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What Does an A.I. Engineer Do?

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What Does an A.I. Engineer Do?
What Does an A.I. Engineer Do?

A.I. Engineers are in demand in most industries, and there’s a good reason for this. If you’re wondering what an A.I. Engineer does, we’ll break it down for you.

Businesses can use the massive amounts of data they generate daily to improve and simplify common, everyday tasks. With the right A.I. systems, companies can take these tasks off the hands of their teams so they can focus on more important work. Technologies like speech recognition, business process management, and image processing are only some of the A.I. technologies changing the world.

Companies need A.I. Engineers to put these systems in place, maintain them, and adapt them to changes in the business. In this article, we’ll explore what A.I. Engineers do, what kind of skills they need, and how you can get started on the A.I. engineering career path.

But first, let’s examine what A.I. engineering is and how it relates to machine learning.

What is artificial intelligence?

A.I., or artificial intelligence, uses computers and machines to emulate how the human mind operates to accomplish problem-solving and decision-making tasks. It combines the robust data sets we generate daily with computer science to achieve this goal in its simplest form.

In A.I., machines learn the outcomes of specific actions by crunching mountains of past data. They then use the insights gained from this process to make decisions about future actions and solve problems. At the same time, data is collected on the machine’s decisions and is used to correct and perfect future actions and decisions.

What’s the difference between A.I. and machine learning?

Machine learning and artificial intelligence are often lumped together in the same definition, but they aren’t necessarily the same. In our forums, one of our learners, J, provides a helpful explanation:

“Artificial intelligence can be described as when machines carry out tasks in an intelligent or smart way, based on set rules to solve certain problems. Artificial intelligence, or A.I., makes decisions, learns, and solves problems similar to how humans would.

Machine learning, on the other hand, is a subset of artificial intelligence. It’s when we give machines data and have them learn from that data on their own, without being explicitly programmed. Machine learning models learn from the data and try to make improvements to its predictions over time.”

So machine learning is a subset of the A.I. field, but not all A.I. is machine learning. A.I. is a broader field. Check out our article on what a Machine Learning Engineer does to learn more.

What does an A.I. Engineer do?

A.I. Engineers develop new applications and systems to:

  • Enhance the performance and efficiency of business processes
  • Help the business make better decisions
  • Lower costs
  • Increase revenue and profits

Simply put, they use software engineering and data science to streamline a business with automation.

Many of an A.I. Engineer’s tasks overlap with those of a Machine Learning Engineer. Some of the responsibilities of an A.I. Engineer include:

  • Coordinating with business leaders and software development teams to determine what business processes can be improved by using A.I.
  • Creating and maintaining the A.I. development process and the infrastructure that it runs on.
  • Applying machine learning techniques for image recognition.
  • Applying natural language processing techniques to text and voice transcripts to pull insights and analytics from this data.
  • Building and maintaining chatbots that interact with customers.
  • Developing AI-driven solutions that mimic human behavior to accomplish repetitive tasks currently done by people.
  • Building, training, and perfecting machine learning models.
  • Simplifying the machine learning process so that other business applications can interact with them using APIs.
  • Building recommendation engines for shopping sites, streaming services, and other applications.
  • Developing data pipelines that streamline the process of transforming raw data into the structured data necessary for A.I. processes.

Required skills for an A.I. Engineer

A.I. is a broad field, and an A.I. Engineer requires both the skills of a Software Engineer and those of a Data Scientist. It may even help to know mathematics and statistics.

An A.I. Engineer definitely needs to know at least one programming language and will usually end up learning multiple during their career. Many of the tools that A.I. Engineers use to make their job easier will require knowledge of Python, R, or Java.

To build and work with machine learning models, an A.I. Engineer will also need to know the fundamentals of various machine learning frameworks, like TensorFlow, Theano, PyTorch, and Caffe. They’ll also need to know how to turn raw data into the features that machine learning models use.

