After publishing a blog post about my experience choosing and preparing for data science boot camp, I have gotten many follow up questions, especially ones about life after boot camp. For these people who are considering boot camp, I am hopeful that these blogs and my YouTube channel will help answer some of these burning questions. Though everyone situations differ, I also give some general advice about going to boot camp.
TLDR/TLDW, my top advice to prospective boot campers:
Establish connections with the faculty and staff of the boot camps you are considering in order to get a better sense of whether or not it’s what you need/ and to establish trust and communication with those people.
Look at the job placement record of the boot camp. If they have placed many people at the company or any companies that you want to work at, then it’s probably a good sign that this boot camp will work for you.
I think the boot camp is for people with high drive and discipline, people with plenty of time and energy and people who love to learn and challenge themselves.
Here are my answers to FAQs:
Question #1: Is boot camp worth it?
Yes, my boot camp experience was definitely worth it. I am very satisfied with the education and mentorships I received. I found a job after a 2-month period of being unemployed. To be transparent, I received a large amount of financial assistance, which also reduced the stress and uncertainty of attending a costly program. My situation at the time when I attended boot camp afforded me the time, energy and focus to fully engage in the curriculum and I learned a lot. But I think the question about the worth or value of any educational endeavor depends on your goals. Consequently, without having specific goals, the question of value is hard to determine. If you plan to attend a boot camp in order to get a 6-figure job (right after finishing), then you will be disappointed. But to expect that 6-figure job after 5 or more years on the job is more realistic. Most boot camps promise to deliver a job after you graduate, so if this is what you want/need, then compare boot camps to traditional education as well as on the job training and self-teaching. Boot camps are the best option among these paths for getting into a job in a tech field quickly and effectively.
Question #2: Are you happy with your job?
Yes, I am very happy with my current job, but it took me some time to get here. My first two jobs were contractor positions that I was not in love with. In my first job, I was working on Excel VBA scripts. Eventually, I left this job and I took an opportunity to work at a larger company because I saw better career opportunities there. My second job was on a design team doing front end development and data visualization work. I liked this work but it also wasn’t what I wanted to do in the long run and I only used this opportunity in order to get my foot in the door at this company. I was then able to switch teams at this same company and work on a data analytics team. I was working on data visualizations and I enjoyed the work a lot. But there were some very repetitive and mundane aspects of this job. Recently, I was able to switch to another team, which is data engineering work. I love my team and boss and being able to learn tools and new skills. I’m also being supported/groomed into becoming a machine learning engineer or data scientist in this position. So I am very pleased with this.
Question 3: Do you use skills you learned from boot camp in your job?
Yes, I use some things like Jupyter notebooks, PySpark, Tableau in my current job and also general knowledge of machine learning models is very helpful because I work on operationalizing models. However, personally, I don’t believe it is possible for your first job to match 100% with all the technical skills you learn at a boot camp. First of all, boot camp teaches either a generalized set of skills or else a highly specific software/technique. Any given job in the tech industry will never 100% match with that you study in boot camp because lots of jobs are either a very specific role, i.e. Tableau developer or a React developer, or else a generalized role in which the tech stack (group of technologies that a company/person uses) will vary widely. Don’t get hung up on technical tools. They vary too widely and change too often.
Question 4: Dislikes about your job?
I disliked repetitive and mundane tasks in previous jobs. I dislike the politics of corporate work and the draining aspects of professional development in this setting (i.e. meetings).
Question 6: What to study to supplement learning during and after boot camp?
During boot camp, I personally did not do a lot of extra work. I needed to take care of my physical and mental health so I limited my time online. I actively engaged in all of the curriculum during the boot camp, and I believe that as long as you do this, you should be okay. Towards the middle and end of the boot camp, I started applying to jobs and this took up a lot of time. I tried studying and completing coding challenges on popular websites but I was easily frustrated with them and didn’t spend a lot of time on this. The only thing that I truly would recommend in terms of extra work during boot camp is cultivating projects and skills in your desired specialization. For me, this was data visualization.
