Meet Flavia Jones. She’s a student in the Master’s of Accounting (iMSA) program from Gies College of Business at the University of Illinois Urbana-Champaign (UIUC). Flavia works at the AT&T headquarters in Dallas, Texas. She discovered Coursera through AT&T University, which encourages employees to develop skills and advance their career with online courses.
Flavia got started on Coursera by taking massive open online courses (MOOCs), and she’s continued to learn through her master’s program from Gies. This is her story.
Starting With Open Courses
Flavia already had her associate’s and bachelor’s in accounting, but she wanted to refresh her accounting knowledge and learn more about data analytics for accounting. Through AT&T University, Flavia soon found an introductory Coursera Specialization with open courses taught by Professor Ron Guymon. She liked the courses and noticed Professor Guymon was teaching from UIUC. Moving forward, she always kept UIUC in mind for when she would eventually pursue her master’s.
Choosing the iMSA from Gies
As Flavia was searching for a master’s program later on, she was seeking a hybrid learning experience that included both live sessions and asynchronous work. She was determined to find a highly ranked school for accounting that offered an affordable program and an engaging experience.
Remembering UIUC, Flavia saw that the iMSA from Gies had weekly live sessions and lower tuition than competitors. With other programs, Flavia would’ve had to take the GMAT exam before applying and attend some classes in person. With the iMSA from Gies, she qualified for a fully online program based on her references and professional experience.
Doing More With MOOCs
Flavia now encourages colleagues who are interested in data analytics for accounting to enroll in a Coursera Specialization with open courses. She says you can get a glimpse of the subject matter and a sense of managing your study time through MOOCs. She also says you can be sure you’re learning from experts who are teaching up-to-date curriculum when you’re on Coursera.
Flavia has even enrolled in additional MOOCs recommended to her by other students, and she’s become a board member of a student organization called the iDegrees Graduate Business Association. Through this organization, she’s able to work with other Gies students on new ideas for MOOCs.
Are you on a path similar to Flavia’s?
Flavia’s story is a powerful example of how individual courses can help you prepare for a degree program. If you’ve been inspired by Flavia, you can check out the iMSA here and explore MOOCs from UIUC here.
This Sunday is The Grammy Awards, and many of the biggest names in music — like Bad Bunny, Lizzo, and Taylor Swift — are nominated for awards this year. While we won’t know who’ll take home a gilded gramophone until Sunday, some of the nominees already have quite a few Grammys to their name.
Beyoncé, for example, is poised to break some Grammys records. Beyoncé is already the most decorated female act in Grammys history, with 28 awards under her belt. This year, she claimed the most Grammy nominations with nine, including Album of the Year for Renaissance. If Beyoncé wins at least four of those awards, she’ll become the most decorated Grammy artist in history, in other words, the Grammys GOAT.
This is a pretty major feat in music history, but Beyoncé’s impact is bigger than just her collection of awards and extremely catchy music. As a massive pop star and artist, Beyoncé has frequently used her platform to celebrate and promote Black excellence. Think: Hiring HBCU marching bands when she headlined Coachella in 2018, reimagining The Lion King in the 2020 visual album Black Is King, and paying tribute to Black queer artists in Renaissance.
“As an artist, I believe it’s my job, and all of our jobs, to reflect the times,” Beyoncé said in a 2021 Grammys acceptance speech. “It has been such a difficult time, so I wanted to uplift, encourage and celebrate all of the beautiful Black queens and kings that continue to inspire me and inspire the whole world.”
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To commemorate Black History Month and the Grammys, we’re putting Queen Bey’s Grammys accomplishments in perspective using programming tools we know and love: data science and visualization. You might be thinking, Why bother doing this when the music speaks for itself? Well, the best way to practice data visualization (or pretty much any coding language or skill) is to apply it to something that motivates you, says Eva Sibinga, a Codecademy Curriculum Developer in Data Science. “That can be for a fun reason or a serious reason, but if the project demands your attention because you’re passionate about it, you’ll push yourself to learn new things and grow your skills.”
Telling a story with data
Anytime you translate large amounts of information into something actionable, you’re engaging with data science. Broadly speaking, data science is a combination of probability and statistics, software engineering, and domain knowledge.