Additionally, an A.I. Engineer must have experience with a variety of machine learning model types and what type of jobs they work best for. These types include:

  • Neural networks
  • Recurrent neural networks
  • K-nearest neighbors algorithms
  • General adversarial networks
  • Supervised learning
  • Unsupervised learning
  • Random forests
  • Reinforcement learning

To actually create new models and understand how they work, an A.I. expert may have to know linear algebra, probability, and statistics instead of using pre-built models. These topics help you understand hidden Markov models, Naive Bayes, Gaussian mixture models, and linear discriminant analysis — the techniques used in machine learning.

Data is also a vital part of an A.I. Engineer’s job. A lot of that data is stored in relational database management systems, so having a basic knowledge of SQL, the language of databases, comes in handy. Still, some of this data will be stored in unstructured or semi-structured data stores — so knowing big data technologies like Apache Spark, Apache Hadoop, Cassandra, and MongoDB is a big plus.

A.I. Engineers require more than technical skills, though. They must also:

  • Be meticulous and detail-oriented because small inconsistencies in data can cause big discrepancies in machine learning models.
  • Have excellent communication skills because many of the people they work with won’t understand much of what they do. They’ll have to explain the results of their tasks in a way that anyone can understand.
  • Be good at big-picture thinking so they can understand business needs and build A.I. systems that benefit the company.

A.I. Engineer salary

A.I. Engineers make good money. The average salary for an A.I. Engineer in the U.S. is over $160,000. In states like California, the average reaches close to $200,000.

The demand for A.I. Engineers has always been high, so expect job openings and pay to increase in the future. The U.S. Bureau of Labor Statistics expects all Software Developer jobs to increase by 22% over the next decade, and this includes A.I. Engineers.

How to become an A.I. Engineer

Gone are the days when a computer science degree or even any college degree would be required to become an A.I. Engineer. Good Artificial Intelligence Engineers are just in too much demand to require a degree, and employers have learned that many skilled A.I. experts don’t even need one. They do it because they love the work.

If A.I. is the career path for you, and you don’t have a degree or want to spend four years learning artificial intelligence, you don’t have to. There are plenty of educational opportunities to learn A.I. online whenever you have the time and wherever you are in the world. Plus, most of the tools you need for the learning process are open-source and freely available online.

If you’re new to artificial intelligence and looking for the best place to start your journey, why not try Codecademy? Since knowing at least one programming language is a prerequisite for becoming an A.I. Engineer, a great place to start is our Learn Python 3 course.

Python is one of the top languages used by Data Scientists and A.I. Engineers. It’s also a requirement of our Learn the Basics of Machine Learning course, which will introduce you to the field. You can also check out our Data Scientist Career Path that covers many of the skills you’ll need as an A.I. Engineer.

While taking these courses, make sure to also learn and work on custom A.I. projects on your own time and add both your course projects and side projects to your portfolio. Also, keep your LinkedIn profile updated with your new learning achievements and projects to make it stand out for recruiters and companies looking for A.I. Engineers. It also pays to practice interviewing skills to be ready when you get a call from a recruiter.

Keep learning today

Never stop learning. A.I. is a broad field, and learning Python and machine learning fundamentals is a great start, but each skill you add to your resume can increase your value to a company. Building Chatbots with Python will teach you how to build software that can carry on conversations like a human. Learn to Program Alexa will teach you how to write software for Amazon’s bot.

For even more courses to build your A.I. skills, check out our machine learning course catalog and revisit the skills section of this article. Good luck with your A.I. career path!


Machine Learning Courses & Tutorials | Codecademy

Machine Learning is an increasingly hot field of data science dedicated to enabling computers to learn from data. From spam filtering in social networks to computer vision for self-driving cars, the potential applications of Machine Learning are vast.

Lesson of the Day: ‘Chasing the Truth: A Young Journalist’s Guide to Investigative Reporting’

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Lesson of the Day: ‘Chasing the Truth: A Young Journalist’s Guide to Investigative Reporting’

8. Now that you have read the first chapter of “Chasing the Truth,” revisit your response to the warm-up. What did you learn about investigative journalism that you didn’t know? Why is it important? Would you want to be an investigative journalist? Why, or why not?

9. Make a prediction: After finishing the first chapter, how do you think Jodi and Megan will continue their investigation? What are some major steps they will need to take?

