This isn’t to say there won’t be challenges I need help to overcome, but just that it is important to be willing to try, to fail, to try another way or two, and reserve the help requests for only when other options have been exhausted or time is running short.
#Unconventional trello how to#
If they were going to take the time to show me exactly how to do a task, they may as well just do it themselves. Lastly, and one of the most valuable lessons I learned, was that there likely will not be anyone holding my hand through new challenges out there in the field. This is the sort of skill I can’t summarize as a bullet point on my resume, but it should prove invaluable in my future roles in Data Science.
I was happy to see how well we all did when everyone was positioned to do their best. I was able to identify who needed support, who needed space to work and trust that they had it under control, and who just needed to know I had their back either way. I really felt this from the reactions and responses from my fellow Data Science teammates. I also learned that I am a more capable team member and leader than I had been aware. Technical learning in a field like Data Science literally never ends. What I learned, for one, is that I will always continue learning.
#Unconventional trello code#
I could go through the details about how we created user stories, broke them into engineering tasks, navigated the brown-fields of another teams code base, created FastAPI endpoints, worked within an Agile framework to show our progress and communicate with each other and the project leads, and eventually deployed the final project on AWS which we had never encountered before, but that’s not what I found the most value in learning during this experience.Ī snap of a card I completed on our Trello board. It wasn’t time to show what I had learned, but instead to show what I could still learn while also getting the job done. Little did I know that I would have more technical learning to do within those two months, more side missions to accomplish, more meetings, lectures, group chats… more distractions than ever. Going into Labs I knew we would be working on a cross-functional team for multiple weeks to deliver a project, or upgrades to a project, but instead of just 2 weeks to work, we would have 2 months. Screenshot of our Trello Board near the end of Lambda Labs What I Thought vs. The time to build the best thing yet, the biggest project to add to my portfolio as I venture out into the wild world of data in search of my first job at which I would begin my career… or so I thought. The time I could put everything I learned to use. Add SQL queries, Containerization, Productization, Cloud Deployment, and some Data Structures and Algorithms for good measure, and I find myself quite knowledgable in the world that is now known to me as “Data Science”.Īs we wrapped up our education, the final section was “Labs”.
Through the year we were taught many valuable frameworks and libraries in Python, concepts in Machine Learning, Model Interpretation, Neural Networks, Natural Language Processing, Data Wrangling, Feature Engineering, Data Storytelling, Visualizations, and even learned a good bit about Statistics including Bayesian statistics, T-tests, and A/B testing. I have just finished the Data Science program at Lambda School, on time, amidst a pandemic, and I couldn’t be more proud. So it’s been a year of determination, frustration, victories, struggles, but all the time… learning. Unconventional Education: Sometimes the Greatest Lessons Aren’t on the Syllabus.
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