Data visualization is the process of mapping, graphing, plotting, and charting data to discover relationships and patterns. “When I have a question or a hunch, I often want to see the answer laid out visually,” Eva says.“That means more to me than numbers without visuals, because data visualization allows us to show numbers in context and add richness to a simple calculation or statistic.”
Much like writing music, creating compelling data visualizations can be an art form. There are lots of different types of charts and graphs — like bar charts, histograms, and pie charts — that you can code to convey specific relationships in data. Deciding which type of chart will best illustrate your data findings and customizing it with color and other design choices is all part of the fun of being a data scientist.
Data doesn’t have to come from fancy sources to be interesting or worth exploring. You just have to evaluate its quality and accuracy, not its academic pedigree.
Eva Sibinga
Codecademy Curriculum Developer, Data Science
Lots of data scientists work with the programming language Python and its data-specific libraries like Pandas, Matplotlib, and Seaborn. If you want to level-up your data science work in Python, data visualization is a great skill to explore next. You can learn the ins and outs of data visualization in the path Learn Data Visualization with Python.
Never dabbled in data science before? That’s totally okay! We have lots of beginner-friendly data science courses and paths that you can explore. If you want to get more comfortable thinking about and analyzing data, start with the free course Principles of Data Literacy. For a more comprehensive and hands-on approach, take the path Data Science Foundations. In this path, we’ll teach you how to use go-to data science tools like Python and SQL to access, manipulate, analyze, and visualize data.
Analyzing Beyoncé’s awards using data visualization
One of the first steps in making a data visualization is to identify the type of data you want to visualize. In this case, we wanted to chart Beyoncé’s music career through the lens of Grammy nominations and wins and noms, from her first win in 2001 with Destiny’s Child, to her knockout 2016 album Lemonade, and everything in between.
Okay, data, now let’s get in formation. We started creating our dataset by pulling information from Wikipedia lists, which are an excellent source for this kind of public information that’s not up to interpretation, Eva says. “Data doesn’t have to come from fancy sources to be interesting or worth exploring,” she says. “You just have to evaluate its quality and accuracy, not its academic pedigree.”
We organized our information in a simple Google Sheet that included all of Beyoncé’s Grammy nominations organized by year, type of award, and whether or not she won. “Then we just had to make sure the information was cleaned so that the sheets for each artist we compared had the same columns,” Eva says. Using the Python library Pandas, we’re able to import a CSV file and use the library matplotlib to make our graph.
Eva decided that a stacked bar chart would be the best way to visualize this dataset, because she wanted to show the counts of three categories (nominations, wins, and pending awards) over time. A bar chart is a simple and digestible way to communicate that information. We create a bar graph using the specific bar chart function, and add everything else to the graph using different general functions.
Here we can quickly see the trajectory of Beyoncé’s Grammys career. Eva used the color parameter in matplotlib‘s plt.bar() function to customize the colors in the chart so we can differentiate the categories that are relevant to us.
“When we talk about the Grammys, it’s usually about ‘wins’ and ‘nominations,’ so we want these categories to be easily distinguished in this graph,” Eva says. “Because we’re in the short window of time where some of the current data isn’t known yet, we have an additional category for pending awards.” The beige bars represent the nominations she received, the pink section is her Grammy wins, and the blue bar on the far right is for this year’s Grammys that haven’t happened yet.
Well, we have one chart, but how can we tell how Beyoncé stacks up to other Grammy winners? We took a look at the other artists who are nominated for several Grammys this year for inspiration — like Adele, Mary J. Blige, and even Beyoncé’s husband and frequent collaborator Jay-Z.
To date, Beyoncé and Jay-Z each have 88 Grammy nominations, making them tied for the title of most-nominated artist in Grammy history. Interestingly, the couple has been nominated together a total of 17 times and they’ve won five Grammy awards for their collaborative works. Let’s repeat this process with Jay-Z’s Grammys career.
