Thursday, April 25, is Take Our Daughters and Sons to Work Day, a day meant to help young people imagine their future adult lives as full of professional possibility.
Have you ever visited your parents at work? If so, what was the experience like for you? Did you enjoy seeing where your parents spend their days? Did you learn anything? Do their jobs seem like something you might want to do when you grow up?
If not, would you ever want to go to work with your parents for a day? Why or why not?
Tell us in the comments, then read the related article to learn more about what children can get out of going to work with their parents.
Find many more ways to use our Picture Prompt feature in this lesson plan.
: cause to be more favorably inclined; gain the good will of
_________
The word placate has appeared in 101 articles on NYTimes.com in the past year, including on March 26 in “Helping an Estranged Family Reconnect” by Lori Gottlieb:
Forgiveness is a tricky thing, in the way that apologies can be. Are you apologizing because it makes you feel better or because it will make the other person feel better? Are you sorry for what you’ve done or are you trying to placate the other person who believes you should be sorry for the thing you feel completely justified in having done? Who is the apology for?
Imagine you are from another planet and have arrived in the United States.
Your mission: You must send a report to your extraterrestrial superiors describing the cultural beliefs of these strange people called Americans. Take five minutes and create a list of at least five statements that describe American beliefs and values. Here’s an example: Success is more important than happiness. Here’s another one: Happiness is more important than success.
From the point of view of an unbiased (alien) outsider, which items on your list do you think are true and beneficial? Which items do you think are mistaken or even harmful?
In his Opinion piece “Five Lies Our Culture Tells,” David Brooks questions many of the core beliefs of American society. He believes these “lies” have led to a spiritual and emotional crisis. In tracing the origin of this crisis, he outlines five lies he believes to be at the root of many of the challenges and divisions Americans face today. Here are excerpts from four of them:
Career success is fulfilling. This is the lie we foist on the young. In their tender years we put the most privileged of them inside a college admissions process that puts achievement and status anxiety at the center of their lives. That begins advertising’s lifelong mantra — if you make it, life will be good …
The truth is, success spares you from the shame you might experience if you feel yourself a failure, but career success alone does not provide positive peace or fulfillment. If you build your life around it, your ambitions will always race out in front of what you’ve achieved, leaving you anxious and dissatisfied.
I can make myself happy. This is the lie of self-sufficiency. This is the lie that happiness is an individual accomplishment. If I can have just one more victory, lose 15 pounds or get better at meditation, then I will be happy.
But people looking back on their lives from their deathbeds tell us that happiness is found amid thick and loving relationships. It is found by defeating self-sufficiency for a state of mutual dependence. It is found in the giving and receiving of care. …
Life is an individual journey. This is the lie books like Dr. Seuss’ “Oh, the Places You’ll Go” tell. In adulthood, each person goes on a personal trip and racks up a bunch of experiences, and whoever has the most experiences wins. This lie encourages people to believe freedom is the absence of restraint. Be unattached. Stay on the move. Keep your options open.
In reality, the people who live best tie themselves down. They don’t ask: What cool thing can I do next? They ask: What is my responsibility here? They respond to some problem or get called out of themselves by a deep love. …
Rich and successful people are worth more than poorer and less successful people. We pretend we don’t tell this lie, but our whole meritocracy points to it. In fact, the meritocracy contains a skein of lies.
The message of the meritocracy is that you are what you accomplish. The false promise of the meritocracy is that you can earn dignity by attaching yourself to prestigious brands. The emotion of the meritocracy is conditional love — that if you perform well, people will love you. …
The article concludes:
No wonder it’s so hard to be a young adult today. No wonder our society is fragmenting. We’ve taken the lies of hyper-individualism and we’ve made them the unspoken assumptions that govern how we live.
We talk a lot about the political revolution we need. The cultural revolution is more important.
Students, read the entire article, then return to your list from the beginning and tell us:
— How did your list of cultural beliefs and values compare to Mr. Brooks’s list of lies? What lies or hidden assumptions would you add to or delete from his list of five?
— What do you think of Mr. Brooks’s argument? Do you believe that American culture is in crisis? Do we need a cultural revolution? Or do you think that Mr. Brooks may be overlooking positive aspects of the things he describes as “lies”? Which parts of Mr. Brooks’s arguments resonate with you and which do not?
