My Inspirational Journey in Starting Data Science with No Code Experience through 12 weeks of Coding Bootcamp.

David Lee
11 min readJul 20, 2020
That’s me!

Tomorrow is my first day in a three month Data Science Immersive (DSI) program through General Assembly. I’ll be documenting the concepts I learn throughout the duration of the course to reinforce learning, to reflect on my experiences, and to share insights to those who are thinking of following my steps one day. I hope my progression from this point on will resonate with many as a message of hope, determination, and resilience in a time where many are losing their sense of direction in the walk of life post COVID-19. This article is primarily focused on some of my own life events up to this exciting point.

How it started for me:

I first learned the power of data after years of struggling to hit B2B sales numbers since the start of my professional life back in 2005. I was this naive, young and married 21 year old who was desperate to find any job which happened to land in Sales to start providing for my new family. I never fundamentally enjoyed sales and had many sales positions to be confident in a resilient effort on my part.

Warning: A short rant! Feel free to skip

I sought the wisdom of Sales Managers, Trainers, and training programs to increase sales , my closing ratio, and fill my leads pipeline with a great attitude and knowledge to master my trade.

I tried to accept all too common phrases in the B2B sales environment such as:

“Activity, activity, activity! The seven steps to the Sale! Handling Objections! Positive Attitude! Fake it til you make it! Etc…”

This meant more phone calls, more knocking on doors, more of pretty much everything, except repeatable business as time and focus on each client dwindled. Logs would then have to be made in CRM databases that I personally have seen filled with made up data by many former colleagues to keep Managers off their backs. I’ve also seen many instances of Managers that would hand off customer orders to the same Representatives based on variables that had little to do with effort or skill. For me, this was a failing formula which was cause for great stress and frustration!

I started documenting myself and made adjustments to try to help my chances to survive. It started with doing my very best in hitting these unrealistic activity standards of 50 telemarketing calls a day, 20 cold calls on new businesses, and 6 appointments in a rural sales territory, all on the same day. On my best days I would achieve close to 70% of these targets which also included proposals, and revisions to quotes I prepared after work hours, which at the time had roughly a 5–7 appointment average in my industry before a sale, along with order documentation. Needless to say, my real logged CRM efforts often led me to meetings with management letting me go for “lack of activity.” My sales territory, superior product knowledge, and unfavorable split of new to existing clients ratio had little impact on my “value” to the company.

Forward Thinking:

I find that its often the most painful experiences and unplanned trials in life that are the best opportunities to refine your values and change the course of the rest of your life, if you allow yourself to.

Fast forward to 2012-2014, things got much worse as my families’ 20 years retail business and 10,000 sq/ft building was lost, along with 3 beautiful 3,000 sq/ft houses we had mortgages on due to the housing market crash, student debts, and other factors. This is something I’d like to elaborate on in a different series of articles one day, but long story short, my wife and I were forced to take some drastic measures to survive, including sending my son to live with my parents, who became Full-time Independent Missionaries in Peru at the time (truly amazing people with a better story than mine, they are now in the Philippines serving the impoverished).

While my son was with my parents for 6 months, my wife and I closed down the store and short-sold/ foreclosed two of our residential properties, living in the last house which was in foreclosure for 3 years not knowing when we would receive an eviction letter.

My son Eric on the right with his class mates in Peru.

I had gotten another Sales position being taught the same strategies and activity levels I’ve heard many times before. I knew from the start that I had many of the same obstacles, but I took a very different approach this time around.

I learned how to use Excel better!

I realized at the start of this position that the process I was taught didn’t work for me. I knew the flow of multiple call closes, the front and back end paperwork, the pricing and margins, the lease rates and financing terms well!

I knew that if I were the customer, I would be fed up of everyone using the same sales tricks. I would never buy equipment that costs as much as a car if I didn’t get the information I wanted fast without feeling like a rep was reaching for my pockets. So…

I learned and created an Excel sheet that quickly allowed me to configure my device in front of potential clients, with the pricing they can see, as I consult and configure the perfect solution for their work environment with them Every Time!

With different macros and formulas I created many cool shortcuts on various cells that eliminated all duplication across every order forms, automated quote emails with product information, and a visual interactive experience that gave the customer what they needed to make a decision.

This was a process that typically averaged:

  1. 5-7 separate meetings | about 30 minutes each
  2. Quotes and revisions | about 45 minutes each
  3. A competitive advantage analysis | 5 minutes each
  4. Sales Documentation | 45 minutes

A best case scenario would typically have been:

1 meeting — for 30 minutes

2nd meeting with proposal- 30 minutes

1st proposal prep- 45 minutes

Advantage analysis- we can ignore as it wasn’t always required

Signed Order and back office documentaion — 45 minutes per order

Approximately 2 hours and 30 minutes as a best case scenario start to finish per sale!

My excel program did all this in about 5–10 minutes. It also boosted my sales closing ratios to numbers I didn’t think possible.

Data’s impact on me:

After the first year of utilizing my Excel solution I nearly tripled my yearly income solely from sales commissions and working smarter. I literally went from struggling to make a $45,000 yearly income for so many years to over $115,000 with over and $11,000 in manufactures bonuses in 2013 and $125,000 with over a $8,000 manufactures bonus in 2014.

I was able to pay off all of my $40,000 in student debt and save enough to place a down payment on my first house just before I was forced to leave my foreclosed property in time. I was able to comfortably have my son back from my parents while we were in the middle of our trials.

I believe I was helped by a higher power, but its clear to me that using Data saved me from my own deficiencies in Sales!

