I introduced my students to Modern Love by reading “I Wanted To Love Her, Not Save Her” aloud, and explaining the structure of the narrative essay. Then I encouraged them to read at least two more essays of their choice.
Next, I assigned them to assume the voice of one of the characters from “Interpreter of Maladies” and write their own Modern Love column as if they were that character. I stressed that their essays should be simple, clear, include dialogue and tell the story. The essay did not have to have a traditional happy ending, but I asked my students to make a clear point about love. I assigned them a minimum of 1,000 words — not quite as long as the Modern Love column, but long enough that they would really have to get into it. I allowed students to pull entire settings and dialogue straight from the story, but emphasized that the entire column should read more conversationally than the book.
With this assignment, I wanted students to try to feel what it was like to be another person, and to break down the biases that the stories were bringing up in them. I also knew they would learn more about the characters and understand them better by speaking in their voices. It was almost a back door to real literary analysis, as opposed to the analytical paragraph and essay writing they do all year long. And I just knew they would have fun.
Here is what one student came up with when he wrote from the perspective of Dev, a married man who has an affair in the story “Sexy”:
When I met her at the counter of a makeup store, I could tell right away she would have an impact on life. Even though I was a married man, something about her caught my attention. I thought to myself I’m not wearing a wedding ring for a reason. I remember the first words she said to me in a soft voice, as she said, “I don’t usually like men with a mustache.”
I quickly responded in a flirtatious manner, “Is there something different about me?”
“Yes, you’re handsome, very handsome,” she told me.
This was the initial spark in a relationship that would give me butterflies. We started off by spending almost every night together. It helped that my wife was out of the country, making it much easier to spend time with her. The passion I so quickly gained toward this woman had never happened to me before. The feeling of being in love like this was new to me. She knew what to say and when to say it. One night I remember so vividly as she talked about how “it felt lonely to always be alone.”
She then quickly followed that up saying, “Until I met you.”
The feeling I got inside my stomach when she said this was indescribable, as I then responded to her by saying, “I’m so happy we met.”
This student found a way to humanize Dev, who in Lahiri’s story comes across as selfish, and who doesn’t seem to care very much about his wife or his mistress. But here, Dev is a loving, engaged partner rather than someone simply looking to use a woman for a sexual relationship.
Another student wrote about “A Temporary Matter,” a story about a stillbirth that has the effect of separating a husband and wife. The student takes the perspective of Shukumar, the husband, who cannot find his way through his grief and back to his marriage.
It was the worst day of my life. We got in the car after leaving the cold left wing of the hospital, and in some ways I was dreading going home. It was a way for me to escape, to walk around a little and get away, and while I hadn’t told Shoba this, I had held the baby after he had died. When I was in the hospital, it was easy for me not to tell her and, besides, I knew it would hurt her if I did. I just thought it was best that I kept this to myself.
As we were entering the car, we both paused and looked at the baby seat in the back. I watched as a tear fell down Shoba’s face. She tried to keep it discreet, but it was too late. I had already seen it. I didn’t really know what to do so I just gave her a kiss on her forehead and said, “Everything is going to be OK.” I felt numb and guilty for some reason. I didn’t actually know if everything was going to be OK, but it felt like the right thing to say at the moment.
The whole car ride was silent. We normally listened to the radio, fought over directions, and laughed, or we would sing along to our favorite song, “Butterfly” by Jack Smith. But we didn’t say a word. It felt like the longest 15 minutes of my life, like every minute was an hour or day or even a week. It was just so awkward for some reason. I had known Shoba for years. We were married, for God’s sake, but it was like all our history disappeared as soon as we walked out the doors of the hospital, and we were strangers again.
In Lahiri’s story, Shukumar stops caring about even taking care of himself. He’s relieved when his wife doesn’t check on him or talk to him, and he turns the baby’s room into his office, a jarring detail for most readers. But by placing him at the scene of the trauma, and telling the story from his point of view, the student makes Shukumar a more empathetic character.
In preparation for this post, which is likely to stir emotions on both sides (supporters of assigned learning vs those who are not), I went about and did an exploration of various sites on the web. I stayed clear of academic journals and academic articles, because academics are not the ones taking the online learning courses/content at the corporate level. They are not a new employee. Nor are they the blue-collar worker on the manufacturing floor who is lucky if they are provided time during their day to go online and take some courses/content.
The academics are not mid-managers, managers, let alone C-level suite executives. They do not run an association’s training/education, nor non-profit learning/training, nor customer education in various industries.
There isn’t anything wrong with academia, I speak from experience, but when relying solely on academic data even with online learning (they usually focus on the higher education/ed type of learning – synchronous based), is a detriment. For those who cover online learning, asynchronous based, it is always with the “completion” angle in play.