10. Finally, based on what you just read, what questions do you have for the authors? (We hope to feature video versions of some of them on our Jan. 27 panel, so if you’d like to ask yours that way, follow Step 2, below.)

Now that you’ve read Chapter 1, you probably realize that an investigative journalist is likely to spend considerably more time reporting a story than writing it up. Asking the right questions, finding sources who are willing to speak on the record, identifying clear evidence, and checking and double-checking all the facts takes time.

Using your own curiosity, some of the techniques you read about in “Chasing the Truth” and the advice from Megan and Jodi you’ll hear in our “Live Panel for Students: How Investigative Journalism Works,” think about what an investigative journalism project of your own could look like.

Step 1: Brainstorm your topic.

On your own or with a classmate or small group, brainstorm a list of possible issues, large or small, you’d like to investigate. Keep in mind that you’re likely to have more success investigating topics in your school or community than chasing a national or international story. Why are you interested in these subjects? Why are they relevant or important?

Our related Student Opinion question, “What Do You Want to Investigate?,” can help you get started, and offers this advice:

Think about the problems or injustices in your community or school. Consider questions you or others have about how local systems work — or don’t. Think about big investigative pieces you have read in national news outlets, and “localize” them: How does that same issue look in your area? (To help you brainstorm, you might scroll through this list of investigative pieces that have won Pulitzer Prizes or through this list of “21 Excellent Stories of Student Journalism Against the Odds.”)

When you have some ideas, we encourage you to post them and read what other students from around the world have to say in the comments section of our forum. Or, proceed to Step 2 to make a video.

What Do You Want to Investigate?

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What Do You Want to Investigate?

Use Ms. Kantor and Ms. Twohey’s groundbreaking 2017 article as your guide. You can read it either as it was originally published in The Times or via this PDF from their book, in which the authors annotate their work throughout to show you their reporting process.

Two decades ago, the Hollywood producer Harvey Weinstein invited Ashley Judd to the Peninsula Beverly Hills hotel for what the young actress expected to be a business breakfast meeting. Instead, he had her sent up to his room, where he appeared in a bathrobe and asked if he could give her a massage or she could watch him shower, she recalled in an interview.

“How do I get out of the room as fast as possible without alienating Harvey Weinstein?” Ms. Judd said she remembers thinking.

In 2014, Mr. Weinstein invited Emily Nestor, who had worked just one day as a temporary employee, to the same hotel and made another offer: If she accepted his sexual advances, he would boost her career, according to accounts she provided to colleagues who sent them to Weinstein Company executives. The following year, once again at the Peninsula, a female assistant said Mr. Weinstein badgered her into giving him a massage while he was naked, leaving her “crying and very distraught,” wrote a colleague, Lauren O’Connor, in a searing memo asserting sexual harassment and other misconduct by their boss.

“There is a toxic environment for women at this company,” Ms. O’Connor said in the letter, addressed to several executives at the company run by Mr. Weinstein.

An investigation by The New York Times found previously undisclosed allegations against Mr. Weinstein stretching over nearly three decades, documented through interviews with current and former employees and film industry workers, as well as legal records, emails and internal documents from the businesses he has run, Miramax and the Weinstein Company.

During that time, after being confronted with allegations including sexual harassment and unwanted physical contact, Mr. Weinstein has reached at least eight settlements with women, according to two company officials speaking on the condition of anonymity. Among the recipients, The Times found, were a young assistant in New York in 1990, an actress in 1997, an assistant in London in 1998, an Italian model in 2015 and Ms. O’Connor shortly after, according to records and those familiar with the agreements.

Teenagers in The Times: December 2021

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Teenagers in The Times: December 2021

Here is the December, 2021 edition of Teenagers in The Times, a roundup of the news and feature stories about young people that have recently appeared across sections of NYTimes.com. We publish a new edition on the first Thursday of each month.

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.

_________

Education

Suspect in Michigan School Shooting Faces Murder and Terrorism Charges

A 15-year-old accused of killing four of his classmates and wounding seven other people had described wanting to attack the school in cellphone videos and a journal, the authorities said.

