Mr. Newsom said the outgoing governor had left the state “in better shape than probably any governor in modern times.” But he said that Mr. Brown had given him a somewhat mordant warning as they discussed what was around the corner.
“‘Good luck,’” he quoted Mr. Brown as saying. “’Cause he sees the headwinds, he sees the fixed costs, he sees the hockey stick of health care and pensions. He sees all this building pressure, he knows what the Legislature is revving up to do and all these interest groups that are a deeper part of that appetite than the Legislature. They are all expecting the next governor to solve their problems.”
The MOOC platform FutureLearn recently published a series of articles exploring who its learners are. Based on a survey of 7,000 learners, FutureLearn’s User Experience Researcher Tracey Walker identified seven archetypes, corresponding to seven patterns of behavior among users of FutureLearn.
Walker grouped these archetypes into three types: Work and Study, Personal Life, and Leisure. Work and Study describes people who are primarily on the site to improve their career prospects. Personal Life archetypes are using FutureLearn to address aspects of their personal lives. Leisure archetypes are pursuing hobbies or a love of learning.
The seven archetypes are summarized below. Do you see yourself in any of them?
Work and Study Archetypes: Advancers, Explorers, and Preparers
Advancers: Advancers are working in their field of choice and are seeking to pick up additional work-related skills. They are primarily in the age range of 26-35 and are likely to purchase upgraded course certificates.
Explorers: These learners are considering a career change and are using online courses to evaluate the options. They are also mainly in the age range of 26-35 and are slightly less likely than Advancers to purchase course certificates.
Preparers: Preparers are younger (19-35) and, as the name suggests, are either preparing for a chosen career field or have recently started working in that field. These learners are using online courses to pick up skills that will help them stand out. Like Advancers, they are likely to purchase course certificates.
Personal Life Archetypes: Fixers and Flourishers
Fixers: These learners are evenly distributed across a wide range of ages (19-75). They are using online courses to manage a personal life situation, such as their health or the health of a loved one, a political situation, or a social issue. They are generally uninterested in certification.
Flourishers: These learners are using online courses for personal development. They are the group most likely to take multiple courses.
Leisure Archetypes: Hobbyists and Vitalizers
Hobbyists: Among Hobbyists, a large portion are retired and fall between the ages of 56-75. These learners take courses to support their personal interests and projects.
Vitalizers: For this group, learning itself it their hobby. Like Hobbyists, many are retired. Vitalizers have wide ranging interests and may take courses on a diversity of topics.
The researchers emphasized that it common for there to be overlap among these types and that few people identified with only one archetype.
What about you? What kind of learner are you? Let us know in the comments.
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.
Spring is almost here! Only a few more weeks and we can say goodbye to winter until next year and say hello to fresh blooms, butterflies, and many more beautiful signs of spring. Welcome spring to your home or office with this pretty free printable.
On Feb. 7, Representative Alexandria Ocasio-Cortez of New York and Senator Edward J. Markey of Massachusetts introduced a congressional resolution known as the Green New Deal — a sweeping and ambitious call for a “10-year national mobilization” to combat climate change.
Liberal Democrats put flesh on their “Green New Deal” slogan on Thursday with a sweeping resolution intended to redefine the national debate on climate change by calling for the United States to eliminate additional emissions of carbon by 2030.
They continue:
… as a blueprint for liberal ambition, it was breathtaking. It includes a 10-year commitment to convert “100 percent of the power demand in the United States” to “clean, renewable and zero-emission energy sources,” to upgrade “all existing buildings” to meet energy efficiency requirements, and to expand high-speed rail so broadly that most air travel would be rendered obsolete.
1. What kind of a congressional proposal is the Green New Deal? If it is approved by Congress, what will happen?
2. The resolution uses two major reports as its guide. What picture of climate change do those reports present?
3. What are the central goals of the Green New Deal? Give three examples of provisions intended to meet them.
4. How have critics responded to the Green New Deal? Why has there been some confusion about what exactly is in the resolution?
5. Why does the resolution include issues of social justice, like jobs, housing, human rights and oppression? How does it connect these issues to climate change?
6. The article says the Green New Deal would “change the way we design buildings, travel and eat.” In your own words, explain how.
7. From where does the Green New Deal take its name and inspiration? Why do you think the drafters of the resolution chose this historical precedent?
8. How much might the Green New Deal cost? Why is it difficult to calculate this figure?
9. The article concludes:
There is going to be a lot more political jockeying around the Green New Deal in coming weeks and months …
It is likely that the Green New Deal will remain a lightning rod throughout the 2020 presidential campaign.
How has the Green New Deal affected debate on climate change and the 2020 presidential campaign?
Finally, tell us more about what you think:
— What do you think of the Green New Deal? Is it a bold vision to address the dire situation of global warming? Or is it an unrealistic, everything-but-the-kitchen-sink approach that will not lead to real changes? Which aspects of the Green New Deal resonate the most? Which do you find least persuasive?
— How important is the issue of climate change? Do you think this country is doing enough to address the problem? Is the Green New Deal a step in the right direction or an example of government overreach?