This was clear in the web searches with the term “assigned learning success rate”.
Every site that I went to, matched assigned learning and thus success with completion. As completion equates to success.
On one hand, there are a lot of L&D, Training and other folks (HR, Sales, EdTech) who truly believe that the best way to show the proof of success for their employees, customers, members and even students are completion rates.
A completion rate though doesn’t tell you whether the learner really is interested, let alone will retain, or the goal of online learning – synthesize the knowledge and build upon that.
Completion rates are something that is learned at an early age. When were you first assigned learning? The first homework assignment? The first read this entire chapter and let’s talk about it the next day?
The process simply repeats itself each and ever year in school. Going to college or a university? Assignments are everywhere (Not every faculty member does this, but the masses do). The term though be be listed as “homework”, as if the one word will change the perception of what is merely assigned. Going to grad school? Flexibility starts to appear, but assigned does show up depending on the professor/instructor/etc.
What is left is an embed on the type of learning, that I’d argue most people were never fans of to begin with. Yet that embedded form of learning is not discarded in online learning for adult learners; oh no; it is embraced with all the extra trimmings.
Synchronous based learning (SBL) is highly used in EdTech Online. You can easily recognize it the moment you see a syllabus or similar. You go step by step. You complete assignments with specific due dates. You complete the entire online course. In turn, the university or college or school can show those completion rates – the high rate – and say, “See – success!”
Brown University has a web page dedicated to “effective online assignments and activities.” One section says the following, “The first assignment is a good indicator of whether a student will complete the course.” ().
Note the words, “complete the course”. Brown isn’t alone in this thinking, but it reinforces the idea around assigned learning.
Coursera offers a report called “Drivers of Quality in Online Learning”. In the executive summary alone the following is presented to the reader
Under Instructors – Keep lectures under 10 minutes to improve completion rates by 16% and increase learner satisfaction. Courses that are “roughly” a month long have the highest completion rates.
Actionable Takeaways for learners mentions completion multiple times.
Under the section, “How to Increase Engagement” – “we use completion rates among the population of learners who are eligible to complete and are the most likely to have a goal of course completion”
The rest of the report taps into the completion aspect, even bringing up MOOCs whose own completion rates are beyond poor, and have been since they arrived on the scene. Who typically takes MOOCs? Adult learners – non-traditional learners (usually refers to adults over 25).
Who tends to buy Coursera? Adult learners – whether they are getting reimbursed by their company, or doing it themselves, or the company is buying it for their learners.
Corporate Assigned Learning
Corporate learning/training with learning systems continue to push the heavy usage of assigned learning. They mention it in their marketing of their system – “assigned learning”. They note in when folks ask about it, “yes, you can do assigned learning”.
The Argument for Assigned Learning on the corporate side
Mandatory. That’s the term we use for assigned learning. It sounds extreme. Do you know who else over abundantly uses the term “mandatory”? Prison.
Mandatory learning – and for our purposes – online, is cited as essential for
Compliance of any kind. Let’s not kid ourselves, compliance required training is because companies due not want to be sued. This isn’t about being proactive from the learner standpoint, it is from the corporate, state/province, government, regulatory commission. When do people tend to take compliance courses? Usually at or near the deadline to complete it. Check your data – and let me know how many times Mike went back into that “How to drive a forklift” course? OR how many times did your VP of HR go back into any of the compliance courses they had to take and complete?
Compliance creates a conundrum to those folks who believe assigned learning is not an effective way nor means to retention and synthesis of learning, and acquiring knowledge. It is required, do not pass go – which for now, has to be followed – no exceptions. Could compliance content be turned into something more engaging via interactive labs, with short modules, with benefits to return to the courses/content to continue improvement? Could it be achieved without making it mandatory by the end of quarter or month? Or is it something that has to be done, just as you have to wait at the DMV for hours just for them to tell you, you do not have the appropriate form?
What else is mandatory?
Onboarding – Not always all the content, but a chunk of it – sure this is dependent on who is overseeing this, but we are talking general here. A friend of mine who started a new job was given access to the learning system and assigned a set of courses. The courses included such items as company’s procedures, values, navigating the office (they work remote), welcome to the company with the CEO thanking them (pre-recorded) and a video of various employees talking about how much they enjoy working at the company. What value! Any mention of where to find your parking spot?
Tasks – The worst. This implies that you have to complete this task – perhaps daily, and in turn it will increase your knowledge and retention because it is often. They are right in one way – your retention – from the standpoint of how much you will dread taking it. Daily assigned tasks are ideal if you want to reside in a flat/home with a significant other who expects (understandably) for you to take out the garbage, mow the lawn, wash the car, water the plants, get the mail, listen to your Dad tell you that they mowed lots of lawns for free, so getting a quarter should be a happy blessing. Seriously though, task assignments, are assignments – like homework but for adults.