In the Michigan School Shooting, the Prosecutor Asks, What About the Parents?

After seeing the evidence, Karen McDonald made an instinctual, and unusual, decision to charge Ethan Crumbley’s mother and father. Can she succeed?

How ‘Shadow’ Foster Care Is Tearing Families Apart

Across the country, an unregulated system is severing parents from children, who often end up abandoned by the agencies that are supposed to protect them.

Third Accuser Says Epstein and Maxwell Preyed on Her as a Troubled Teen

The accuser, who testified under her first name, Carolyn, described being preyed upon as an especially vulnerable child.

Scuba-Diving YouTuber Finds Car Linked to Teens Missing Since 2000

A YouTuber who investigates cold cases found a missing Tennessee teenager’s car submerged in a nearby river. It is at least the fourth such discovery by amateur investigators in two months.

Teen Who Sought New Life Found Death at Hands of the Police, Father Says

The family of Valentina Orellana Peralta described the terrifying moments before the 14-year-old girl, who had recently moved to Los Angeles from Chile, was killed by a stray bullet fired by a police officer.

_________

Science, Health, Technology and Sports

Chasing the Truth Chapter One: The First Phone Call

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Chasing the Truth Chapter One: The First Phone Call

Page 2 of 15

Unlike almost anyone else in Hollywood, McGowan had a history

of speaking out against sexism, even if it meant she wouldn’t get movie roles. She once tweeted out the insulting clothing requirements on a casting notice for an Adam Sandler movie: “tank that shows off cleavage (push-up bras encouraged).” In general, her tone on social media

was tough, confrontational: “It is okay to be angry. Don’t be afraid of it,”

she had tweeted a month earlier, later adding: “dismantle the system.”

a

If McGowan, as much an activist as an actress, would not have one off

the-record conversation with Jodi, which would be kept confidential,

who would?

Harvey Weinstein was not the man of the moment. In recent years, his moviemaking magic had faltered. But he still had power, specifically the power to make and boost careers. First he had invented him

self, going from a modest upbringing in Queens, New York, to concert promotion to film distribution and production, and he seemed to know how to make everything around him bigger-films, parties, and most of all, people. Over and over, he had propelled young actors to star

dom: Gwyneth Paltrow, Matt Damon, Michelle Williams, and Jennifer

Lawrence. He could turn tiny independent movies into phenomena. He

had pioneered the modern Oscar awards campaign, winning five Best

Picture statues for himself and armloads for others. His record of rais

ing money for Hillary Clinton, and joining her at countless fundraisers,

was almost two decades long. When President Obama’s daughter Malia

had sought an internship in film, she worked for “Harvey”—first name only, used even by many strangers. By 2017, even though his movies were

less successful than they used to be, his reputation remained outsized.

Rumors had long circulated about his treatment of women. But

13 –

A Live Panel for Students: How Investigative Journalism Works

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A Live Panel for Students: How Investigative Journalism Works

In October 2017, New York Times journalists Jodi Kantor and Megan Twohey broke the story of the Hollywood producer Harvey Weinstein’s alleged sexual misconduct. Their reporting helped ignite the #MeToo movement and initiate policy changes around the world.

In “Chasing the Truth,” their new book for young people, Ms. Kantor and Ms. Twohey share the methods behind their reporting process as a guide for aspiring journalists. They argue that you don’t have to be a New York Times journalist to conduct investigations that reveal the truth and make a difference in your community.

Ms. Kantor and Ms. Twohey will speak directly to students about investigative journalism at our live panel on Jan. 27. We recommend that classrooms prepare for the panel with the two teaching resources below, which include excerpts from “Chasing the Truth.” We also encourage students to submit video questions by Jan. 20 that may be played during the panel.

Before viewing the panel, we ask teachers and students to use one or more of the following resources, each of which features an excerpt from the book, “Chasing the Truth.”

  • Our Student Opinion question asks students to share what they would like to investigate.

  • Our Lesson of the Day invites students to read the first chapter of “Chasing the Truth” and examine how Ms. Kantor and Ms. Twohey began their investigation.

