In this post we share courses to help in different ways with improving the lives of children across the globe.
Help children grow and develop
The first part of solving a problem is understanding it. To help solve the problems children face we must understand how they grow and develop as infants.
Good nutrition is an enormous part of helping an infant become a healthy child and then a healthy adult. The right foods can help prevent disease and ensure a child is getting all the nutrients they need to grow mentally and physically.
Along with joy children also bring a fair amount of fear – from trips and falls, to putting the wrong thing in their mouths, a child’s curiosity comes with risks. You might not be able to stop accidents happening, but you can learn how to respond appropriately.
Helping children who have experienced trauma and poverty can be a difficult task, but immensely rewarding. Learn how to make a difference in children’s lives.
Try the course Caring for Vulnerable Children Develop an understanding of some of the approaches involved in caring for vulnerable children with the course following the story of ‘Billy’ an imagined vulnerable boy.
What’s the best way to care for a child with an autism spectrum disorder (ASD)? How can we help children with learning disabilities (LDs)? Both ASDs and LDs challenging conditions it’s crucial to have strategies in place to help children manage them.
✓ Create designs and art using code ✓ Learn a bit about the history of design, and think about the future ✓ Think about the relationship between people, machines and creativity
✓ Combines theory and practice ✓ Taught by University of Kent, who have 30 years experience in functional programming ✓ Learn the life-cycle of an Erlang process
✓ Get an intro to high performance computing for big data analysis ✓ Learn basic clustering, regression and classification ✓ Understand the basic problems of supervised and unsupervised learning
The future of learning and the future of work are converging. At a time when globalization, technological advancements, and social networks are reshaping our lives, they are also causing a rate of change that is outpacing human adaptability. This is what inspired us to launch Coursera for Business in 2016 – to partner with governments and organizations around the world in their efforts to transform the workforce in the face of accelerating change. Today,1,500+ companies and organizations use Coursera for Business as they upskill their employees to compete in the new economy. But there are still many parts of the world that have yet to benefit from the transformative learning content and experience of our enterprise platform.
Today, I’m excited to announce that Coursera for Business is expanding into the Middle East – a region propelled by the boundless energy of 300 million people, but also constrained by a 31% youth unemployment rate. Coursera will be a strategic partner to government and major employers in the region, accelerating their efforts to develop a talent base that delivers on the ambition of becoming a knowledge-based economy, where the industrial base is no more dependent on natural resources but one that is powered by technology and innovation.
We’re kicking off our expansion in the region with a number of public and private sector customers. Most notable among those is an ambitious partnership with the Abu Dhabi School of Government (ADSG) to train 60,000 government employees in critical leadership and technical skills such as data science, artificial intelligence, and digital transformation. As our largest government partnership to date, we are excited to see this become a global model for public sector skills transformation.
Dubai Electricity and Water Authority (DEWA), Etihad Airways, TECOM Group, and Dubai Asset Management are some of the other major employers in the region who have partnered Coursera to upskill employees as part of their digital transformation roadmap. It is crucial to our mission that businesses, irrespective of their size, are able to access Coursera at their workplace; we’re thrilled to see that more than 35 small and medium-sized businesses in the region are using our self-serve platform to ensure their employees are up-to-date with the latest skills required to compete in their industries. To make our content more accessible to Arabic-speaking learners, we are offering 70 courses with Arabic subtitles and 30 fully translated, with more to come over time. Coursera will also be opening an office in Abu Dhabi under Zayd Badwan’s leadership to better serve the region.
With the opportunity to develop a highly skilled workforce driving innovation, help transition the economy and become a strategic partner to government and companies in their efforts to invest in the future – we couldn’t be more excited about what’s ahead.