Job role related – This one makes zero sense. It is as though we are all back at school learning a specific subject and that to proof that we know said subject, you are given due dates/completion requirements. Many a times, it comes from the manager of said individual. If you are telling an employee that you believe in their learning/training of X skills, and “open exploration”, it kind of goes out the window, the moment you tell them, they have to take this and complete it. Couldn’t you achieve the same objective by putting together a catalog of courses/content for that individual or group, let them select from it, (which will tell you far more about them and learning goals for skills and insight) and then monitor from there. If I see that Melissa selected three courses around leadership, then my guess is going to be she is a)interested in this subject b) planning to tap into it or has a reason for seeking that information, c)if she is a manager, then this is an area she wants to improve or build upon, d)if not, she may be looking to develop these skills for future opportunities to be a manager.
Completion Equates to Success
Malarkey. Utter rubbish.
We in the corporate world (and education too) look at those completion rates as though they are the validation we need to show someone, anyone that online learning works and is successful. Successful for the department. Successful the institution, entity, business, association, and so on. Learner completes – therefore they know the information/skill/whatever and this equates to success. High completion rates – we are successful with our online learning.
It means NOTHING. NOTHING. You are not in fifth grade here. You are working at a company. You are not in Ms. Willard’s class staying after school to complete the book report, you failed to turn in during class.
There are learning systems whose entire machine learning algorithm (noted as A.I. by the vendor) is based heavily on completion of the content. Fail to complete? No worries, it is not computed with the algorithm – skipped. Fail to complete? No worries, you are given less weight than if you complete it. Fail to complete? No worries. Just click the “complete” button.
I like Degreed, but from day one (and yes, I saw the system when it first came out, so many moons ago) their system was setup with completion as a key indicator. I remember getting into a discussion with then CEO and Founder, David Blake on whether or not he knew why WBT was created (it wasn’t about completion), because of their instance on completed with the system. Telling someone to click “complete” so that it shows it is completed, skews data.
Skews how you say?
The recommended playlist? Based on completion. So even if Mark spent 29 seconds in course X and clicks complete, the system says he completed it. Despite the fact that Mark never went any further, never went back, did nothing.
Assigned learning? Well, if the majority of company is assigned six courses of the same subject and topic, what do you think will appear skill/topic wise with recommended?
Suggested or most popular? If assigned is the backbone of your employees’ learning or customers, then most popular is skewed.
The data you are looking at with systems whose algorithms weight heavily around completed, or penalize (okay, ignore in some cases), non-completed, is IMO, data misrepresented.
This is why I always ask every vendor the question around weights, completion or non-completed, bringing up a core reason on why WBT was created in the first place. To empower the learner – to learn what they are interested in, when they want to, wherever they are. They are not forced nor required to complete the course/chapter/etc – because synthesis is the better data point here, not completion.
If your learning system presents as a key data indicator – completed vs non-completed and you are relying on this data as the CORE for proof of validation, you need to go back and re-think this thru.
If assigned learning is the ESSENTIAL to your learning for your employees, students, customers or members, then you need to go back and re-think whether this is how you felt when you were assigned learning during your days at school.
If you ever have had the pleasure of listening to employees gripe on having to attend a training session, and take away from their time to do their job, you will recognize first hand, how required really plays here. What is the completion rate for attending? 100%. What is the comprehension and synthesis for these happy err less than enthralled employees on this subject? Very low. They are still stewing about attending.
Bottom Line
If you have a learning system, take a look at whether or not completed is one of the data points you are seeing. My guess, is it will be.
Ask yourself, what completed really means to you? What does it really tell you about the learner? Their retention and synthesis of the content?
Is your learning or training success level solely tied to completion?
Our 10th annual Coursera Conference recently offered a unique opportunity for Coursera’s leadership team, representatives from our partner organizations, and more than 3,000 participants from all over the world to come together through a shared commitment to transforming lives through learning.
The event featured over 40 sessions that explored new opportunities for the future of learning and working in a digital world. Recordings for most of them can be watched on-demand under the session description on the agenda page of the event website.
We’ve already summarized the highlights. Now, in this article, we’d like to draw your attention to five sessions that stood out to us.
1. Invest in the Best: Creating a Culture of Learning to Drive Competitive Advantage
A culture of learning can be the difference between accelerating business outcomes and digital transformation or stagnation. However, this culture can often be challenging to build.
In this session, Jennie Drimmer, Senior Regional Sales Director at Coursera, and Bartosz Zieleźnik, Head of Online Learning at Prosus, discussed how they’ve adapted to the changing role of learning and development, their experiences with building a culture of learning, and how they’re investing in their workforce to maintain a competitive edge.
Here are a few of the main takeaways:
Why does establishing a culture of learning matter?