What questions do you have for Ms. Kantor and Ms. Twohey? Submit a video through this form by 11:59 Pacific time on Jan. 20, and we may play it during the panel. Each video should be no longer than 30 seconds.

Students are also invited to submit a short video sharing what they would like to investigate and why. Learn more in our Student Opinion question.

For their work on Harvey Weinstein, which helped to shift attitudes, and spur new laws, policies and standards of accountability around the globe, Ms. Kantor and Ms. Twohey, together with a team of colleagues who exposed harassment across industries, were awarded the Pulitzer Prize for public service, journalism’s highest award. They also received or shared in numerous other honors, including a George Polk award and being named to Time magazine list of 100 most influential people of the year. “She Said,” the book Ms. Kantor and Ms. Twohey wrote recounting the Weinstein investigation, was called “an instant classic of investigative journalism” by the Washington Post. “Chasing the Truth” is a young readers’ adaptation of that work.

But before they broke the Weinstein story, both journalists had done extensive reporting that has helped to spur societal change. Jodi Kantor’s article about the havoc caused by automated scheduling systems in Starbucks workers’ lives led to changes at the company and helped spark a national fair-scheduling movement. After she and David Streitfeld investigated punishing practices at Amazon’s corporate headquarters, the company changed its human resources policies, introducing paternity leave and eliminating its employee ranking system. And Ms. Kantor’s report on working mothers and breastfeeding inspired two readers to create the first free-standing lactation suites for nursing mothers, now available in hundreds of airports and stadiums. Ms. Kantor has also done extensive reporting on Barack and Michelle Obama, and her best-selling book “The Obamas,” about their behind-the-scenes adjustment to the jobs of president and first lady, was published in 2012.

Megan Twohey has reported on Donald J. Trump, helping to reveal allegations of sexual misconduct against him, his business interests in Russia and illegal efforts to silence two women who claimed they had affairs with him. She exposed an underground network where parents gave away adopted children they no longer wanted to strangers met on the Internet in a practice known as private re-homing. The series, “The Child Exchange,” showed how the dangerous black market took place with no government oversight and at great risk to children, and was a finalist for the 2014 Pulitzer Prize for Investigative Reporting. Ms. Twohey was one of the first journalists to expose how police and prosecutors were shelving DNA evidence collected after sex crimes, robbing victims of the chance for justice. In response to her stories, Illinois passed the first state law mandating the testing of every rape kit.

Top 13 OOPs Interview Questions (And How to Answer Them)

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Top 13 OOPs Interview Questions (And How to Answer Them)
Top 13 OOPs Interview Questions (And How to Answer Them)

If you’re getting ready for your first interview for an Object-Oriented Programming (OOPs) role, congratulations! We know you’ve put in a lot of time and effort to get this far. You’re probably now wondering what kinds of OOPs interview questions to expect.

That’s why we’ve put together this list of 13 common OOPs interview questions and how to answer them. Between studying these OOPs-specific questions and our guide on technical interviews, you’ll feel confident and prepared before the big day.

1. What are OOPs?

Object-oriented programming is a programming model based on objects rather than procedures or functions. Objects contain data as well as methods, or functions, that operate on that data.

2. What are the advantages of OOPs?

There are many advantages to OOPs, including:

  • OOPs abstraction helps make code easier to use and understand.
  • OOPs reuse code which helps reduce redundancy and save coding time.
  • OOPs can easily handle and manipulate complex datasets.
  • OOPs support a lot of flexibility through polymorphism.

3. What are some examples of OOP languages?

The most popular OOP languages are:

4. What are the four main concepts of OOPs?

The four main concepts or principles of OOPs are:

  1. Encapsulation
  2. Polymorphism
  3. Inheritance
  4. Abstraction

5. What is encapsulation?

Encapsulation refers to the consolidation or bundling of all data and methods into a single unit. At the same time, encapsulation hides or restricts any unnecessary data and methods to minimize complexity.

For example, if you define an object that contains a list of integers, your object will always include the method used to calculate the average of those integers, even if you can’t access the source code directly.