Codecademy’s very own Nick Duckwiler (left) and Ryan Tuck from Warby Parker (right) in our office. (📷: Mitch Boyer)
Last month, Codecademy and Warby Parker came together to work on a special Learn SQL from Scratch Capstone Project. It was during this time when I met Ryan Tuck, a Data Engineer at Warby, who played a major part in this partnership. So when he decided to drop by our office for the final QA round, I had to break out my notebook and ask some questions. Enjoy.
Hey Ryan, let’s start off with a question I’ve had for a while — what is a Data Engineer? (Is it similar to a Data Analyst or a Software Engineer?)
At Warby Parker, data engineers are responsible for creating and maintaining the plumbing required to support the data and reporting needs of the business. We use software engineering practices to automate the work of data cleaning, normalizing, and model building so that data is always ready to be consumed by data analysts in every department.
What languages/frameworks do you use at Warby?
On data engineering, we use Python as our general purpose programming language, as do most of the other teams in our Technology department. When it comes to databases, we use PostgreSQL for the majority of our SQL needs, and are beginning to use Amazon Athena and Google BigQuery for some of our larger datasets. We use Looker as our exclusive business intelligence entry point to all of this data.
What are some of the projects you worked on?
I’ve had the privilege of working with a lot of of smart people in every department at our company to help them solve their varied data needs, from reconciling financial data with the Accounting team to automating and modeling standardized performance metrics for our team of over 200 customer experience advisors.
As part of a team of five supporting the data needs of a rapidly growing company, I’ve tried where possible to focus on helping our analysts solve their own problems. This includes helping people learn Python and commit to our codebase, guiding the creation of data models in SQL, and encouraging people to submit pull requests to add features in Looker, our BI tool.
Seeing dozens of otherwise “non-technical” colleagues opening up PRs on a daily basis, and consequently being part of the democratization of tech that we value at Warby Parker, is probably the most rewarding “project” I’ve been a part of.
One project finished recently during our first annual “Hackweek” is called Pipes, which allows anyone at the company to easily move large amounts of data from wherever to wherever (Looker, Google Sheets, PostgreSQL, BigQuery, etc) on a regular cadence, or manually through a simple one-line chatbot interface. The adoption has been overwhelmingly positive and we’re looking to grow this sort of tooling out even more.
“We use software engineering practices to automate the work of data cleaning, normalizing, and model building so that data is always ready to be consumed by data analysts in every department.”
What got you into the data field?
I’ve always been drawn to analytical fields like math, and became pretty proficient in Excel during some internships in college. Once I had learned to program and learned more about data science and its applications in artificial intelligence, I knew that anything I could do to immerse myself in the world of data would be a step in the right direction.
Three and a half years ago, I landed a job as a junior software engineer at Warby Parker not fully knowing what I was in for, but am so glad I got the opportunity to help build tools to support an interesting and ever-changing data-driven culture here.
Where did you learn SQL and Python?
I had a background in C++, and was exposed to Python through an Intro to Data Science course. When Warby Parker hired me onto the Data team in 2015, I had never written a SQL query in my life, but picked it up quickly and within a few months started up internal SQL training classes, which I still teach on a monthly basis.
What does your tattoo say?
The ultimate cheatsheet.
This is Bayes’ Theorem, which is an equation that describes how to update probabilities given new evidence. Two summers ago I worked on building a tool to help predict weekly fantasy football performance. Some colleagues suggested a Bayesian approach would be appropriate, since there aren’t really enough data points in an NFL season to be able to use statistical approaches that require larger datasets, and I’d want to regularly update my predictions after each player’s latest performance.
I did a deep dive into understanding the (simple) math underlying Bayes’ Theorem and came out of that experience with a whole new worldview, understanding my entire knowledge of the world as a big and intricate probabilistic model that I was continuously updating with every experience I ever have. It was pretty transformative, and I figured that was worth a tattoo.
What is a concept in SQL/Python that’s essential to your work?