After boot camp, I continued to apply to jobs and started to work on personal projects. This was a lot of work in itself and probably THE HARDEST part of boot camp. I.e. right after graduating is the most difficult part because of the incredible uncertainty and absolute frustration with an inadequate and unfair HR/job interviewing paradigm. But I kept myself sane by focusing on my health and physical fitness. I developed two small data visualization projects and spent most of my time applying to jobs. It’s hard but sticking to a scheduled routine helps as well.
I am hopeful that this helped answer some questions regarding coding (data science) boot camps. Though everyone situations differ, I think that this route is good to consider if you want to quickly launch a new career and if you have the time/energy/focus to commit to intense study. If you have any other questions or concerns, please contact me at email@example.com.
I recently made a career transition from artist to data engineer and wanted to share what I learned. By sharing my personal journey, I attempt to give my best advice based on entering the tech field as a newb and I am hopeful that this will help and inspire others.
TDLR, here are my 5 key lessons. Below I elaborate on each in detail.
5 key lessons
Lesson #1: Don’t try to work at a FANG (Facebook-Amazon-Netflix-Google) company just for the prestige or money.
Lesson #2: Don’t apply to a company unless you know their values, products, investments and ethics.
Lesson #3: Pick out a group of job titles that are suitable for your skills and education level.
Lesson #4: Start searching where you currently live or a few places where you could realistically live.
Lesson #5: Knowing yourself and your strengths will help you create your professional identity and get where you want to be.
Why the Job Search
At the heart of my job transition in 2009 was an existential struggle to find myself in a capitalist society. In my twenties, I didn’t give a damn about money or my net worth. I only wanted to make art. But this commitment to art (and not money) left me broke and burnt out. I struck out to find a suitable and profitable job, but it was hard because I lacked an identity and purpose in any professional field outside of the fine art world.
In order to find a job in the tech industry, I had to re-invent myself to properly land in a company and position that was right for me. Properly understanding my strengths, goals, skills or lack of skills and values was just as important as knowing how to write a resume and cover letter, interviewing and etc. In other words, the job application tricks were not as important as “finding yourself”, i.e., crafting a professional image of oneself. It’s not only about a job title but instead about purpose, motivation and values.
Of course, the tricks of job hunting are extremely valuable because job hunting is not easy. There is little transparency in hiring practices and even worse, unjust and prejudiced practices everywhere. Despite this unfairness, I was able to find a job and I will share my journey by deconstructing the job search.
Finding a Starting Point
I sought out help from a family member (my cousin Sam) who worked as a software developer. She helped me find a starting point in the form of a set of questions: What kind of company are you willing to work for? Do your ethics align with theirs? What kind of position are you seeking? Where do you want to work?
Seems like a really simple set of questions. But you won’t believe how many people get these wrong or simply neglect them altogether. Most people just hop on a job board and start applying to anything that looks remotely interesting. I started doing this at the beginning. But I would advise against it.
Also, out of pure naivete and ambition, I wanted to work for a FANG (Facebook-Amazon-Netflix-Google) company. I didn’t know much about the tech industry besides a handful of companies that I use in my everyday life, so I really didn’t know how to begin looking and I wasted a lot of time pointlessly applying to jobs at FANG companies.
When you are brand new to the industry, however, it’s confusing to start thinking about where to work. For me, I was not only brand new to the tech industry, I was also completely clueless about working in any industry.
How to tackle these 4 important questions
Question 1: What type of company?
There’re a few ways to think about this. There’s the private sector and the public sector. For-profit and non-profit. Big corporations and small companies. Startups and everything else. Each has its pros and cons. For a beginner, its best to seek employment in a large to medium sized company because there’s room to learn on the job and be mentored.
The question of what kind of company do you want to work for is an essential first step your job search. I uncovered that I was naively clinging onto the idea of working at a FANG company because of the money and prestige. This made me realize that there are other considerations like culture, leadership, diversity, work-life balance, mentorship and resources for training that I needed to figure into my search.
Lesson #1: It’s a big mistake to want to work at a FANG (Facebook-Amazon-Netflix-Google) company just for the prestige or money. You will set yourself up for disappointment if you are blindly seeking jobs at a FANG company. Take the time to research companies and don’t be afraid to work at a company that isn’t well known. (More on why FANG isn’t for everyone later.)