It’s an employee value proposition that you can use to attract people into your company. You also need to be able to create enough talent mobility within your workforce by supporting them with the correct learning interventions.
What’s important to realize is that a learning culture is not something you need in the distant future. It has to happen now because we’re at the core of the war for talent and internal mobility and the reskilling game that we want to launch within each company.
How do you build a culture of learning?
You need to sit down with the executive team and present a business case of why learning matters. If you build an AI department, for example, it doesn’t need to be massive to have a significant impact. Having these conversations to get the executive team on board is the easy bit. The hard part is leading by example. The way your executive team learns and uses your learning and development products will define how your learning culture lands within your population.
Inspire the executive team with real stories. Every time you want to make a presentation about learning, come prepared with a first-hand account of someone who completed a course. It enhances your business case. Around 50% of your time should be spent educating the leadership team. Still, middle managers are critical to the success of establishing a learning culture that filters through to the whole organization.
Why is mid-level management so important?
It would be best if you legitimized learning within a person’s workday. You can achieve that by educating managers and telling them you’re very serious about learning, and asking them what space they want to create for their teams to thrive.
We tend to look at the number of enrollments versus the number of completions, but sometimes the focus on quantity can be detrimental. So we started experimenting by asking our graduates about any tips and tricks they have for someone taking the same course. People come back with all sorts of insights: for example, blocking out the time to study regularly and aligning with their manager was key to their success. By getting managers on their side, you create a bunch of enablers who make this learning culture possible.
2. Talent Champions: How IKEA and Genentech are Proving the Value of Workplace Learning
In this session, we explored how to make a case for learning within your organization.
Jill Kenney, Director of Skills Transformation at Coursera, was joined by Cyril de Avellar, Learning & Development Leader at IKEA, and Roya Mirilavassani, Senior Trainer, CMG Leadership Development at Genentech, who shared how they’ve successfully made the business case for Coursera, and how their learning programs have provided organizational value.
Can you tell us about the learning programs you rolled out at your organizations?
Cyril de Avellar:We launched a learning hub and looked at ways to improve the use of this platform by approaching it from the perspective of a typical retailer: How do you increase retention and the average time users spend on the platform? We explored different ways of promoting the content and quickly realized that we had the best traction when we engaged learners to recommend their preferred content to other learners.
We introduced several activities, like a subscription that you can sign up for to receive a regular email recommending content on five specific areas aimed at different levels of expertise: data, engineering and technology, experience design, product management, and security. We also appoint platform ambassadors. Our most active learners host webinars and onboarding sessions with new co-workers and post ideas and suggestions about the learning program on Slack. And we run learning hackathons to support a specific team in learning new skills together. All these activities are the key to keeping up the active engagement of our learners.
Roya Mirilavassani:Coursera was the first big push for us to challenge the concept that learning can’t happen outside of the classroom. It’s been really well received, and we’ve expanded our program to complement what we do in-house to provide our employees with a wider breadth of opportunities. We’ve started to map them to our classes for anyone wanting to dig deeper into a specific area.
To increase engagement and enrollment in our platform, we introduced Learning Olympics that are held every year. The corresponding page features resources like the Coursera courses staff can enroll in for different topics. There’s a leaderboard, as we want to see who is accessing the most workshops and taking the most classes.
We also do frequent marketing and use different channels to reach people. We send custom emails to registered users as well as newsletters. Within those communications, we highlight what’s coming out and the top courses that other folks are taking so that readers can see what they might want to register for.
Most engagement comes from word of mouth. Many folks will take a course and rave about it to their colleagues. Since we launched Coursera’s Leadership Academy (which covers 42 different SkillSets and 35 human skills), we’ve also had a lot of managers approach us, wanting to see how they can integrate it into their development plans.
3. The Voice of the Student: Perspectives on Skills, Employability, and Lifelong Learning
In this unique panel, student representatives from around the globe shared how they are preparing for new workforce realities and what support they expect from their institutions along their career journey.
Today’s students are graduating into a new labor market where opportunities are emerging with increasing digital and human skills requirements. So it’s essential to understand how confident students are feeling – particularly given that recent data shows securing employment is an increasingly significant factor in how students decide where and what they’ll study.
Samar Farah, Senior Skills Transformation Consultant EMEA at Coursera for Campus, was joined by Natalia Fernández Rosel (a third-year communications student at the Universidad Anáhuac Mayab in Mexico), Anna Kovács (a second-year business and management student at the faculty of Economics at the University of Szeged in Hungary), and Satyam Dubey (a third-year computer science student at the CSMSS Chh. Shahu College of Engineering in India).
What role does gaining job-relevant skills play in your academic programs?