Donald Knuth said, “Premature optimization is the root of all evil.” I’ve generally found this to be true, and try to live by it in my work. For example, I’ll generally prefer to keep a data model simple by rebuilding it for all time on a daily basis using a single SQL query instead of making a more complicated model that requires iteratively adding to a table, keeping track of state, updated timestamps, when something last ran, etc.
A wise man once said, “Duplicating data makes things go fast,” but databases are already impressively fast to begin with, without implementing anything to improve performance. Ultimately, I almost always approach a problem thinking about optimizing for my time over machine time, for readability over performance, and for introducing as little cognitive overhead as is required by the problem at hand. Only once performance issues or readability issues present themselves will some code be worth a rewrite.
Last question! Since you wrote Warby Parker’s internal SQL training courses, I know there gotta be some inner Curriculum Developer in you. Can you teach a SQL concept in 2 minutes?
Sure! Have you ever written a query that yields some result set and you think, “I’d love to query the stuff I just produced like it was a table?” Enter the WITH clause.
Suppose I have a mega query that gives the transaction summaries:
select
transactions.date as transaction_date,
sum(items.price) as total_cost,
count(*) as number_of_items
from
transactions
inner join
customers
on
customers.id = transactions.customer_id
inner join
transaction_items
on
transactions.id = transaction_items.transaction_id
inner join
items
on
items.id = transaction_items.item_id
Using WITH, I can create a temporary table within my query that I can SELECT from and treat it just like a regular old table.
I will put everything from the previous query in a parentheses and use WITH to give it the name transaction_summaries.
Then I’ll apply the date and customer filtering down below for a more readable query, to separate out all the JOIN logic from the actual WHERE filters that I want to apply on that data.
with transaction_summaries as (
select
transactions.date as transaction_date,
sum(items.price) as total_cost,
count(*) as number_of_items
from
transactions
inner join
customers
on
customers.id = transactions.customer_id
inner join
transaction_items
on
transactions.id = transaction_items.transaction_id
inner join
items
on
items.id = transaction_items.item_id
)
select
*
from
transaction_summaries
where
first_name = 'beyonce'
and
transaction_date > '2018–01–01'
order by
total_cost desc
limit
5
If you’re familiar with subqueries, this does a similar thing but makes the SQL far more readable, even if your query isn’t quite as performant as it would have been. This is essentially an implementation of the mantra “Don’t Repeat Yourself” that’s common in the world of programming.
Incredible. And love the SQL styling! 😍
Huge shout out to Ryan and the whole Warby Parker team for making this partnership happen. Special hat tips for behind-the-scenes support from:
A Day in the Life of a Software Engineer (via Life of Luba)
With Airbnb came a revolution of sorts in the world of vacation travel and culture. We sat down with Luba Yudasina, a YouTuber, an opera singer, and a Software Engineer on the Airbnb’s Homes Platform team, to discuss software engineering and her programming journey—from Codecademy to Airbnb!
Hey Luba, let’s start with the basics! What does a Software Engineer on the Platform team do at Airbnb?
Homes Platform’s mission is to create the building blocks to power all Homes categories. Any project undertaken by our team should be reusable and extensible in some way. This means that as a backend engineer, I have a lot of opportunities to work on impactful technical projects that create systems and services to support Homes, as well as collaborate across teams to come up with the best architectural decisions and designs.
Recently, our team wrote a blog post on classifying Room Types into categories using Machine Learning and computer vision. The room-type classification problem largely resembles the ImageNet classification problem, except our team’s model outcomes are customized room-types.
After a few experiments with various models, the team chose ResNet50 due to its good balance between model performance and computation time. To make it compatible with our use case, we added two extra fully connected layers and a Softmax activation in the end.
Let’s rewind a little bit. Coming from a chemical engineering background in college, how did you make the switch into programming?
I went to the University of Waterloo in Canada—a university with the biggest co-op program in the world. Co-op means that to obtain a bachelor’s degree you must complete a certain number of internships. If you are in Engineering at Waterloo, you must complete 5 internships to graduate.