For me, I thought it would be fun to work at a startup. But then I learned about the work strain involved in being a part of a small startup team where each team member bears lot of responsibility.
I shunned the idea of working for a big corporation because I didn’t want to support a money-making, soul-sucking company. So I thought that working for some type of non-profit would be best for myself. But then I quickly learned that there aren’t many good paying or entry-level jobs in the non-profit world.
Not knowing what else to do, I created a large spreadsheet with lists of companies that I liked. I found them by searching for lists of best ranked companies to work for and best ranked companies for LGBTQIA folks. I spent time looking at who worked there, whether they support causes that I do, and what kind of products they create. One easy way to begin filtering out companies that you dislike is to go onto LinkedIn and view their employees and leadership. If there aren’t many women or people of color in leadership roles, then I personally would pass on the company.
Ultimately, I decided to target large companies in order to have mentoring and continued learning available to me. I reasoned that a larger company would have room for learning on the job and mentorship from more senior members. So far, I have found this to be true.
Question 2: Do your ethics align with theirs?
It is important to consider whether you could ethically stand working for a company. For example, would you be willing to work for a company that has a history of unfair compensation practices? E.g. Facebook? (= Privacy concerns) Uber? Door Dash? (= driver pay concerns), etc.
Lesson #2: Don’t begin applying to jobs unless you know the ethics (values, products, vision, work culture) of the company and don’t apply unless your ethics align with theirs.
Sure, most people may not have the luxury of being able to work for the company of their dreams. Most people just need to earn a paycheck. But for me, in order to have a modicum of integrity and motivation, I want to know that I am working for a company that I ethically align with. It’s not just about the paycheck. If you can’t honestly say that you support the product or mission of the company, then don’t waste your time applying to a job there.
Some may call this question of ethics a question of culture fit. But I think it’s more than that. I believe that ethical alignment means that you support the products, practices and individuals employed there.
Of all the considerations that I am writing about, this question of ethics is the most difficult to discuss because its fraught with issues and complexities. So I will just leave it at this. The lesson here is to know the company’s ethics/vision and know your own ethics/vision.
Question 3: What kind of position are you seeking?
Based on your education, training and skills, you should begin to craft a list of job titles that would be best for you. Have a very ambitious plan here. Don’t hold back. Ideally, you can get help from a career advisor or someone who works in the industry. You should know what a career progression might look like. For example, data analyst to business analyst to data scientist to senior data scientist. But don’t worry if you don’t have it all figured out—the process is not always linear.
Lesson #3: Pick out a group of job titles that are suitable for your skills and education level. Be very ambitious in your planning but give yourself lots of time to grow into your career and be realistic about your timeline goals.
In the beginning of my journey, learned about data science and began to craft a career development plan as best as I could with limited knowledge and experience. Because I chose to attend a coding bootcamp for data science, I knew I was aiming for data scientist positions, but I learned over time that I could start at a different job title and quickly work my way up. So far, I have had with job titles like “Junior Developer”, “Web Developer”, “Front End Software Developer”, “Business Analyst” and “Data Engineer”. And I am currently on a path to become a machine learning engineer.
Again, the journey of job hunting is never linear. You may go back and forth through many stages and deepen your knowledge over time. In the same way, your career will not be linear either, especially if you are entering the tech field. Be prepared, however, by finding a career path and aiming high.
Question 4: Where do you want to work?
Be very realistic here because you need to narrow your job search. Pick a few places at most and begin your search there. With a narrowed and purposeful set of requirements, you will find it easier to navigate the hunt.
Also, it is always best to utilize local organizations, meet ups and education programs in order to tap into a local network. If you just finished school, then use the resources of your alma mater to find networking opportunities. Investing your time and energy into your local communities will not only help you find a job but it will deepen your sense of belonging, purpose and identity in the new field. This is extremely important, in my opinion.
Lesson #4: Don’t be idealistic or reach for far flung places when you are considering where you want to work. Start with where you currently live or a few places where you could realistically live.