So, what can we learn from this graph? Right away, we can see that Beyoncé’s graph has a more classic “pop star” look to hers and Jay-Z has a more “producer” look, Eva says. What that means is Beyoncé’s wins tend to be concentrated at peak moments in her career when she released albums, whereas Jay-Z’s are more consistently split (except for 2018, when he went home empty-handed).
We know that Jay-Z has an extensive career producing music by other artists in addition to performing and rapping his own work, so he’s eligible for more Grammys in more categories. “It seems like he is nominated more consistently for behind-the-scenes work — because his spikes don’t just correspond with heavily publicized albums,” she says. An artist as popular as Beyoncé, on the other hand, may not release new music every single year.
The singer Adele, for example, is up for seven Grammy awards this year, including Album of the Year. But she’s only put out four albums in the course of her career, so her graph looks sparse.
Let’s look at another multi-hyphenate artist, like singer and songwriter Mary J. Blige. Like Bey, Mary J. Blige has been included in the Grammys since the ‘90s, and she’s won nine awards to date. This year, she’s nominated for six Grammys, including Album of the Year for her 14th studio album, Good Morning Gorgeous. You’ll notice that her chart has the greatest range in terms of dates.
Notably, Mary J. Blige has collaborated with lots of artists in her career across a diverse range of musical genres — from R&B to country and classical. She’s also written songs for movie soundtracks and executive produced albums. “Her chart made me most curious to read about what she’s been doing over the last seven years where she had no nominations after lots of activity from 1996-2015,” Eva says. “Sometimes the absence of data is the interesting part!”
Ultimately, these awards graphs are just an entertaining way to take a different look at your favorite musical artists’ careers and apply data science to your daily life and interests. You could even do this with your favorite actors ahead of The Oscars! As you can see, there’s no limit to the types of interesting and relevant datasets you can explore with data science.
If music and pop culture isn’t your thing, check out all of the Codecademy data science projects that you can complete to practice applying your programming skills to real-life contexts. For example, in the case study Analyze NFL Stats with Python, you’ll build a machine learning model to predict the winners of NFL games (just in time for the Super Bowl!). The bottom line: There’s value in doing fun projects simply because they make learning easier and more enjoyable.
They conducted two experiments. In the first experiment, participants were asked to study one of two text passages (biological anthropology versus geology) and then instructed participants to study in one of four conditions:
1. Provided-Flashcards: Participants were given premade flashcards from the textbooks to study with. These flashcards were heavily detail-level ones.
2. Self-Generated-Flashcards: Participants were asked to create their own flashcards.
3. Conceptual Self-Generated-Flashcards: Participants were instructed to create their own flashcards, but were provided instructions to use a conceptual approach.
4. Free-Study: Participants were instructed to study the text passage as they wished.
In the second experiment, participants were provided with either detail-level or conceptual-level flashcards to study one of the two text passages. In both experiments, participants’ structure building ability was measured. Performance was measured on a multiple-choice and a short-answer test covering both detail and conceptual questions.
What did they find?
Findings from the first experiment:
a) Students were more likely to generate detail-level flashcards if not instructed to do otherwise. In addition, the provided flashcards from textbooks were also heavily biased towards detail-level content. So, without any further instruction and if left to their own devices student will be mainly exposed to or generating flashcards that contain definitions or simple facts. Prompting students to generate conceptual-level flashcards was successful to engage them to create those flashcards, but the authors also mention that they only asked students to generate a few conceptual-level flashcards – making the difference between the different study groups less extreme.
b) No difference was found between the four study groups in relation to their test performance on either test. The authors explain that this could be due to the abovementioned little difference between the three flashcard conditions which all were more biased towards detail-level content. In addition, they acknowledge that even participants in the free study condition may have been using strategies similar to the other study groups – making that group more similar to the others.
c) In this experiment, no benefit was found of students generating their own flashcards. However, a significant difference was found in regard to study time: Participants in both self-generated-flashcards conditions studied for longer (approx. 24 minutes) than participants in the provided-flashcards and free study conditions (approx. 15 minutes). Thus, generating flashcards took them longer to do without an effect on performance. However, it is important to keep the just mentioned limitations in mind before jumping to conclusions. Furthermore, despite the fact that no differences were found between the four study groups, the authors found an overall positive relationship between the number of conceptual-level flashcards generated and test performance: More conceptual-level flashcards was associated with better performance on both tests.