Natalia Fernández Rosel: Nowadays, students are not satisfied with only finishing their degrees. We want to do more and develop and learn new skills to apply for more and better job opportunities. So gaining additional practical experiences outside of the core curriculum, for example, through internships, has been really important. When we apply for jobs, we can show that we’ve already used specific skills in a professional environment.
Anna Kovács: My university organizes career fairs twice a year, giving us a great opportunity to connect and support our needs. The faculty also allows students to go on internships to allow us to gain real-world experience. And the university is also in partnership with Coursera, which enables students to broaden their horizons and accomplish courses for free. The advantage of online learning is that we can create our own schedules. Hybrid learning is the best way to go because it gives us the flexibility to work from anywhere.
What should universities be doing better to support their students’ academic experiences and their preparation for the labor market?
Satyam Dubey: The best thing students can do is become familiar with the environment they’re going to enter after graduation. It’d be amazing if universities could provide internships before graduation, not just in the final year but also in the second and third year, for at least a month. That would help students understand the particular skill sets they are going to need and how prepared they are already. Universities should also focus more on practical rather than theoretical subjects because practical skills help us gain the required knowledge so much faster.
Natalie Fernández Rosel: University teachers need to listen to us. A lot of students have great creative ideas about workshops, masterclasses, and practical experiences that they want to gain. For example, I’d like to see universities create experiences involving people working in the fields we are studying. As students, we want to be connected to them so that we can ask questions.
4. Mind the Gap: Bridging the Skills Gap to Prepare Students for Industry 4.0
In this session, we heard from academic leaders about what universities can do to prepare their students with the skills needed for success in today’s job environment and bridge the skills gap with prospective employers.
Scott Shireman, Global Head of Coursera for Campus, was joined by Dr. Amber Wigmore Alvarez, Chief Talent Officer at Hired, and Dr. Mark Rosenbaum, Dean of the College of Business at Hawaii Pacific University.
What kind of skill gaps do you see in students?
Dr. Amber Wigmore Alvarez: At Hired, we analyze macro trends in the hiring and recruiting space. Let’s take a look at three now. For example, we see that students feel unprepared for jobs. A recent survey we conducted identified that one in three business school students think they lack the digital skills for employment in Industry 4.0. And almost nine out of every 10 students believe that skills such as data analytics and search engine marketing are now considered entry-level requirements. Also, 71% of talent believe that senior leaders poorly understand digital skills in Industry 4.0.
The second trend is that skills needed in many roles have a shorter lifespan. We found a growing demand from employers and individuals for upskilling and reskilling to remain employable, and they want to do this on their own terms.
The third trend is that students expect job-relevant skills in the core curriculum. When we asked students how they believe that their business schools could improve when it comes to helping them get a job, 65% said the integration of employment skills within the degree programs.
Scott Shireman: We’ve just rolled out Career Academy to help universities prepare their students for in-demand digital jobs. Students using Career Academy will learn cutting-edge skills with no experience required. They’ll earn professional certificates from some of the world’s leading companies like Google, IBM, and Meta. They’ll have access to guided projects to help them master skills and the tools that will help them stand out from employers today. And it will allow them to explore the right career path and learn flexibly across web and mobile.
As the first school to use Career Academy, what’s your experience been so far?
Dr. Mark Rosenbaum: Career Academy brings business education back to its historical, skill-focused origins. Our faculty can use Career Academy materials as a textbook, assignment, or optional reading. What is critical is that educators link our classes to career opportunities. The value proposition is enhanced as students are here to obtain meaningful skills. Career Academy especially helps us to stay current in fast-changing areas like cybersecurity, data analytics, and social media marketing because Career Academy’s partners are creating the content.
In the future, I see Career Academy available to all of our students at any time, almost like a downloadable internship opportunity to engage in different career explorations.
5. Developing the Workforce at Scale: An Ecosystem Approach
What does it take to prepare millions of people for the economy of tomorrow? This is the fundamental challenge that this session’s panelists face every day.
Kevin Mills, Vice President at Coursera for Government, was joined by Kenyatta Lovett, Managing Director for Higher Education at Educate Texas; Chris White, Deputy Commissioner for the New York State Department of Labor; and Hyejin Lee, Director at the South Korean Ministry of Education, to explore how to position talent and employers for success.
What are the key challenges and opportunities you’re facing in your region?
Chris White: Through our career center, we usually serve 500,000 people each year, but at the peak of the pandemic, it went up to more than 5 million. There are a lot of people in need, but it’s also a huge opportunity. People are now more interested in assistance and how to get to the next step in their careers. They are also paying more attention to workforce development. And there’s tremendous value in telling them about the deficits businesses say job seekers have and pointing them to specific Coursera courses that can help them learn those skill sets.
