the database and being able to access it later.

Since this was an online boot camp, did you feel connected to your cohort? 

Compared to other boot camp experiences, it was easy to schedule time to meet with each other in the Berkeley Data Analytics Boot Camp. I’ve maintained contact with a lot of my cohort on LinkedIn. 

What kinds of projects did you work on in the boot camp?

We had about four projects over the course of the boot camp in addition to the weekly homework. Three of these projects were group projects. The instructors let us choose our own projects, which gave us an opportunity to get to know each other's interests, whether that was video games, finance, or anything else. I tried to work with different people on each project to expand my connections. 

Our group projects included an analysis presentation, a data visualization project, and a machine learning project. For my three group projects, my teams built: 

1. An air quality analysis presentation. We had a week to gather data on air quality in cities around the world, including the US, India, and China. We compared the pollution levels a few years before the Covid shutdown and during the Covid shutdown to see how much the pollution levels decreased during the three or four month total shutdown period. Then we displayed those results in a presentation.
2. A data visualization project. We built an interactive world map of venture capital (VC) startup funding all over the world that included: where the startups are located, how many are in each city, how much funding they get on average, and how much total funding the whole city gets from venture capital.
3. Machine learning. We researched a company in India that makes motor bikes, called TVS, and they also offer people loans to buy the bikes. We used Kaggle to identify customers who could potentially default so they don't offer them credit. 

The only individual project in the boot camp was an ETL (extract, transform, and load) project. For this I gathered data from Coinbase, one minute crypto currency data for bitcoin and ethereum, and stored it in a database. 

How did Career Services help you land your first job after boot camp?

Career Services emphasizes using LinkedIn to set up informational interviews, which is where I found my first software development role as an intern at a start-up. The careers team is transparent about their availability to help at any time, and were easily accessible to offer guidance on resumes, pitches, interview prep, and how to grow a LinkedIn network. They were amazing. 

You currently work as a Software Developer at SandTech Solutions — How are you using the skills you learned in the boot camp on the job? 

The job is pretty strict in terms of what we're allowed to do and build, compared to the boot camp where there was more flexibility and freedom with what we could develop and how we could write the code. At work, there's a lot more of a process with code reviews and people checking the code and controlling the product for quality. 

The database classes from boot camp have helped me on the job, such as working with JavaScript on the front end and understanding how the servers work and interact with the front end. In the class, we don't use the JavaScript framework, but we do use JavaScript, so that information was important.

The boot camp also taught us about APIs: what they are and how they transmit the data with JSON. A lot of what I learned about the database (how the database stores data, how you can retrieve data, how you can save and look up data ) is all part of what we do on the job.

How has learning these data skills helped you evolve as a developer? 

The boot camp offered immense personal growth and insight on different skills and tools I didn’t know before, such as Kaggle. I’ve been looking at their data sets and posting my own with good responses. It’s good to keep your skills fresh with side projects! 

I am noticing that small companies and young startups will hire someone who can do multiple roles so they don’t have to hire more people. Since I know enough about data analytics, AI, and machine learning, I might be asked to make a quick mockup of something to see if they can iterate on it. An expanded skill set means I can perform more responsibilities for different roles. 

Do you recommend that other software developers add data skills to their toolbox? 

I absolutely recommend software developers learn data skills. I would advise them to take free introductory classes in data analytics or data science first to make sure they're interested enough to stick it out in a more intense boot camp setting. 

Looking back on this experience, was enrolling at Berkeley Boot Camps worth it for you?

Definitely. I enhanced my skill set and expanded my professional network with good, hard-working people. What really stood out to me was Berkeley Boot Camps’ top-notch career support, who actively worked with me to get a job. I got hired within a few months of graduation, thanks to their invaluable suggestions and workshops. 

Find out more and read Berkeley Boot Camps reviews on Course Report. This article was produced by the Course Report team in partnership with Berkeley Boot Camps, offered in collaboration with edX.