In the second experiment all participants were provided with flashcards (either conceptual-level or detail-level ones). While there was no difference between the two conditions on the multiple-choice test, they found an advantage in short-answer performance for participants in the conceptual-level flashcard condition. Interestingly, the benefit of conceptual-level flashcards was moderated by structure building ability: Particularly participants with low structure building ability benefitted from conceptual-level flashcards whereas for participants with high structure building abilities it did not matter whether conceptual versus detail-level flashcards were used.
Do you aspire to occupy the corner office? Is your dream to be a successful entrepreneur, businessperson, or renowned industry leader? Have you set your sights on the ultimate success in sports, arts or in your field of interest? The secret to success, if you ask anyone in any industry, is being a member of the 5am club. For years this concept has revolutionised how people work and achieve success. And we’re diving right into it and exploring 10 reasons you should join the 5am club.
The 5am club
20 years ago, best-selling author Robin Sharma released a book, The 5am Club, to global acclaim. In his book, he shared the concept of how getting up at 5am is the difference between the ordinary and the extraordinary. According to Sharma, a 5am wake up allows you to complete a set of 20/20/20. 20 minutes of intense exercise, 20 minutes to reflect on your goals, and another 20 minutes to learn a new skill. The 20/20/20 technique is a method to optimise your productivity.
How the 20/20/20 looks
If you’re like most of us, your reflex will be to toss your alarm clock (not your phone) across the room when it blares at 5am. Very normal reaction. But resist the urge. Keep in mind the purpose behind the early start – to be the best, most productive person you can be.
“Early to bed, and early to rise makes a man healthy, wealthy and wise.” —Benjamin Franklin
7 reasons to join the 5am club
Let’s be real for a minute. Our lives are busy. From the moment we wake up until we go to bed at night, we live jumping from one task and responsibility to the next. With little to no time dedicated to accomplishing key projects – well. Or even giving time to things that excite us, challenge us, and make us feel alive. Enter the 5am club mentality.
No distractions. At 5am, very little is happening in the world. Your phone isn’t buzzing with notifications, the kids are still sleeping (if you’re lucky), and few people are awake. This quiet time is the perfect time to tap into your brain and do or begin working towards one thing uninterrupted.
Creates a routine. Our bodies have a 24-hour internal clock, the circadian rhythm, that helps us regulate our physical and mental functioning. Our mind and body serve us best when they are well rested. A consistent sleep-wake schedule gives you more energy to get through the day and get things done.
Time to plan. The extra hours you get in the morning allow you to plan your day ahead – without the rush and madness that tends to come with lateness.
Exercise. While Sharma’s rule calls for “intense exercise”, find something that works for you. The key is to get your body moving, the happy hormones flowing, and your body primed for the day. A Pilates class, walk your dog, go for a jog or a session at the gym, the burst of energy will do wonders for your body.
Prepare. Dedicate the other 20 minutes of your 5am start to reflect on your goals. These can be your daily, weekly, or even monthly goals. Are you on track to achieving them? What can you do today that will get you closer to meeting them? What did you do yesterday that you can build on today? And how can you prepare for the day ahead in a way that will get you where you need to be?
Discipline. Anyone can wake up at 5am tomorrow. And keep that up for a week or two. To do something when everything in you screams not to, that’s where change happens. Waking up at 5am requires discipline and digging deep when the urge to sleep is strong. The discipline of repetition for months and years on end takes stamina, mental and physical strength, and an unwavering commitment to succeeding. “Discipline is choosing between what you want now, and what you want most.” – Abraham Lincoln.
Healthy habits.Waking up at 5am means you’ll most likely go to bed earlier. Which means you’ll “switch off” and reduce the late-night indulgences we’ve become accustomed to – think late night snacking, bingeing on series, and the incessant scrolling in bed. The 5am club, by default, encourages developing healthier habits that contribute to your success.