— Do you agree that we live in a “hyper-individualistic” society? If so, what do you think are the benefits and drawbacks of that individualism? How has American individualism affected your own life and aspirations?
— For the conclusion to the report for your alien superiors, would you say that American culture promotes living a happy and fulfilling life? Why or why not? What do you think are the keys to a rich, happy and fulfilling life?
Students 13 and older are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.
The United States census, taken every 10 years, is essentially a head count of all the people living in the United States. Its data informs many state and federal decisions, but one of its most important roles is determining how seats in Congress will be apportioned among the states, and thus in the Electoral College.
On Tuesday, the Supreme Court heard arguments about whether the next census in 2020 should ask respondents if they are American citizens, a question that has never been asked of all the nation’s residents in the census’ 230-year history.
If noncitizens weren’t counted in the census, how might American politics be affected?
Take a look at the two maps above as an example of the effect this question could have. As you compare them, respond to the following questions:
• What do you notice?
• What do you wonder?
• Taken together, what story are these maps telling about the citizenship question?
• What implications might a question about citizenship have in the 2020 election and beyond?
1. Why did the reporter, Michael Wines, use the 29th Congressional District of Texas in Houston to illustrate the battle that is brewing over the way the nation tallies its population?
2. What are the main arguments in support of and against a citizenship question on the census?
3. Census data is used to redraw political maps each time it is given. How might knowing the number and location of noncitizens shape those maps? Which party would benefit more from these maps and why?
4. How many noncitizens are estimated to be living in the United States? What is known about these residents?
5. How do Democrats generally feel about adding a question about citizenship to the census? How do Republicans generally feel about it? Why?
6. Margo J. Anderson, a historian and expert on the census at the University of Wisconsin-Milwaukee, says the debate about whether to count noncitizens in the census is “uncharted territory.” Why is that?
7. How would redrawing maps without noncitizens alter politics in immigrant-rich places, like Houston?
8. In what ways do noncitizens rely on elected officials and government services? How might daily life for these residents be affected if they were not counted in the census?
Finally, tell us more about what you think:
As noted above, census data is used to influence more than just politics. How else might an undercount of the population affect the nation?
Take a look at this list of other commercial, political and research efforts that depend on accurate census data. Choose one of these areas and explain how it might be affected if noncitizens were not counted in the 2020 census.
Then, tell us what you think: Should there be a question asking about citizenship status in the next census? Why or why not?
Computer science (CS) degrees are in demand — and for good reason. Jobs that rely on CS skills are growing fast in exciting fields like artificial intelligence, data science, and biotech. Many of these career paths offer six-figure salaries straight out of school.
Unfortunately, a recent story in The New York Times highlights growing challenges for on-campus CS education programs. This means that programs like the high-quality CS degrees delivered through Coursera are becoming essential for more and more computer science students.
As detailed in The Times, the supply of quality CS teachers hasn’t kept up with the surge in demand for CS education. A new survey from the Computer Research Association indicates that the number of undergraduate CS major more than doubled from 2013 to 2017, while tenure-track faculty grew by only 17%.
This has caused a growing number of universities to take steps to limit access to CS classes, leading in turn to frustration among aspiring CS students. For example, Swarthmore College is holding lotteries for CS classes, and capping the number of courses that CS majors may take. The University of Maryland is making CS a limited enrollment major.
These limits may lead to new challenges for groups that are already underrepresented in CS, including women, people of color, and low-income students. That’s because some universities are requiring students to get accepted into CS majors before they arrive on campus, which disadvantages those who lack opportunities to take CS courses in high school.
This shortage isn’t just a matter of waiting for the supply of teachers to catch up with soaring demand for CS degrees. High entry-level salaries are luring undergraduate CS majors into the private sector instead of graduate school and teaching, and top tech companies increasingly recruit professors and PhDs. Ironically, the success that CS skills make possible is limiting access to an on-campus CS education.
Online degree options help solve the on-campus CS demand crunch by allowing professors to reach more students. Coursera’s industry-leading education platform hosts four high-quality CS degrees from top universities:
The Arizona State UniversityOnline Master of Computer Science program offers the opportunity to dive deep into a range of advanced CS topics like AI, cybersecurity, big data, and blockchain.