I was living in San Antonio, Texas when I began to self-teach and went to a coding bootcamp. When I graduated from this bootcamp, I began a nationwide search for jobs in the data science field. I had a few phone interviews with out of state companies but I ultimately got my first job in town through a local coworking space’s Slack channel.
At first, I really wanted to find a job in a cool city like Los Angeles or New York City. But I quickly learned that there’s a huge disadvantage to applying to jobs in locations where you don’t currently reside. Without many years of experience, I was mostly wasting my time. I also found that moving was a commitment that I couldn’t really make financially. Ultimately, I found a job in the city where I lived and it was the most beautiful thing ever.
Finding a Job Through Bootcamp – Shit Gets Real
Lesson #5: Knowing yourself and your strengths will help you create your professional identity and get where you want to be. Craft your image into a professional and you will become one.
While I was attending the data science bootcamp, I had a career advisor, Mary, who was exceptional and highly competent. This school was well known in south Texas and had a well-established network with local companies. That’s why I decided to go there.
However, it was very frustrating to not know a damn thing about the industry I wanted to work in. I attributed some of this frustration to Mary, at first, thinking that she should be a better educator in addition to a career advisor. Alas, now that I think back on the experience, I know that she was doing excellent work in her job, which was not to educate per se but to rather network with companies and discover opportunities for me.
Learning about a new industry takes time. As I struggled through a few interviews that Mary had set up for me, I was continually researching, applying and refining. All aspects of the job application process are challenging, but as it progressed, I was also grasping at deeper questions about myself and who I wanted to be.
I started to see what my career trajectory might look like. I began to weed out companies that I could not stand to work for. I deeply examined my experiences, skills and talents and began to realize that the image I had of myself was slowly changing and I wanted that image to be reflected back to me in the company that I worked for. Creative, astute, productive and successful. That’s how I saw myself and that’s what I wanted to see in the company I worked for. But it wasn’t so easy.
I owe a lot to Mary and the bootcamp I attended. I was groomed and trained to tackle most aspects of the job hunt. Professional headshots, LinkedIn profiles, new CV’s, job fairs, interviewing. Most importantly, I was forced into meeting and networking with professionals, which is hard for a socially awkward introvert. I was able to put myself together as a newly minted data scientist by not only utilizing the resources I had but also by taking ownership of expanding my knowledge of the industry and metamorphizing into a new person. (Professionally at least.)
I talk about the bootcamp experience in my other articles. But I will say that the bootcamp is the best means to finding a job in tech if you are completely new because of the network they have already established. Mary taught me that the single most important step of finding a job is putting yourself out there in a ready state. Purposeful optimism helps.
Finally, Getting a Job
Earlier when I discussed my desire to work at FANG companies, I argued that there are many different aspects of a company that need to be considered before applying to jobs. It’s not just about the prestige or amount of money you make. To further elaborate, I learned over time that there are certain types of jobs that only exist in large companies. And that these types of roles involve the products and inner working of the company itself. Once you attain skills and experience in your career, then you expand your knowledge of the roles and responsibilities of different jobs and how a company actually works.
I learned in my first year in the industry that there is a dichotomy in the data science field (and other fields in tech) between “researchers” and people who implement the stuff that researchers make. In other words, there are those who develop new algorithms and then there are the people who use those algorithms in the real world. When I was just beginning my search, I did not know this, and my cousin Sam helped elucidate this further. This dichotomy reflects the difference between research/infrastructure and feature/user-facing work.
Learning never stops in the tech industry. Consequently, your skills and knowledge are constantly changing. In my experience, I dispelled misconceptions and myths about the tech industry by slowly learning and experiencing it. One of the most important myths was about FANG companies. They are not for everyone, but if you are aiming to work in research/infrastructure (i.e. creating new algorithms), then a FANG-like company may be best for you.
The whole process of finding a new job is transformative though extremely difficult and stressful. The secret to finding a job is being in a state of readiness, having purposeful optimism and maintaining a clear identity in the field. In spite of the deficiencies of hiring practices, crafting your truth, purpose, and ethical views as a data scientist (or whatever) will guide you to the right people.
After all the struggle of finding my first job, I also learned that job searching never stops. I got my current job because I got internally promoted at my current company. The only reason I was able to do this is because of networking, a fundamental skill for job hunting.
