Even the biggest dragons can be killed, according to many Medieval stories.
The COVID-19 problem we have now is the real-world equivalent of the mythical dragon. But it is not a knight in shining armor that can defeat the pandemic, but a team of real-world data champions.
Frontliners like policemen and healthcare workers are the ones making the headlines in the fight against the pandemic. However, behind the scenes, data scientists are tapping away at their keyboards in order to help stop this public health crisis.
How is data science used to help fight COVID and its most recent Omicron variant? Let’s delve into this mysterious world in the eyes of Eskwelabs’ learners.
The amazing world of data science is shrouded in mystery for some. For others, it’s only for techies. But here at Eskwelabs, we have a data science program that is composed of techies and non-techies alike. These learners are studying one of the hottest fields today.
Investopedia simply defines data science as a “field…that…uses techniques such as machine learning and artificial intelligence (AI) to extract meaningful information and to predict future patterns.” The information mentioned here is extracted from a large pool of data (such as number of patients, age of patients, number of hospital beds, etc.). The logic of machine learning and AI, where a computer imitates the way people think, is combined with this large dataset in order to come up with solutions to business or social problems.
Skills in machine learning and AI have enabled Eskwelabs’ learners to come up with high tech projects that may be used to combat COVID-19, one of recent history’s most difficult challenges.
Curious to find out how our learners managed to help find potential and potent solutions for the pandemic? Here are some of the capstone projects of the learners of our 15-week Data Science Fellowship.
Politics aside, one thing stares Filipinos in the face. According to a 2022 Rappler report, there are not enough COVID vaccines for everyone, especially in the Philippines’ far-flung provinces.
One of the silent victims of vaccine shortage are the country’s senior citizens.
Some reputable studies suggest that the elderly’s immune systems are in general weaker compared to their younger counterparts. This, plus the fact that many senior citizens are not as mobile as the younger population, increases the chances that older people will run out of vaccines. After all, with some of them already sickly, senior citizens do not have all the time in the world to get their shots since people with illnesses are generally advised to wait until they get healed before getting their vaccine dosage.
This is what Dr. Generoso Roberto aimed to address in his capstone project, which he submitted prior to graduating from Eskwelabs’ Data Science Fellowship. In his work, he used machine learning to determine which areas in the Philippines should be prioritized given the limited amount of vaccines.
In order to solve the said problem, Generoso first gathered data from the Department of Health, Facebook Data for Good, and the Philippine Statistics Authority. The information he acquired from various sources took into account factors like COVID cases per 100,000 population in a municipality, the number of hospital beds, and the amount of poor people in a municipality. Dr. Generoso processed the data he collected using a machine learning method called K-Means clustering (a data science-related method). Using this method, he was able to determine which municipalities or cities should be prioritized in accordance to which of them need vaccination the most.
Learn more about Dr. Generoso’s capstone project by watching the video below.
Have you encountered websites where there is “something” that chats with you quickly and automatically in order to answer your questions?
If you had this experience, you were probably talking to a chatbot. This is a program that uses machine learning and AI in order to imitate how a human being answers chat-based inquiries. In other words, chatbots use data science tools and techniques to give you the impression that you’re talking to a real resource person.
The arrival of COVID-19 and the vaccines devised to stop it led to a great hunger for vital information about the pandemic. In a world full of fake news and misinformation, it is difficult to differentiate between accurate COVID data and sensationalized information that simply causes fear or panic.
That is why our Data Science Fellows and their capstone project come in handy during these uncertain times. Fatima Santos, Mikee Sevilla, Kaye Yao, and Phoemela Ballaran pooled their newly-acquired data science skills to come up with a chatbot of their own. This chatbot also uses artificial intelligence (AI) and machine learning (ML) to provide people with automated and high-quality answers to vaccine-related questions.
Harnessing the power of data science and the related fields of AI and ML, the four-person team scraped thousands of COVID vaccine-related comments from Twitter, categorized the comments into topics, and used the topic classification to come up with a chatbot. It took the team only a few days to accomplish this. Without the help of data science tools like Snscrape and Textblob, data gathering and topic classification of thousands of Twitter comments would have taken months or years.
From the categorization of comments into topics, our Data Science Fellows were able to program a chatbot that can provide answers to questions regarding the most talked about aspects of COVID vaccines. This chatbot was even featured in a Rappler article.
To get an in-depth view of our learners’ amazing chatbot, you may watch the video below.
You might be thinking, who would want a future pandemic? Why all the paranoia and negativity about a grim future where millions of sick people die?
We at Eskwelabs hope for the best, but are prepared for the worst. This spirit of being ready for anything can also be found in our learners, especially our Data Science Fellows.
In order to help our country, or even foreign governments prepare for future pandemics, our very own alumni Heide Balcera came up with a dashboard to help identify regions that are most susceptible to the spread of viruses. She came up with this project because the Philippine healthcare system was so unprepared when COVID-19 struck, that millions of people got infected while tens of thousands died.
Wanting to prevent another “surprise attack,” Heide designed an app or dashboard that can help government planners and healthcare leaders deal successfully with the next big pandemic. Like any data scientist, she first gathered huge chunks of data from government agencies like the Department of Health and Philippine Statistics Authority and American scientific organizations like NCBI. The data she gathered include hospital bed capacity, population density, death rate, and virus occurrence per Philippine region. Heide also gathered information about the characteristics of the different viruses that plague the country.
Using NCBI’s BLAST algorithm (basically a database-driven matching software), Heide assigned numerical scores to the viruses based on how their material composition causes them to inflict harm on the human population (the higher the score, the more harmful the viruses are). Through K-Means clustering, Heide processed these scores together with other government data and determined the relationship between how certain viruses are harmful on their own, how susceptible each Philippine region is to the viruses, and the capability of said regions to handle an upsurge in infections.
With Heide’s app, government leaders will be able to wisely allocate limited resources to address healthcare gaps in regions that need help the most during the spread of virus-driven illness.
Watch the video below to get a glimpse of Heide’s groundbreaking project.
You don’t have to be a soldier or a knight in shining armor to become a hero during pandemics or other similar social problems.
If you have an open mind and the growth mindset to learn something new, you are welcome to enroll at our 15-week Data Science Fellowship or our 9-week Data Analytics Bootcamp. Data analytics is another field you might want to consider if you’re more interested in turning data into visualizations like graphs instead of programming models like the capstone projects featured in this blog.
We welcome both techies and non-techies in our two bootcamps, as long as you pass our entrance assessment.
To make the tuition more accessible, we teamed up with study-now, pay-later financing partners. Bukas and InvestEd have financing options that break down tuition payments into manageable chunks. In addition, many of our learners are subsidized by their employers. If you are working for a private company or nonprofit institution, we encourage you to talk to your human resources manager or supervisor and discuss this possibility.
It is said that fortune favors the brave. In an age where the pandemic has disrupted and destroyed the lives of many, the courage to grow is more important than ever before. After all, given that data scientists generally earn higher salaries, daring to dream can be as noble as it is profitable.
If you learn data science and data analytics with us, you can help make a difference not only in society, but in the lives of your loved ones as well.
Use data skills to help solve massive social problems like COVID-19. Click “Apply Now” in either of the following links to embark on your data upskilling journey:
If this is your first time reading about the Data Science Fellowship, full program details can be downloaded here.
If you are curious about the Data Analytics Bootcamp, check out this link to know more about the bootcamp’s curriculum.
Money becomes less of an issue once you get to know our financing partners. Click on any of the links below to learn more.
Get the chance to work, earn, and learn right after graduation through our two bootcamps’ Industry Apprenticeship. Click here to learn more.