The University of PennsylvaniaOnline Master of Computer and Information Technology is the only online Ivy League Master’s degree in Computer Science tailored to non-CS majors, allowing students from diverse fields like chemistry, literature, and medicine to succeed in tech-oriented career paths.
Between these four programs, Coursera offers a CS education that matches practically every need — regardless of your past academic background or your future career goals. Most importantly, they each provide the opportunity to learn from the same great faculty as on-campus students with the affordability, accessibility, and flexibility of online courses.
Back in April 2012, Daphne Koller and Andrew Ng launched Coursera to enable anyone, anywhere to transform their life through learning.
Seven years ago, we couldn’t have imagined where we’d be today: connecting 40 million learners around the globe with the world’s greatest thinkers, educators, and institutions.
A lot has happened since 2012. We admire the dedication we’ve seen from learners like Balesh, Scotty, Anastasia, and so many others who have come to Coursera to learn new skills, grow in their careers, and adapt to an ever-changing world.
We wanted to take a moment to celebrate this milestone by looking back on key global trends from each year, as well as the popular courses and Specializations that went along with them.
In 2011, Apple launched Siri, which used natural language processing to answer questions.
The same year, IBM’s Watson computer defeated television game show Jeopardy champions Brad Rutter and Ken Jennings.
Most popular course on Coursera in 2011:
Machine Learning from Stanford University: Andrew Ng, a Stanford University computer science professor, launched his open online course on machine learning in 2011. Before long, over 100,000 learners had enrolled. Through this course, Andrew and Daphne discovered the impact online learning could have on increasing access to education, which led to the founding of Coursera.
2012: Power of Social Sharing
Social media became the go-to place for sharing in 2012. More than 50 percent of adults used a social networking site in 2012, and 67 percent used those platforms to share their opinions.
Medium also launched, giving people across the globe the chance to pen an article without their own blog. With these tools, people had the platform to tell their own story or join the national conversation.
Most popular course on Coursera in 2012:
Think Again I: How to Understand Arguments from Duke University: This course, taught by Dr. Walter Sinnott-Armstrong & Dr. Ram Neta, teaches learners how to identify, analyze, and evaluate others’ reasoning. It also detailed ways to craft your own winning arguments. Richard Faigo, who took the course, said, it gives “clear technical insights with regard to analysis of arguments.”
2013: Hello, Sharing Economy
People worked together in new ways in 2013. The sharing economy took off in 2013 with the rise of Uber, Lyft, and Airbnb.
Crowdfunding, which allows people to come together and collectively back projects, broke into the mainstream. In 2013, crowdfunding sites raised $5 billion, a 50 percent increase from the year before.
Most popular course on Coursera in 2013:
Social Psychology from Wesleyan University: This course, taught by Professor Scott Plous, dives into human behavior and shares tips on how to apply evidence-based findings to decision making, persuasion, and group behavior. Marisa, who took the course, said, “I have truly enjoyed and learned tons about why we humans act the way we do. Professor Plous is a pleasure to listen to, and the team behind him has done a great job in making this course relevant and interesting.”
2014: Spotlight on Lifelong Learning in a Changing World
A 2014 Bloomberg report showed that half of occupations could be automated over the next two decades.
Individuals and companies began thinking about ways to adapt to a changing workforce by learning new technologies.
Most popular course on Coursera in 2014:
Learning How to Learn from McMaster University and University of California, San Diego: Today, more than 2.4 million people across the world have learned to apply research-backed best practices and master tough subjects with this popular course taught by Dr. Barbara Oakley and Dr. Terrence Sejnowski. Chinelo O. who took the course, said, “It totally changed my mindset positively. I use Pomodoro for time management, and my life perspective is more open-minded.”
2015: Unprecedented Demand for Data Scientists
In 2015, “data scientist” emerged as one of the most coveted and best-paid professions in the U.S.
Demand for data scientists outpaced other tech professions, like engineers and data analysts, by 50 percent.
Most popular course on Coursera in 2015:
Data Science Specialization from Johns Hopkins University: Quickly becoming one of the most popular Specializations in Coursera’s history, this series of courses taught by Professors Jeff Leek, Roger Peng, and Brian Caffo teaches the entire pipeline of data science concepts and tools. One learner said the course was challenging and compulsory for anyone who wants to work with data or become a data scientist.