Kenyatta Lovett: The workforce shortage will be with us for a while, and it’s concerning that we don’t see participation in traditional education channels the way we used to. People now have to make distinct choices between entering the workforce or going into education. The rate of high school graduates in Texas that move on to college dropped down to 45%; in some regions, it’s as low as 35%.
However, we’re now seeing a renewed understanding and appreciation for work-based learning experiences to make sure that employers can feed their talent pipeline as they need to. At the same time, we’re seeing growth around short-term and micro-credentials, which enable people—especially from disenfranchised backgrounds—to learn a new skill within just a few months to increase their career options.
Hyejin Lee: In South Korea, the birth rates have been dropping rapidly, so it is very important to focus on the current workforce and equip them with the best possible education and training. We provide lifelong learning for everyone and, in 2015, launched an initiative with the help of partners like Coursera, to transition offline lectures online. We started with 27 classes and now have more than 1,300. In 2020, the need for online classes imploded because of the pandemic, and the number of students enrolled soared to about 960,000.
We cover a variety of topics, especially new digital technologies like blockchain and machine learning, and focus on providing practical classes which are not offered by universities and also help students get hands-on experience offline.We are trying to become a matchmaker because there is a need for specific skills and people want to learn them, so we are connecting them.
Even though we’re just scratching the surface of possibilities when it comes to machine learning, it’s already shaping our everyday lives and the decisions we make. Major companies like Google, Amazon, Netflix, and Tesla use machine learning to deliver personalized results to millions of users, understand and interpret human conversation, train neural networks to predict what a human driver would do, and so much more.
And there’s no sign of slowing down. The global market is expected to reach $117.19 billion by 2027 — that’s a yearly growth rate of nearly 40%.
The significant growth within machine learning, as well as the opportunities to develop new and exciting technology, has attracted many professionals to the industry. While there are the obvious titles — like Machine Learning Engineer — there are also other positions you can explore that use machine learning but might not be as obvious.
Here are seven popular jobs that use machine learning, along with information on how to get started in each role.
1. Machine Learning Engineer
Machine Learning Engineer is one of the most popular positions in the machine learning industry, and you’re likely to find many roles with this exact title during your job search. These engineers design and implement machine learning models, expand and optimize data pipelines and data delivery, and assemble large, complex data sets. Models developed by Machine Learning Engineers are used to reveal trends and predictions that can help companies meet business objectives and goals.
Robotics Engineers have a huge advantage if they also have a machine learning background. Robots are often driven by either the need to emulate human behavior or to maximize the efficiency with which something can be done. So as a Robotics Engineer, you might help develop a robot’s computer vision, which would enable it to interpret and understand the visual world around it, and then make accurate — and safe — decisions. Or maybe you’d develop a machine-learning algorithm to process massive amounts of data produced by robots that assemble vehicle parts.
Designing the machines that make people’s lives easier can earn you about $99,040 a year, on average. If you’re thinking about a career in robotics, you’ll likely need to know C++ and Python, and you can get started with these in our Learn C++ and Learn Python courses.
3. Natural Language Processing (NLP) Scientist
A Natural Language Processing Scientist uses algorithms to pinpoint natural language rules, and then use them to enable computers to speak and understand the language. Machine learning makes this easier because you can design an algorithm that discovers and tests patterns for you — so you don’t have to do it manually or with elaborate spreadsheets. In a way, a Natural Language Processing Scientist builds bridges between languages and machines, making it possible for machines to understand people and vice-versa.
As an NLP Scientist, you may specialize in a subfield of NLP, such as computational linguistics, human language technologies, automatic speech recognition, or machine translation. And you’ll likely also collect, explore, and improve the quality of data used to adapt and extend machine learning-based technologies that support these areas.
Software Developers design and build applications for mobile and desktop use, as well as the underlying operating systems. Machine learning can help Software Developers analyze data to predict how users will react to certain features of an application, design models that output data according to what users want to see, and create programs that enable chatbots to interact with end-users in more natural ways.
If you’re interested in a software development position that specifically involves machine learning, you could learn TensorFlow, an open-source platform for machine learning, or Pandas, a tool in machine learning that’s used for data cleaning and analysis. Focusing on learning the tools and programming languages that are typically used in machine learning will help you qualify for these types of software development jobs.
On average, Software Developers earn around $107,510 a year.
5. Data Scientist
A Data Scientist analyzes, processes, models, and interprets data to help create actionable plans and guide business decisions for companies and organizations. As a Data Scientist, you have the potential to be one of the most useful team members in your company, largely because your ideas and suggestions are backed by hard data.
Data Scientists working in the machine learning industry help write algorithms that can discover patterns, which are then used to provide insights and recommendations. The critical role of Data Scientists is reflected in their salaries, too. You can earn an average salary of over $119,000 a year as a Data Scientist.