Nobody has to be a progressive to be concerned about the environment. Nobody has to be a progressive to respond to climate change. Any proposal that conditions response to climate change on the adoption of the full progressive platform is not only doomed to fail, but raises the question of whether the declared climate emergency is more pretext than crisis. There’s a need for a serious discussion about our climate. The Green New Deal is not serious.
— Do you agree? Is the Green New Deal wrong to connect climate change to other progressive issues?
What would the home of your dreams look like? Would it be a minimalist apartment in a bustling city? A mansion with 40 rooms, a basketball court and a pool? A farm with more animals than you could count? A shack on the beach so you could surf every day?
Tell us in the comments in as much detail as possible. Then, read the related Opinion piece to find out about the newest trends in home design and construction.
Find many more ways to use our Picture Prompt feature in this lesson plan.
The city’s votes were sprinkled widely across the massive field of 14 candidates who had hoped to replace Mr. Emanuel, who didn’t run for a third term. With 92 percent of the votes counted, Ms. Lightfoot had the highest vote tally, with about 17 percent. Ms. Preckwinkle had 16 percent, and Mr. Daley, who was well funded and who many here had expected to easily make the runoff, came in just below 15 percent.
…. For weeks, the sheer number of candidates seemed to have left some Chicagoans flummoxed — unsure, even in the final hours, whom they would vote for. Some political strategists said they wondered if that might discourage some people from voting at all in the election, which is technically nonpartisan, though Democrats reliably win.
I think they really already are getting paid. When we talk about college athletes getting paid we’re usually talking about the best of the best. The ones who have full scholarships to their colleges, many times these colleges would costs in the tens of thousands some even in the hundred thousand, but college athletes don’t need to pay anything. They are given access to some of the best facilities in the world and sometimes even better than professional sports teams. With these facilities, these players can push themselves to their limits and become the best versions of themselves.
If you bring actual money into college sports it will change it forever, it will change the dynamic of the whole sport. Many players love being in college and if they choose the right college and coach they will always be welcomed back and a second home. Not only are the players given the facilities to develop into great athletes but if they choose a great coach, the coach will mold them into great young men who are fit for anything. At Clemson University there is an emphasis on this, Dabo Swinney the head coach for the football team only recruits athletes that he finds fitting for the program. The whole vibe at Clemson is a very good vibe and many players build bonds that will last forever. In all, the college experience is a great one and it really isn’t the college experience after players are paid, it just becomes another division of professional sports.
College sports are only to represent your college and make them proud. If they want money and the sports department is not giving it then let them not participate. I am sure the team is not going to lose out. Usually, in sports, there are a lot of people who try out so it is easy to find a replacement for him. Moreover, all the sports gets you good fame and a good personality.
College sports are a preparation for professional sports. This drives many athletes to attain college level skills; they use the more competitive game and intense training to get a feel for a higher level. Tracy argues that too many organizations “reap billions of dollars from the efforts and talents of preprofessional athletes.” Yes, their games are televised, but this doesn’t just bring profit to companies and colleges. It publicizes players and gives them an opportunity to be scouted by professional coaches.
I feel as a student athlete, your attending school not only to play sports but to also obtain good education to succeed in life. When your playing a sport for a school, your basically representing your school for whatever sport your playing. While playing for the school, the coordinators for the sports and other volunteers put in a lot of money to make sure you have the essentials you need in order to play … College Athletes are provided with so much stuff that they don’t really need to worry about money. They are well taken cared of.
At first, I believed that college athletes should be paid, because they work as hard and are as good as professionals, provide a source of entertainment, and sell millions of tickets per game they play. However, after reading through the comment section, I’ve changed my mind … The whole point of college is to get a good education and to use that education in the future to help them guide their way to their careers. However, if they start getting paid, they will focus on money and not their education. That can result in a decrease of interest in education and grades of college players will also decrease, leading to the chances of being a pro athlete decreasing as well. Furthermore, if college athletes get paid, the pay will most likely be different for each player, and that will create a competitive atmosphere among the same team of athletes. If college athletes get paid, the pay of each player will be what defines them, instead of their skills. Therefore, I think that college athletes shouldn’t be paid.
Yes, college athletes deserve a cut of the profits.
In my opinion, I do believe college athletes should be paid or at least be able to get some type of income. These athletes are bringing in over 11 billion dollars a year, including TV broadcasting, tickets, and even sponsors. Also the NCAA prohibits these athletes from getting a job or receiving any type of income, and some of these athletes don’t come from high, rich families and they don’t receive a full ride so they don’t know how to pay for the rest of their tuition.
Below, the February 2019 edition of Teenagers in The Times. This roundup of the news and feature stories about young people that have recently appeared across sections of NYTimes.com appears on the first Thursday of each month during the school year.
For ideas about how to use Teenagers in The Times with your students, please see our lesson plan and special activity sheet, both of which can be used with this or any other edition.
In a class-action lawsuit, three women claim Yale has fostered an environment where alcohol-fueled gatherings at fraternity houses dictate the undergraduate social scene.
“Our country has most of the best colleges in the world. Students should be able to afford them, and borrowers should not be crushed by debts,” states this Opinion essay.