2016: Coding as an Essential Skill for All
In 2016, more than half of the jobs named by Glassdoor as top “lucrative, in-demand” professions required programming skills.
Most popular course on Coursera in 2016:
Functional Programming in Scala Specialization from EPFL: This hands-on series of courses taught by Professors Viktor Kuncak, Heather Miller, Martin Odersky, Aleksandar Prokopec, & Julien Richard-Foy introduces students to a widely-used programming language, Scala. A learner called it, “an excellent introduction to the concepts of functional programming that had the ‘side effect’ of getting me hooked on the language!”
2017: Real-World Applications of Deep Learning
In 2017, after nearly ten years of research, passengers rode in Waymo cars that utilize deep learning for the first time.
There were more than 10,000 job vacancies in the US for people with AI or machine-learning skills, according to a study of job ads.
Most popular course on Coursera in 2017:
Deep Learning Specialization from deeplearning.ai: Touted as a series of courses that helps individuals break into AI, this Specialization helped learners gain the most highly-sought after skills in tech, like neural networks and machine learning. Zohair Shafi said, “[Andrew Ng’s] courses on Machine Learning and Deep Learning got me to where I am today. In all my years of formal education, I’ve never met anyone who can break down concepts and explain as well as Professor Ng does.”
2018: The Year of Self-Care and Wellness
The modern-day “wellness” trend went viral in 2018 and turned the wellness industry into a $4.2 trillion global industry.
Trends like mindfulness, self-care, and mental health took root. People wanted new ways to stay healthy and happy in a modern-tech era.
Most popular course on Coursera in 2018:
Science of Well Being fromYale University: Professor Laurie Santos taught Yale’s most popular class ever on the good life. Before long, she launched her course on Coursera so that people around the world could learn about ways to cultivate the things that make people happy. One recent learner said, “A quality course everyone should take, especially after you’ve started your career or overloaded with school. It’s like hitting the refresh button when living an overscheduled life hour-by-hour.”.
2019: AI Goes Mainstream
While 2017 was a pivotal year for AI breakthroughs, 2019 looks to be the year we realize how much AI already impacts our daily lives. 72 percent of today’s CEOs regard AI competencies as the most important asset of a company.
64 percent of organizations said AI helped them get an edge on their competitors.
Most popular course on Coursera in 2019 (so far!):
AI For Everyone from deeplearning.ai: In this course, Andrew Ng teaches non-technical professionals about the power AI can have for businesses. A learner who took the course said, “I got a comprehensive overview of what AI is and the meanings of various concepts being talked about in this context. Excellent course for one to start on a solid ground. Five stars!”
P.S. Did we miss your favorite course? Share with us @Coursera and give a shout out to your favorite instructor!
Today, we’re happy to share that Coursera has raised an additional $103 million of investment in a Series E equity round. With this round, we welcome SEEK Group, a global leader in investing, scaling and operating online employment and education businesses, as our new investor. Existing investors Future Fund and NEA also joined the round.
The Fourth Industrial Revolution, marked by advancements in automation and artificial intelligence, is dramatically reshaping our lives, businesses, and jobs. Coursera is at the forefront of preparing individuals, companies, and governments to address these challenges head-on and turn this disruption into an opportunity. The additional funding gives us the resources and flexibility to further expand internationally and to accelerate the development of a learning platform that currently serves 40 million learners, 1,800 businesses, and over 150 top universities.
Even with our rapid growth and global reach, we still have so much more to do. As the future of work and the future of learning converge, there is an enormous opportunity for us to make the world’s best education available to hundreds of millions around the world and change the way they learn. We are so grateful to our learners, partners, enterprise customers, and employees who helped us get to this point and will propel our innovation and growth in the years ahead.
Answering your most pressing questions about the new Computer Vision Specialization on Coursera are Radhakrishna Dasari, Computer Science and Engineering Instructor and Dr. Junsong Yuan, Associate Professor of Computer Science and Engineering and Director of the Visual Computing Lab from the University at Buffalo, The State University of New York.
An integral part of this Specialization is the use of MATLAB, a leading mathematical computing software for engineers and scientists. Dr. Brandon Armstrong, Senior Online Content Developer at MathWorks, will be discussing how learners can apply and build skills in computer vision using this industry standard tool.