No matter where you are in your career, you will always be job searching and consequently you will always be networking. Good networking requires you to be resourceful and inquisitive. Never stop networking. Never stop having purpose and building your identity along with your career. Best of luck.
The psychology of uncertainty is the biggest challenge when searching for a job. There’s ups and downs and rejection. In this article, I will describe my approach to job hunting, including goals, tips and techniques I used.
I landed my first job in technology after about a year and a half of learning to code, including a 4.5 month coding bootcamp. I was lucky to have a career advisor / advocate through the coding bootcamp that I attended. But even so, the process was difficult, long and unpredictable.
TDLR; Having an effective resume, using LinkedIn and actively networking are the most important tools for finding a job in tech. Here are the stats:
Number of days actively applying
Number of applications sent
Number of phone interviews
Number of in person interviews
Number of offers
Number of rejections after interviews
Ghosted after phone/in person interviews
Success rate (success=job offer)
My job hunt
Creating a great resume in four different formats is essential: one page resume – both for a human reader and a machine readable version – and also a two page resume – both for human and machine. Since I have a background in fine arts and design, I created something myself using Adobe Illustrator. If you don’t have design skills, then it is safe to rely on online templates but remember to customize layout for your specific strengths. For example, if you have little to no work experience but good projects, then list your projects at the top and the work experience at the bottom.
A less ethical hack is to copy, paste and hide / mask the job description with all its keywords directly into your resume so that when the resume is parsed through a machine reader, your resume will pass any screenings. Because I don’t know the efficacy of this hack, I wouldn’t recommend it. Also, I tried it and it didn’t seem to help so don’t waste your time.
Any introvert knows that this is the worst part about finding a job. I went to several job fairs and struggled through them. These job fairs did not lead directly to a job offer but I believe that in some mystical, intention-setting way, they helped me find a job. I would only recommend a job fair to someone who has researched every company that will be in attendance and someone who had a solid set of business material to hand out and a confident mastery of their own skills and what they can offer to a company. What this means is that you know how to sell yourself, or to put it another way, you know how to describe your skills and goals as a professional in your field. If you are less confident about yourself, but can still BS your skills, then give it a try. But it is essential that you research all companies in attendance and genuinely want to work for them.
Here’s the thing about networking—it’s a reflection of the wildly inefficient system that networking remains the best and most vital way to find a job. You have to know someone to get your foot in the door. So this means that applying to jobs through online portals without knowing anyone at the company is useless. It sucks to hear/know this, but it’s true.
As a hardcore introvert, it took me a long time to realize what networking really is. I work best one-on-one. So ‘networking’ was always a nightmare. Here’s the basic idea though: Let’s say you want to meet and interact with 100 people. Doing this one person at a time will take awhile… Let’s say that at 1 person per day, it will take 100 days (since you gotta walk around and find a person willing to really speak with you)! But if you use networking and meet 5 people and get to know them well, then you can leverage each of those 5 people’s networks in order to gain access to a myriad of other people. Let’s say each of those 5 people you met has an average network size of 50, then you gain access to 250 people with only the amount of work it took to meet 5 people! Magic! That’s only 5 days to meet 250 – whereas with the one-by-one approach it took 100 days to get 100 people. It’s obvious that this method of leveraging people’s networks is more effective.
Okay, so now that I explained how important networking is, my last two tips are about networking.
You have to get LinkedIn Premium (or free trial of it) in order to be able to send messages to people. Aim for contacting one person a day about opportunities at the company they work for. But you have to be strategic about it. Don’t just copy/paste generic messages in bulk to randos.
Here’s the strategy I took with LinkedIn. I applied to a lot of jobs through company websites, not knowing what I was doing. But for each company and job that I was really excited about I hunted down a person from that company and sent them a message using LinkedIn. I either found a HR person or a data person since that’s the field I was entering. I asked to speak in person with them, inviting an interview opportunity and showing confidence and initiative.
This method of cold-calling someone is controversial. But I was able to get interviews this way.