6. What is polymorphism?

Polymorphism is the concept of having a single function or method do different things depending on the object class. For example, using the “+” operator will perform a summation if the inputs are numbers. But the same “+” operator will perform concatenation if the inputs are strings. In other words, the “+” is an operator that takes on several forms — it’s polymorphic.

7. What is inheritance?

Inheritance is the concept of a class or object gaining certain properties and methods from a parent class.

For example, suppose we created an “Animals” class with properties like age and weight. If we create a child class called “Mammals,” we might add mammal-specific traits like hair color. But, as a child class of “Animals,” the “Mammals” class would automatically inherit properties of age and weight. That’s how inheritance works in OOPs.

8. What is abstraction?

Abstraction is the concept of hiding unnecessary details about an object, method, or function from someone using your program. For example, when you use a coffeemaker to brew a cup of coffee in the morning, all you need to do is add water and coffee beans. You don’t need to understand the mechanics of your coffeemakers or how the sensors are calibrated.

So, while your code may include a complex function or method, following abstraction means that anyone using your program only needs to provide the necessary inputs for the function or method to work. And the only outputs are those that are useful to the person using your program.

9. What’s the difference between a class and an object?

Both classes and objects are essential components of OOPs. A class is essentially a template, or blueprint, for an object. An object is a member of, or an instance of, a particular class.

In other words, all objects belong to a class that defines the object’s properties and how that object can interact with other objects. And, while you need to declare a class only once, you can create as many objects as you need to — even objects that are part of the same class.

10. What are subclasses and superclasses?

A subclass is a class that inherits from another class. For example, you can create a class called “Animals” that includes properties such as age, weight, and natural habitat. These properties can apply to any animal.

When you create a subclass called “Birds,” the subclass, or child class, inherits everything from the parent “Animals” class — age, weight, and natural habitat — but can also include bird-specific attributes like egg size and wingspan.

A superclass is a class that acts as a parent to one or more child classes or subclasses.

11. What is method overloading?

Method overloading is creating different methods that are defined under different classes but share the same name. For example, if you have two classes, “Dogs” and “Cats,” then you may assign both classes a method with the same name, “Speak.”

For “Dogs,” the “Speak” method outputs “Woof,” while for “Cats,” the method outputs “Meow.” When you create a new object, “MyPet,” and call the “Speak” method, the output will be different, depending on whether “MyPet” falls within the “Dogs” or “Cats” class.

12. What is a constructor?

A constructor is a special method or subroutine of a class that initializes a new object of that class. When the object is first declared or created, the constructor sets values to properties of the object, which can be default values or user-defined. Constructors will have the same names as the class itself, but they’re not considered to be true methods because they don’t have a return type.

13. What is an exception?

An exception is a problem that interrupts program execution. For example, an exception may occur when a user inputs a string into a function that only accepts integers. Proper exception handling can resolve many exceptions — for example, checking that input data is the correct type and displaying a notification that the function only accepts integers.

Be prepared for your next OOPs interview

We know you have what it takes to succeed as an OOPs developer. Once you’ve mastered these OOPs interview questions, make sure to check out our guide to technical interviews as well as our technical portfolio guide to make sure you’re ready for anything. A little interview prep goes a long way toward impressing the hiring manager!

Then, once you’re ready to start practicing with real technical interview questions, test your coding skills with one of our Code Challenges. Not only will they give you a sense of what to expect when you walk into your first technical interview, but they’ll also help you identify the concepts you’ll need to refresh your knowledge of if you find yourself stuck.

For more tips on launching your career in development, visit our Career Center.


Interview Prep Courses & Tutorials | Codecademy

Interviewing is an important step in your journey towards landing a job in tech. Technical interviews let you showcase your skills and knowledge, but practice is key. You’ll need to understand technical concepts and be prepared to talk through solutions with your interviewers.