Instructors Radhakrishna and Dr. Yuan: Vision is one of the key senses through which humans learn and navigate through this world. Human vision and the brain evolved over millions of years, enabling us to perform many visual tasks quite effectively. Over the last few decades, it’s been challenging to make a computer see and analyze the visual world as we do! We’ve seen significant progress, however, in the past few years because of the rapidly developing interdisciplinary field of computer vision that adds intelligence to imaging. Its main goal is to automatically understand and interpret images and image sequences. Computer vision has numerous practical applications that are starting to permeate day-to-day life and have been in the spotlight of mainstream media. If you own a smartphone, for example, you have a thinking camera. We are excited to create a resource that compiles advances of this happening field and help start beginners on their path to understanding.
2. Why was this Specialization created?
Instructors Radhakrishna and Dr. Yuan: Computer vision is a vast interdisciplinary field, with numerous journals and conferences continuously publicizing its advances. Computer vision can be overwhelming for someone who does not know where to begin. This Specialization was created to serve as a primer. Our key focus was on summarizing its evolution and highlighting the perspectives of academia and industry, as both are big players in advancing this research area.
Instructors Radhakrishna and Dr. Yuan: The ideal learner is anyone who wants to learn computer vision fundamentals, such as an undergraduate/graduate student or professional working in a STEM discipline. The first course gives an overview of concepts and applications and the next three cover them in detail. Learners should have some programming experience (in any computer language) and basic knowledge in mathematics, especially linear algebra, calculus and probability theory.
4. What can someone expect to learn?
Instructors Radhakrishna and Dr. Yuan: After successful completion, learners will be well versed in computer vision concepts and key application areas. Through four projects, they will become very familiar with programming in MATLAB®, and acquire confidence in implementing new image processing, computer vision and machine learning projects. They will also be aware of venues/resources to monitor in order to keep pace with this rapidly evolving field.
5. What is MATLAB?
Dr. Armstrong: MATLAB® is the leading mathematical computing software for engineers and scientists developed by Mathworks. People are often surprised to learn that MATLAB is nearly 40 years old. Cleve Moler, professor of math and computer science, created MATLAB using syntax that mirrors common science and engineering notation, so his students could focus on solving math and engineering problems. Today, over 3 million people around the world use MATLAB to solve complex problems in industries such as aerospace, automotive, and energy production.
Dr. Armstrong: Students will learn, apply, and build skills in computer vision using an industry standard tool. They’ll first learn image processing theory and then dive into real world examples. For example, self-driving cars require computers to detect image features like lanes, track the motion of objects such as cars, and recognize items like pedestrians. Learners will use MATLAB to implement these fundamental concepts through projects in each course.
Students will also get to use MATLAB apps. These are built-in graphical tools that enable rapid prototyping and allow for fast experimentation of ideas without writing code, so learners can focus on key concepts.
7. What is particularly exciting about this new Specialization?
Instructors Radhakrishna and Dr. Yuan: Despite recent advancements, there are still many unsolved problems in the computer vision field and there is no fixed way to solve them. The same problem has been approached with different solutions. That is why the fourth course – which introduces deep learning – is very exciting! We demonstrate how several problems discussed in earlier courses are solved effectively by using deep learning. But does that mean deep learning can solve all computer vision issues? We gather various perspectives from industry and academia to answer this question.
Dr. Armstrong: Computer vision is an incredibly important field with applications from autonomous robots to cancer detection. Solving these challenges requires working with large cross-disciplinary teams. MATLAB gives scientists and engineers from many different fields the ability to work together to accomplish tasks – from simulation and prototyping to deploying code on actual devices – more quickly than traditional coding. Students completing this Specialization will be more equipped for a career in computer vision and gain valuable experience with MATLAB, an in-demand software package that’s a required skill for many jobs in this area.
MathWorks is excited to partner with the University at Buffalo to give learners access to the same tools used by computer vision professionals. As part of their MOOC Support Program, MathWorks collaborates with Coursera partners to provide free support using their software. They work one-on-one with instructors to create auto-graded assignments, give access to MATLAB, and provide learning resources that teach software functionality. For Coursera partners interested in learning more, email moocsupport@mathworks.com.
What do you think this image is saying? How does it relate to or comment on society or current events? Can you relate to it personally in any way? What is your opinion of its message?