Friendship / sanity
Like I said before, the job hunt will test your sanity and morals. Making friends with other job-hunters is a good way to keep yourself from isolation and depression. Just having someone to speak with about the struggles of job hunting is the best way to cope with the emotions.
I was very lucky have friends from my bootcamp. I organized an ‘accountability buddy’ group with friends who were also searching for jobs. We met in person once a week to sit together in a café and apply to jobs and talk. I would recommend doing the same or at least having a mentor or someone to talk with about your process.
Lastly, and most importantly, you must give yourself time to go through the process of finding a job. And it is a process.
The best piece of advice I ever got was from a former art teacher. “Favor yourself with your time”. Give yourself plenty of time to go through the process. You’ll get better results and, although it is hard because your livelihood is on the line, trust that everything will work out in the end.
In about a year and a half (counting self-teaching), I went
from earning around 28k as an adjunct professor of art (plus side jobs) to
earning around 70k as a developer.
I will discuss my background and the possibility that you
can achieve a similar career change. In general, I highly recommend coding
bootcamps to enter the tech industry. But it is a difficult task and it’s not
to be entered without adequate preparation and planning.
In this article, I will focus on a bigger picture discussion of why and how I changed careers. I have written other articles that discuss the online courses that I completed before I attended data science bootcamp and a review of the bootcamp I attended. For these articles, please refer to my blog.
In short, the reason I jumped on the bandwagon is because I
was financially dependent upon my parents and not earning enough to live
independently. In this sense, I am a typical creative millennial. I have a few
prestigious (useless?) degrees in art and philosophy. However, a few years
after completing my graduate degree, I found myself broke and very lost
I taught fine art as an adjunct professor for a few years
but this was sporadic temporary work without any benefits or job security. So
while I was teaching and living at home with my mother, I started to research
careers, taking personality and strengths tests and creating lists.
The internet told me I would be a good accountant or
software engineer. Then I somehow discovered data science and after reading
about the field in depth, I knew it would be good for my personality and
strengths. So my first piece of advice is to know your strengths, weaknesses,
personality traits and how they would best suit a potential career.
Now that I knew what I wanted to do, I needed to tackle how?
I thought about going back to school to get another Bachelors or Masters
degree. But then I learned about bootcamps and I was convinced that this was my
best option since they are faster than traditional schooling. My second piece
of advice is to consider all your options for educating yourself. Bootcamps are
the quickest way into a job.
The decline of the traditional education system should not
be understated. During my higher education, while I was very well taken care of
because of my privilege, I was not trained nor guided to any specific career.
My parents were supporting me financially and although they wanted me to become
a lawyer, they supported my decision to pursue fine arts as a profession.
My higher education taught me resourcefulness, great
learning habits, adversity and hard work. I did not take any internships. I did
work study jobs and aspired to do creative and intellectual things as you do in
prestigious institutes of learning. But frankly I was very depressed and
struggled through most of undergrad. In the end, I learned more about myself
than about career and the real world.
So my belief in bootcamps stems from an appreciation of
their efficacy but also I acknowledge the purpose and strengths of traditional
higher education. Bootcamps are specifically designed for placing students into
jobs whereas higher education advances personal development and intellect (for
Getting back to my point, I was enabled to find a job in the
data science field in such a short period of time because of the bootcamp I
attended and because of the self-teaching I did beforehand. I doubt that I
would have been able to be so successful in the bootcamp if I had not gone
through undergrad/grad school and self-teaching. My strengths in math and logic
helped me get through the dense statistics and machine learning algorithms.
The biggest challenge of bootcamp is the speed and intensity
of the curriculum and the tenuous job-hunting period after graduating. No one
tells you that the job hunt is the hardest part because it’s a psychological
battle that creates self-doubt, competitiveness and uncertainty. My third piece
of advice, if you attend a bootcamp, is to make sure you find one that has a
great career advising team that will guide you through the entire process.
In the end, bootcamps were created because of the high
demand for skilled workers and the training you receive is highly valued. So if
you are thinking about attending one, please consider it seriously and find
people who have gone through it to discuss your questions.
I am hopeful that this article will be helpful for those of
you who are actively searching to advance or start your careers in the tech
world. If you have any questions, please reach out!