In my first and second years, I interned at chemical engineering companies and afterwards I couldn’t see myself working in the field full-time. That’s why I’m particularly grateful that I studied at Waterloo: if not for co-op, I probably would not have realized I didn’t want to work in chemical engineering until getting a full-time job after graduation.
I happened to have a lot of friends in Computer Science and Software Engineering right when I realized Chem Eng wasn’t for me. They really encouraged me to try coding, and when I decided to follow their lead I never looked back! My first online programming course was Web Development on Codecademy 🙂
“It’s a really cool time to be a software engineer and even cooler to be a female software engineer, because this is the time when women start to embrace their own unique identities and be ok with not being ‘one of the dudes.'” -Luba Yudasina
When I decided I wanted to learn computer science on my own, my goal was to get an internship in the field because working as a software engineer at a tech company would be the best test to really know if it was for me.
I happened to be in Munich, Germany on academic exchange for a whole year when I was learning how to code, so I hustled as much as I could while being there to get experience to learn quicker and have something to put down on my tech resume.
Almost immediately after arriving in Germany, I got a part time job as a developer at a game publishing company. I had a good friend in Computer Science at my German university: her and I ended up working on an Android app as a side project, etc. When I was ready, I started preparing for technical interviews. I then leveraged my network to refer me to companies and do mock technical interviews with me.
Yelp was really random though—a Yelp recruiter looked at my LinkedIn profile and didn’t even message me, but I messaged them anyway asking about internship opportunities, and that’s how I got my interview there!
Airbnb HQ in San Franciso
What is an essential app/item in your day-to-day?
Code searching! A lot of software engineering is problem solving and a lot of it is understanding other people’s code and the reasoning behind writing it a certain way. Searching through the codebases is almost essential to my day to day. Whenever I build something new or build on top of already existing tech, I need to understand how it works and is written, and code search is vital to this.
At Airbnb we use Google’s Codesearch for these purposes, but developers (myself included) also frequently use their IDEs to search for relevant code. I mostly use RubyMine or IntelliJ (depending on the codebase I’m working with).
In your videos, you’ve mentioned the intersection of gender and technology. Can you speak a bit more about that?
It’s a really cool time to be a software engineer and even cooler to be a female software engineer, because this is the time when women start to embrace their own unique identities and be ok with not being “one of the dudes.”
I think it’s particularly important to redefine the stereotypes, and I hope that with my own example I can show young girls and women interested in the field that you don’t have to give up your feminine side to be a software engineer and still be into fashion, or makeup, or art (I personally sing opera) and have other interests outside of coding and be successful in the field.
Before we wrap up, do you have anything else you would like to say to our learners?
Don’t be discouraged, learn and absorb as much as you can! If you don’t understand a concept or can’t build a project right away, know that with practice, perseverance and concentration you will get there!
Take advantage of such amazing tools as Codecademy that are there for you to take and learn. Learning anything new can be frustrating, but knowing that you can do it, staying curious, asking questions and not losing your motivation is the key to success.
Huge shoutout to Luba for this insightful interview. It’s always incredibly moving to see a Codecademy learner go on to do bigger things. Go subscribe to her YouTube channel, Life of Luba.
And thank you to the whole Homes Platform/Engineering team at Airbnb for the support. Check out their wonderful open source projects on airbnb.io.
The word extirpate has appeared in nine articles on NYTimes.com in the past year, including on July 5 in “Who’s Afraid of the Big Bad Wolf Scientist?” by Christopher Solomon:
In 1973, Congress passed the landmark Endangered Species Act. Within a few years, the gray wolf was listed as “endangered” throughout the West. Gray wolves were successfully reintroduced in the mid-1990s when the federal government relocated 31 wolves from Canada to Wyoming’s Yellowstone country and 35 to central Idaho. Since then, wolves have wandered across state lines to take up residence again in their former homes in Oregon and California.