No, waking up at 5am is not easy. But then again, nothing worthwhile ever is easy. And no, not all will become CEOs or billionaires, but that’s not what it’s about at the end of the day. Life is about living to your full potential, being present in any and every moment, doing good (to yourself and others), being productive, creative, and leaving the world better than you found it. It’s being alive. And what better way to achieve this than by getting the most out of every day?
Set your alarm and join the 5am club. Your dreams won’t wait for you.
First, Florida banned the course. Then, the College Board published the official course framework stripped down from an original draft. What’s your reaction?
Getting lost in a great book is one of the best ways to broaden your worldview and develop empathy for people whose perspectives are different from your own. Fortunately, there’s no shortage of great books written by thought leaders in the tech industry.
In honor of Black History Month, we’ve put together a list of books about tech that are all written by Black authors. Whether you’re looking for a way to learn more about iconic Black technologists and programmers who have paved the way throughout history, or just want a thought-provoking book to read on your commute, here are the books you should pick up next — with links to Black-owned bookstores where you can buy these titles.
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Tech has provided new ways to amplify voices of the civil rights movement, with all forms of organizing and activism found across every social media platform. And while you might think digital activism started with the #BlackLivesMatter movement circa 2012, its roots actually date much farther back.
In Black Software: The Internet & Racial Justice, from the AfroNet to Black Lives Matter, Charlton McIlwain traces the roots of (Black) digital activism from modern hashtags to Black digital spaces from the 1990s and Afrocentric message boards from the 1960s to illustrate how tech has been used to address (and uphold) racial injustice. Buy here.
As tech becomes more and more integrated into our society, the need for diversity in the industry becomes more urgent. In this book, sociologist Dr. Ruha Benjamin explains how technology can subtly reinforce societal biases if we’re not careful, using modern examples of problematic software. Dr. Benjamin’s inspiration for the book came from recognizing data-driven discriminatory practices in healthcare, education, and even hiring, she told The Guardian. Buy here.
Unstoppable tells the story of Roy Clay — who, despite being born in 1929 and facing discrimination throughout his life, rose to become known as the Godfather of Silicon Valley. After becoming one of the first Black graduates of Saint Louis University, Clay found himself turned away from several companies due to his race. Everything changed when he taught himself to code and got hired as a programmer at a federal research facility. Later, he led Hewlett Packard’s computer science department, where he oversaw the development of their first computers and led several initiatives to support Black people in tech. Buy here.
Arlan Hamilton is a venture capitalist who featured in our list of inspiring LGBTQ+ people in tech last year. Backstage Capital, her investment fund, primarily supports minority-owned startups — an initiative she led after recognizing discriminatory behaviors in venture capitalism. Her book, It’s About Damn Time, tells her personal career story, including her experiences with homelessness. She also shares invaluable lessons and tips for entrepreneurs from underrepresented groups who aspire to rise to success. Buy here.
In Algorithms of Oppression, Dr. Safiya Noble points out the racial and sexist biases hidden in search engines and outlines how they help reinforce white supremacy. Dr. Noble connects the issue to “technological redlining” and explains how algorithms can veil and reinforce discriminatory practices. “I hope my book puts a spotlight on how these algorithms lead to further oppression and marginalization of, primarily, women of color,” she said in an interview with the University of South Carolina. “But they also do a disservice to understanding complex ideas about society.” Buy here.
It’s never too early to start coding, and Sasha Savvy Loves to Code is perfect for young programmers. The book tells the story of how Sasha Savvy and her friends learn how to stamp out (computer) bugs at their coding summer camp. It’s a great way to introduce children to the world of opportunity that coding provides, and serves as a reminder of why representation matters. With Black Americans comprising only 7% of the U.S. tech workforce, books like Sasha Savvy Loves to Code help show underrepresented groups that there’s a place for them in the field. Buy here.
Black culture’s mainstream (and global) impact is undeniable, and it’s especially prevalent on social media platforms as AAVE (African-American Vernacular English), rap, and hip-hop dominate TikTok and Twitter. Distributed Blackness: African American Cybercultures examines the relationship between Black culture and technology. Scholar André Brock’s book sheds light on how Black culture helped popularize and influenced social media (and has been influenced in return). It’s a must-read, whether you’re super active on Black Twitter or just a casual scroller. Buy here.
