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  • Writer's picture♫Shokolatte♬

Why I Online ~ Learning Machine Project (97)

Updated: Mar 11, 2022


Another R language data visualization course certificate granted.🎉🎊 I think I am pretty good at ggploting by now but why do I still take these fundamental to intermediate courses? There are a couple of reasons.


For one, I am collecting certificates from online courses which became my life-time hobby since covid quarantine started. Although I might have missed one or two to record, this one counts as my 97th certificate since I started this "Learning Machine Project" (Showee's Learning Machine Project Certificates - Google Sheets) inspired by Charles T. Munger's words in this video >>> https://tinyurl.com/ynpuyrjy . And yes, you heard me right, it's going to be a 100 certificates I will have owned very soon too.


But that's not the only reason. Currently, I am a full-time student, thriving to land a job in data analysis/data visualization field which I got mad love but have no substantial "work" experience for. I have applied for a number of data analysis positions but I'm gracefully in this "no experience, no job - no job, no experience" loop as you could imagine.


So how will I become confident in what I do and be flexible to bring forth the solutions like I'm solving the real-life work problems? With 10+ years of work experience prior to academics, I broke down the "business as usual" stream in my prior jobs everywhere, and what comes to the top is that you are given a task(s) so that you apply your best knowledge into it to become a better practitioner the next day. At least that's what I did, even when I was a bartender to sailors or a manager of a team in a global company.


To overcome this part without a job (I mean, employment), I decided to spend at least 8 hours a day for just knowledge application purpose alone besides learning new things for my actual school coursework. Although it may sound contradictory, applying your existing knowledge is about learning something new because it creates a mix of efficiency. Also, even though the courses I take for that purpose might seem shorthanded at the beginning, there are always some new syntaxes that I didn't know, due to the course designs built by different program coordinators who handle similar problems in various different manners -- just like you witness while working in cross-functional teams in the real world. So I am taking this opportunity with ample of free courses in front of me as to simulate work environment myself every day. I am still intimidated to speak with people who are expert in the field (aka interviewers), yet I am growing my competence this way and the technical vocabulary is becoming less of an obstacle (in other words, I started seeing myself speaking as if I'm in this field for a while) for me. Thus I'll keep taking online courses restlessly to gain "experience" until I land a job in the field of my dreams.



I loved this course because the final project assignment was totally on our own and you are also able to view how other students did with the same dataset given through peer grading system. My deliverable can be found here >>> Coursera ‘Data Visualization in R with ggplot2’ course by Johns Hopkins University: Week 3 Peer Review. Nothing big, but I enjoyed creating visualizations from scratch for this assignment.


Description: Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.


This course is the second in a specialization in Data Visualization offered by Johns Hopkins. It is intended for learners who have either have some experience with R and data wrangling in the tidyverse or have taken the previous course in the specialization. The focus in this course learning to use ggplot2 to make a variety of visualizations and to polish those visualizations using tools within ggplot as well as vector graphics editing software. The course will not go into detail about how the data management works behind the scenes.





Took this course for free with CUNYUpskiling account. #CUNYUpskilling.





My "Learning Machine Project" list can be found here >>> Showee's Learning Machine Project Certificates - Google Sheets. The list has information of all courses that I completed.










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