Wherever the predators have arrived, blistering conflicts have followed. Shouting matches at public meetings. Threats to government officials. Dead livestock. Dead wolves. So in 2008, when biologists found that the first wolves had returned to Washington since the animals were extirpated there in the 1930s, officials pledged to learn from other states’ mistakes.
Jeff Bezos, the founder of Amazon and the owner of The Washington Post, accused of “extortion and blackmail” on Feb. 7, laying out a theory that brought together international intrigue, White House politics, nude photos and amorous text messages.
I am pleased to report that the American dream is alive and well for an overwhelming majority of Americans.
This claim might sound far-fetched given the cultural climate in the United States today. Especially since President Trump took office, hardly a day goes by without a fresh tale of economic anxiety, political disunity or social struggle. Opportunities to achieve material success and social mobility through hard, honest work — which many people, including me, have assumed to be the core idea of the American dream — appear to be diminishing.
But Americans, it turns out, have something else in mind when they talk about the American dream. And they believe that they are living it.
Last year the American Enterprise Institute and I joined forces with the research center NORC at the University of Chicago and surveyed a nationally representative sample of 2,411 Americans about their attitudes toward community and society. The center is renowned for offering “deep” samples of Americans, not just random ones, so that researchers can be confident that they are reaching Americans in all walks of life: rural, urban, exurban and so on. Our findings were released on Tuesday as an American Enterprise Institute report.
What our survey found about the American dream came as a surprise to me. When Americans were asked what makes the American dream a reality, they did not select as essential factors becoming wealthy, owning a home or having a successful career. Instead, 85 percent indicated that “to have freedom of choice in how to live” was essential to achieving the American dream. In addition, 83 percent indicated that “a good family life” was essential.
The “traditional” factors (at least as I had understood them) were seen as less important. Only 16 percent said that to achieve the American dream, they believed it was essential to “become wealthy,” only 45 percent said it was essential “to have a better quality of life than your parents,” and just 49 percent said that “having a successful career” was key.
The Opinion piece continues:
The data also show that most Americans believe themselves to be achieving this version of the American dream, with 41 percent reporting that their families are already living the American dream and another 41 percent reporting that they are well on the way to doing so. Only 18 percent took the position that the American dream was out of reach for them
Collectively, 82 percent of Americans said they were optimistic about their future, and there was a fairly uniform positive outlook across the nation. Factors such as region, urbanity, partisanship and housing type (such as a single‐family detached home versus an apartment) barely affected these patterns, with all groups hovering around 80 percent. Even race and ethnicity, which are regularly cited as key factors in thwarting upward mobility, corresponded to no real differences in outlook: Eighty-one percent of non‐Hispanic whites; 80 percent of blacks, Hispanics and those of mixed race; and 85 percent of those with Asian heritage said that they had achieved or were on their way to achieving the American dream.
Students, read the entire article, then tell us:
— What does the American dream mean to you? Did reading this article change your definition? Do you think your own dreams are different from those of your parents at your age? Your grandparents?
— Do you believe your family has achieved, or is on the way to achieving, the American dream? Why or why not? Do you think you will be able to achieve the American dream when you are older? What leads you to believe this?
— Do you think the American dream is available to all Americans or are there boundaries and obstacles for some? If yes, what are they?
— The article concludes:
What conclusions should we draw from this research? I think the findings suggest that Americans would be well served to focus less intently on the nastiness of our partisan politics and the material temptations of our consumer culture, and to focus more on the communities they are part of and exercising their freedom to live as they wish. After all, that is what most of us seem to think is what really matters — and it’s in reach for almost all of us.
Do you agree? What other conclusions might be drawn? Does this article make you more optimistic about this country and your future?
— Is the American dream a useful concept? Is it helpful in measuring our own or our country’s health and success? Do you believe it is, or has ever been, an ideal worth striving for? Is there any drawback to continuing to use the concept even as its meaning evolves?
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.
