Week 3 Recap - Staying Focused

#100daysofcode #beginners #accountability

Bonjour CodeNewbies 👋🏾

It's that time of the week again where I go over my #100DaysOfCode progress. Monday marked the end of Week 3 and a 21-day coding streak. I have learned so much this past week and made some really great progress. Let's get into it!

What I Said I Would Do

Last week, I discussed how I got off track with my goals and found myself swamped with a bunch of unfinished tutorials and courses. After reprioritizing, I decided to refocus on completing the following two Coursera certifications:

Python for Everybody
Google Data Analytics Professional Certificate

From there, I would tackle the remaining incomplete courses:

The Odin Project Foundations pathway
freeCodeCamp Responsive Web Design certification.
W3Schools CSS Tutorial

My stated plan for Week 3 was to stick with this reprioritized list.

What I Actually Did

I am happy to report that I followed through and stuck with the plan. Creating that reprioritized list has made a big difference for me. I'm no longer being pulled in so many different directions, and I feel like I am able to focus and get things done.

I accomplished the following:
✅ Completed Python Data Structures (course 2 of 5)
✅ Completed Ask Questions to Make Data-Driven Decisions (course 2 of 8)
✅ HackerRank Python track: Achieved 2 stars

The first two accomplishments come directly from my reprioritized list. I am quickly racking up Coursera completion certificates. 😄

The last accomplishment was a bit of an add-on, but it's related to learning Python. I added in HackerRank practice to help me reinforce the things that I'm studying in the Python course as well as identify any areas where I need additional work. I've found that I really enjoy mini coding challenges/puzzles. They allow me to practice new skills, test my existing knowledge, learn new things and get the gratification of solving something in a few minutes to hours (vs. days to weeks with completing a whole course).

What I Plan to Do Next Week

I plan to stay the course over the next two months and keep hacking away at my priorities. It will take a while to complete the Python and Data Analytics certificates, so I don't foresee big changes in my plans week to week for a while.

I still keep Sunday open as a freebie day to explore other topics that interest me (aside from Python and Data Analytics). It's how I break up the monotony and reenergize. The key is to enjoy these Sunday excursions without letting them creep into other days of the week and derail the main learning. 🤞🏾 Wish me luck because I'm notorious for starting a billion things at once and getting lost in them. 😂

Around the Web 🌏

I read an article on Vice that discussed a new dermatology app by Google that uses artificial intelligence (AI) and photos to identify skin conditions. It's a cool app with one glaring omission: the darkest skin type was completely absent from the dataset used to train the model, and there are concerns that the app may not accurately recognize conditions in darker skin tones because of it. It's yet another example of how well-intentioned work can lead to unfairness that has the potential to result in worse health outcomes for people left out of the models (i.e. darker-skinned people in this particular case).

As a fellow CodeNewbie, I know that the coding journey can be arduous. There are so many things to learn, so many moving parts and so many changes in a short period of time. It's easy to get lost in all of the technical details. However, as (aspiring) developers, engineers, and technologists, we must put the human element at the forefront of our mind.

It is unacceptable to develop and release products that leave large swaths of the human population out of the design, especially populations that are routinely discriminated against and disadvantaged by the dominant culture. Preventing and rooting out bias and unfairness in the products that we build is paramount. And if there is bias in your product, you have a responsibility to be transparent and upfront. It should not take independent investigations to identify that you are missing basic data.

As you're learning and working on your projects, stay mindful of who your work includes as the norm and who you are leaving out. You could be reinforcing inequality and poor outcomes for groups that are already marginalized.