What It’s Like to Be a Teenager Now: The Winners of Our Coming of Age in 2021 Contest

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What It’s Like to Be a Teenager Now: The Winners of Our Coming of Age in 2021 Contest

Alyse Wicentowski, “Heart”
Angel Zhao and Fiona Xing, “teenage homage”
Bobby Goldyn, 14, “Lost Voices”
Cassie Garrett, 14, “Kindness in the Pandemic”
Dorothy Du, 16, “The Sound of Rain”
Eliana Robin, 15, “Warning: The World is Crumbling”
Eveleen Jiang, 17, “Out of Touch”
Hailey Jones, 15, “Growing Up in 2021”
Hiewon Ahn, “A Cutlery Awakening”
Ilona Lebron, 18, “Painting Something New”
James Kim, 17, “Life was rough.”
Jingyi Yang, 17, “Daydream in Heatwave”
Kalina May, 15, “Shame of Experimenting (in highschool)”
Kasie Leung, 15, “neurons and wings and other fleeting things”
Kevin Park, 16, “The March of Nature”
Kia Brazhnikova, 15, “Impassive”
Leona Su, 15, “Chinatown”
Phoebe Han, 16, “Burdened Puppet”
Selina Zhan, 13; Mia Kang, 14, “Diving into the Device”
Sena Chang, “Triptych: INFODEMIC”
Stella Turowsky-Ganci, 15, “what’s inside my head”
Surya Newa, 17, “To Each Their Own”
Xinyi Zhang, 16, “Me in the Mirror”
Ziqi, “Nest”
Zoey Lestyk, 14, “Just Do It”

Find the full list of students whose submissions received an honorable mention here.


The team that helped choose these finalists included educators, Learning Network staff and Times journalists, as well as teenagers who have won previous Learning Network contests. In alphabetical order they were:

Adee Braun, Amanda Brown, William Chesney, Nicole Daniels, Shannon Doyne, Jeremy Engle, Nora Fellas, Ross Flatt, Annissa Hambouz, Henry Hsiao, Michael Gonchar, Karen Hanley, Callie Holtermann, Susan Josephs, Isabel Hui, Isabel Hwang, Phoebe Lett, Simon Levien, Rachel Manley, Sue Mermelstein, John Otis, Natalie Proulx, Katherine Schulten, Ana Sosa, Ananya Udaygiri, Emma Weber, and Clare Zhang

Favorite Moments in Sports

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Favorite Moments in Sports

The Times has gathered “18 Sports Highlights From 2021 Worth Watching Again,” but before you take a look at our list, we’d love to hear yours.

Whether they come from sports you played yourself, or sports you watched, live or on TV, tell us about some of your most memorable sports moments of 2021, and why you think they’ve stayed with you.

Post your thoughts in the comments then read the related article to see the Times’s list.


Want more Picture Prompts? Find them all in this column.

Students 13 and older in the United States and Britain, and 16 and older elsewhere, 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.

Word of the Day: caveat

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Word of the Day: caveat

1. a warning against certain acts

2. an explanation that ensures something is clearly understood

3. a detail that cautions about or modifies the information given

4. (law) a formal notice filed with a court or officer to suspend a proceeding until filer is given a hearing

_________

The word caveat has appeared in 177 articles on NYTimes.com in the past year, including on Sept. 22 in “What Are the Best Houseplants to Get You Through Winter?” by Margaret Roach:

A friend who has long grown hoyas, or wax plants, has tried to convert me to this variable-looking genus with succulent leaves. But maybe Ryan Wilhelm, the operations manager at Steve’s Leaves, has finally succeeded. A representative of this tropical member of the dogbane family (Apocynaceae), the same family as milkweed, may be destined for a sunny window here.

One caveat, Mr. Wilhelm said: Be careful with the water — as their succulent leaves are trying to tell you — because “they can crash quickly, if overwatered.”

Can you correctly use the word caveat in a sentence?

Based on the definition and example provided, write a sentence using today’s Word of the Day and share it as a comment on this article. It is most important that your sentence makes sense and demonstrates that you understand the word’s definition, but we also encourage you to be creative and have fun.

Then, read some of the other sentences students have submitted and use the “Recommend” button to vote for two original sentences that stand out to you.

If you want a better idea of how caveat can be used in a sentence, read these usage examples on Vocabulary.com.

If you enjoy this daily challenge, try one of our monthly vocabulary challenges.

Students ages 13 and older in the United States and the United Kingdom, and 16 and older elsewhere, can comment. All comments are moderated by the Learning Network staff.