Getting out of Sales:

It didn’t take long for me to seriously consider how I made something that helped me in a tough spot that may benefit others that are just trying to make ends meet. These life experiences set me on a new path to trying to incorporate my sales process solution to companies.

Unfortunately the companies that I spoke with were generally not interested in what I can do with what I learned in Excel, but rather to hit a number called quota.

I finally realized that I may have hit the ceiling on what people perceive of my skill level in solving problems do to a lack of a degree, documented projects and other credentials. I considered consulting as a side hustle, but struggled to find anyone to take me seriously which eventually brought me to the conclusion that at that moment of time, I needed to up-skill myself and get out of sales.

An ability to learn:

I’ve tried a few other things over the past 3 years out of a Sales role that I want to briefly touch on. Actually, back when blockchain technology was all over the news, I took a great deal of time learning about its inception along with the problems it is looking to solve. A.I. and machine learning were always fascinating to me, and at the same time I was thinking of ways to help the church I regularly attend.

I learned more about communication technologies and even created a Slack channel, with Zoom, Trello, and Google Calendar integrations to solve the lag in communications among many church's in America. I even learned how to compose, orchestrate and produce orchestral music in an effort to get my son interested in music.

note — I’ve never attempted anything like that either, but I learned on my own over the course of a year.

After a certain point, bringing me only a few months back, I’ve become more confident in learning new skills and even considered code school which a family friend had turned me towards.

Don’t Wait! Find what you were made to do, and work on the steps to get there!

The road I traveled is anything but smooth. If I really think about it, I’ve become more comfortable with a changing environment and discovered a great desire to solve problems with data, and to be a life long learner.

At 35 years of age, no college degree to show for, and a rocky career history, I’ll be taking on a challenge that has a great bias towards a Bachelors / Masters or PhDs in Computer Science, Math, Physics or IT Degrees. As such, I had requested to take my General Assemblies Data Science Immersive program 3 months after I had gotten accepted with a qualifying income share agreement(tomorrow) to prepare.

Income Share Agreements:

Ok, for those of you that do no know what an Income Share agreement is, this is for you. If you want to attend a coding bootcamp, but don’t have the money pay for the class, or if you don’t want to take out a loan right now due to fluctuations in the market thanks to the pandemic, consider these types of agreements. Basically, after graduating the program, you are agreeing to pay a portion of your paycheck from future work related to your program, in my case, a percentage of my paycheck for a set amount of time. If I do not earn the threshold amount, I don’t have to pay until I do, for a cap of 4 years of payments in my case. Even though I’m confident I will exceed the threshold amount, and probably paying more in the long run, I have no risk of having to pay if I am out of a job. Seriously, don’t let a dollar amount hold you back if its stopping you from doing something you think is meaningful.

Conclusion (the past 3 months until now):

After getting accepted into GA, I knew I needed to work on some skills to ensure I make the most out of my program starting tomorrow. I also know based on extensive research that I probably won’t have the skills to land a position after graduating the program with my existing skill-sets.

To make the most use of my time, I focused on a few skills that not all Data Scientists have in hopes to make myself more marketable. Having little prior knowledge with Macs, and no experience with Linux systems, I decided to purchase a used 2015 Macbook Pro and also build my own Data Science Linux PC from scratch (first build). I may write a future article on the reasons for the parts I chose, but here is the list of parts for my Fedora 32 Linux PC:

Ryzen threadripper 3970x
Evga 1080ti ftw3
Evga Supernova p1000
Noctua nh-u14 str4-sp3
Asrock trx40 Creator
G.skill Trident Z Neo 64 gb 4 x 16 gb ddr 3600
Corsair Mp 600 1 tb
Netgear Night Hawk x65
Noctua redux fan 140mm x 2
Noctua redux fan 120mm
HEL Schiit
ViewSonic vx2433wm
Beyerdynamic dt-990

This is insanely more compute power than I need, but the general idea is to future proof my device for a while and avoid the high costs of services like AWS. The other silver bullet in my decision is to use the cost of my parts as motivators to try my very best.

Here is the finished build:

back wiring
I got it to work

I then needed to work on getting familiar with both Mac OS and Linux while getting comfortable with the terminal or bash, so I also successfully learned how to create and set up a wireguard virtual private network (VPN) on a Linode virtual private server (VPS).

I figure getting my hands dirty on these types of projects would help me learning both platforms at an intermediate level.

I’ve set up my Anaconda environments and got familiar with Jupyter notebooks through step by step tutorials on YouTube:

I’ve found this video from particularly useful for me:

Being short on time, I’ve resorted to going along with the video at 2x speed and re watching parts that I had trouble understanding.

Having not studied statistics, I took the time to get on Khan Academy and just focused on completing the Statistics and Probability course. At the time of this writing I’m presently at 69% completion and 51% AP statistics completion respectively.

I’ve also tried my best to understand the what the real world of data science looks like after I’m done with bootcamp by learning from other Data Scientist channels like the one posted here:


I’m making the choice today to start publicly documenting my learning and findings socially. I’m learning that these types of jobs are in demand, but the process of landing my first position with a Data title is probably going to be really difficult without real world projects to back me up.

Just because I’ll have a certificate of completion from General Assembly in October, will not provide enough value for future employers to take a chance on someone with no prior professional code, math, or data experience.

If anyone has managed to make it this far, I’d like to deeply thank you for taking the time to learn more about me. I’m hoping that others will find my journey useful and inspiring to never give up, and to take that decision to change your life’s direction to one that is simply put, satisfying!

~David D. Lee~

Note — As this is my first article ever, I’d love to hear your thoughts and suggestions on how to make it as a Data Scientist, if you were in my shoes! Best!