I graduated from Codeup in June 2019 as part of Ada cohort,
the first Data Science cohort. In this article, I will review Codeup, giving
pros and cons of the school with some attention to the data science program in
particular and also discuss my experience in the program. My opinions will
differ from others because of my particular background. I am an artist, a
self-taught programmer with less than 1 year of experience with Python (at
start of program), and I have a very privileged educational background. I am
from San Antonio, TX (where Codeup is located) and was living there before I
attended, and I got generous funding to attend the data science bootcamp.
TLDR: Codeup is a great school with many resources and great
instructors. I believe the great curriculum, instructors, network and potential
for financial aid make the cost worth it.
I first heard about Codeup, a small career accelerator
school, because of their web development program. When their data science
program was announced, I was very excited. The staff and instructors at Codeup
were my first selling point as I was really impressed by their Senior Data
Scientist, Maggie Guist, and their Director of Strategic Partnerships, Stephen
Salas. Before I applied to the program, I visited the campus and met with
Maggie. Like when previously choosing what graduate school to attend, I
followed my instincts by seeking out cool instructors and people that I get
The application process was straight forward with small
technical tests, short answer questions and longer essay questions for
scholarship applications and finally a phone call interview with someone at
Codeup. In my case, I spoke with Stephen Salas. I got accepted and during my decision-making
process, I had to determine my financial aid situation because I had no money.
Codeup recommended a number of financial aid options including government
grants, scholarships, and personal loans, which was the worst-case scenario. I
wrote about the financial package I got in the previously mentioned blog post.
In addition, I spoke with alumni from the web dev program
and learned about the pace of the program and the experience of attending a bootcamp.
I was terrified of choosing the wrong thing to study. Would I really like it?
Was I giving into corporate, capitalist America? I found that most people I
spoke with really liked Codeup and found the whole experience transformative in
a positive way.
I accepted and secured my spot in the program and we were
given a number of online courses for preparation. I had 2 months to complete
them and I went through all the courses carefully. Ultimately, when we started
the program it was very slow at first. I was expecting this because of what
others told me. The first week of the program were exciting as we focused on
understanding the full data science pipeline but then it quickly got boring as
we learned the basics of Python. However, I was appreciative of this ‘slow’
time because I really struggled with
the 9-5 routine. As the program progressed and we did our first projects with
real data, I became somewhat depressed as we were tackling business concepts
that I didn’t understand. Everyone else in the class seemed to understand
business principles like churn, attrition and customer acquisition and even
excel at giving insightful business recommendations based on these and other factors.
But having no experience in ‘business’, I struggled with this the most.
So my first critique about the program would be lack of
teaching business concepts and I’d recommend more business oriented
While the program progressed from Excel, Python, basic
statistics, and SQL, we moved into the fundamental data science methodologies.
This was the meat of the program and what I enjoyed most since we got a good
taste of different methods in data science practice. We had regular group
projects on each of the methodologies we learned, which was useful and
instructive. Each project was followed by a class presentation which was very
nerve-wracking. But by the end of the program, it got easier and we all started
to excel at this.
The second critique of the program was time since we didn’t
have enough to cover some topics and the last few weeks of instruction were
very rushed. However, they changed the program length to address this already.
The last two weeks of the program were wholly committed to
completing a group capstone project which we were able to design ourselves. But
since these were group projects not everyone got to work on a project that they
designed. Finally, we presented our findings to a group of employer partners at
the very end of the program. Because I am interested in design research and I
got to design a project idea that I was passionate about, I found the capstone
project proposal process challenging, fun and exciting. At times the process
was confusing to some people and maybe even unfair if someone’s project was not
chosen. However, the overall experience of working in groups was undeniably
valuable and the instructors did a fantastic job creating groups and guiding
our capstone projects.
My experience of Codeup was positive overall. The best parts
of Codeup were the instructors and staff, the very smart students that I met
while attending and the large network of partnerships that they have
established over the years. In particular, their relationship with local
organizations helped me find enough financial aid to attend, which was
incredible. They also offer scholarships that were very useful.
If you have any questions about Codeup or bootcamps in
general, I’d love to help if I can and you can email me at