Cybersecurity Analysts are in charge of figuring out the best ways to defend a company’s digital infrastructure and assets. This involves using many different technologies and can be far easier with machine learning. This is because a Cybersecurity Analyst has to collect and study large amounts of data that reflect the vulnerabilities and threats a company may face.
If you have a background in machine learning and you’re interested in working in cybersecurity, you may have the opportunity to tweak, upgrade, or create new algorithms used to protect an organization. The crucial role of Cybersecurity Analysts frequently earns them salaries in the six-figure range. The average annual pay is about $103,590.
Artificial Intelligence (AI) Engineer is another position in which machine learning can be used. Since machine learning is a subset of AI, there are many AI Engineers with expertise in machine learning tools and applications.
You might develop and modify machine learning models, apply machine learning techniques for image recognition, and develop neural network applications using popular frameworks like TensorFlow and PyTorch as an AI Engineer with a machine learning specialty.
If a career in AI is in your future, skills like Python, R, and Java are common for this role, as well as linear algebra and statistics. U.S.-based A.I. Engineers earn an average salary of over $164,000 a year.
Once you’ve picked the type of machine learning job you want, it’s important to build your resume and cover letter to emphasize the skills and experience most valuable for that position. And to prepare for the types of interview questions specific to that role. You can use this guide to help you write your technical resume, and this advice on landing a machine learning job is a great resource. Here are common machine learning interview questions that you can practice before your interviews. And be sure to check out our Career Center for more resume and interviewing tips.
Some highly processed plant-based milks can also have a negative impact on the environment. Most ingredients used in plant milks are associated with a lower carbon footprint than those in dairy milk.
But many, especially nuts and coconuts, pose their own environmental problems. Almonds are typically grown in areas suffering from water scarcity, and increased demand for them is depleting the water supply in those communities. Rising demand for coconut is leading to increased cultivation and the potential for deforestation and the loss of biodiversity.
Daily Word Challenge
Can you correctly use the word scarcity 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 scarcity can be used in a sentence, read these usage examples on Vocabulary.com.
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.
This lesson is a part of our Accessible Activities feature, which aims to welcome a wider variety of learners to our site and to The Times in general. Learn more and tell us what you think here.
Here are two expressions that also appear in the article: “go for it” and “slowly but steadily.” Do you know what either of these mean? Can you use them in a sentence?
Questions for Writing and Discussion
Read the article below, or as a PDF, and then answer the following questions:
1. What negative associations do people have about tattoos in Japan? How do these affect people who have tattoos?
2. How are some of the negative associations changing?
3. What role has social media played in these changing norms?
4. What is your reaction to the perspective on tattoos by Rion Sanada, the high schooler quoted at the end of the article?
Going Further
What is your reaction to the article? Did it change any of your beliefs about tattoos? What was surprising or interesting about it?
Now check out a fuller version of this article, titled “Discreetly, the Young in Japan Chip Away at a Taboo on Tattoos.” What story do the photographs in it tell? Based on what you just read, what three photographs do you believe are the most essential to telling this story? Why?
Finally, tell a story of your own through images. First, find three photos on your camera roll that are related in some way. Maybe they all feature your dog, a sport you play, a place you like to hang out, or a friend or family member. Put them in an order that, like the photos in the interactive you clicked through, explain something or tell a little story. Finally, write short captions for each that tell that story. Don’t forget to share your creation with others to see what they think!
Want more Lessons of the Day? You can find them all here.
1. After looking closely at the image above (or at the full-size image), think about these three questions:
2. Next, join the conversation by clicking on the comment button and posting in the box that opens on the right. (Students 13 and older are invited to comment, although teachers of younger students are welcome to post what their students have to say.)
3. After you have posted, try reading back to see what others have said, then respond to someone else by posting another comment. Use the “Reply” button or the @ symbol to address that student directly.
Each Monday, our collaborator, Visual Thinking Strategies, will facilitate a discussion from 9 a.m. to 2 p.m. Eastern time by paraphrasing comments and linking to responses to help students’ understanding go deeper. You might use their responses as models for your own.
4. On Thursday afternoons, we will reveal at the bottom of this post more information about the photo. How does reading the caption and learning its back story help you see the image differently?
The Reveal
We’ll post more information here on Thursday afternoon. Stay tuned!
Students 13 and older in the United States and the 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.
Great choice! Python is a powerful, versatile programming language used for everything from web development to data science and machine learning. It’s also easy to read, so it’s well-suited for new and experienced programmers alike. Plus, Python skills are in high demand, so adding it to your tech stack can open the door to many job opportunities.
But there’s a lot to learn. Online courses — particularly interactive ones like our Learn Python 3 course — will help you build many of the skills you’ll need throughout your career. But it’s not uncommon to supplement your education if you want to master the language.
“To truly understand a field, you need to get input from multiple places,” says Codecademy Data Science Domain Manager Michelle McSweeney. “Sometimes books can add theoretical depth, sometimes they introduce more practical applications, but they always serve to help you enter into a culture of coding in addition to the practice.”
Ahead, Michelle shares five Python coding books that’ll help take you from Python newbie to Python expert.
If you’re completely new to programming
If you’re starting from scratch, Michelle recommends Python Programming: An Introduction to Computer Scienceby John Zelle. “It’s such a good foundation,” she says. “It provides a classic introduction to programmatic thinking via Python.”
Python Programming explores the fundamentals of computer science, programming, design, and problem-solving in a way that’s easy to understand. You’ll also learn how to write simple Python programs, and it’ll help you develop your ability to think like a programmer.
If you want to learn about real-world use cases
Learn Python 3 the Hard Wayby Zed Shaw is helpful for those who want to dive deeper into Python programming. “It’s an excellent resource,” Michelle says. “It’s a learn-by-example book and really helpful for getting some immediate practice to supplement your learning on Codecademy.”
Learn Python 3the Hard Way shows you how to install Python on your computer and covers concepts like lists, loops, and data structures. It offers 52 practical exercises to help build your coding skills, and you’ll also learn more about Python’s applications in web development and game development.
If you want a comprehensive introduction to Python
If you want a better understanding of Python’s advanced features, check out Learning Pythonby Mark Lutz. “It’s a TOME,” Michelle says. “The thorough approach is right for some, but not for everyone.”
Learning Python teaches you how to use the latest versions of Python, and you’ll also navigate object types, code packages, exception-handling models, and development tools like decorators and metaclasses as you learn how to write organized and efficient code. It’s also a great introduction to object-oriented programming.
If you want to automate tasks
Automate the Boring Stuff with Pythonis a good choice if you’re just starting out, but it’s also a handy resource that can help you throughout your career. “It’s immediately useful and satisfying,” Michelle says. “It offers such quick recipes that you don’t have to do the thinking, it’ll just remind you how to do something.”
If you find yourself constantly dealing with repetitive tasks, Automate the Boring Stuff with Python could be right for you. You’ll learn how to create Python programs to automate file management, Excel spreadsheet updates, email reminders, text notifications, and downloading content from the internet.
Not only will you learn about the fundamental concepts of machine learning and different types of machine learning algorithms, but you’ll also learn how to use Python and tools like scikit-learn to build machine learning applications. If you’re making your way through our Data Scientist career path, this book is the perfect supplement.
Learn more about Python
Each of the books above will teach you more about Python and help build your skills as a programmer, but nothing expedites learning like hands-on practice. Check out our Python courses to learn more about the language.
If you got offered a job in tech, first of all — congrats! Your hard work is paying off. As you prepare to negotiate your salary and read the fine print of your offer letter, you might come across a benefit in your compensation package that you’re not familiar with: employee stock options.
Lots of companies will give employees “stock options,” or the right to purchase a number of shares of the company’s stock at a set price over a specific period of time. While stock options aren’t exclusive to tech companies, it’s a pretty common benefit at startups.
Equity compensation and stock options are a way for employees to have direct ownership in the company or “some skin in the game,” explains Danny Roberts, Senior Technical Recruiter at Codecademy. And since stock options typically vest over a period of time, it’s also a way to incentivize folks to stay at a company long term.
First things first: Stock options aren’t as straightforward as earning a salary or getting handed “free money.” You can expect your employer to give you a stock options agreement with all the terms laid out, and maybe even host informational sessions that illustrate some common scenarios. But you might still have questions about what all of this could mean for you.
Every company is different, and every employee’s financial situation is different, so it’s impossible to give one-size-fits all guidance. However, here are five things that will help you better understand this part of your compensation package, and hopefully guide your follow-up questions for a recruiter or financial advisor who can speak to your specific scenario.
What even is stock?
If stonks aren’t really your thing, it’s easy to get confused by the concept of equity packages and stock options. To review, a stock is a unit representing a fraction of ownership of a company. Stocks are mainly bought and sold on the stock exchange (like the New York Stock Exchange or Nasdaq); and in some cases, they can also be sold privately.
Whether you work for a publicly-traded company or a private one affects your stock options. When a company “goes public,” it means that it undertakes its initial public offering, aka “IPO,” by selling shares of stock to the public. Anyone can look up the stock prices of public companies (take a look at Meta, Apple, and Amazon’s stock quotes for context).
The value of an individual stock at any given time can fluctuate depending upon the stock market. When employees are given stock options, they’re offered at a fixed price that doesn’t change even as a company grows and gets more valuable.
Private companies that don’t trade shares on the public market yet, but want to offer stock options to employees, have to go through a formal appraisal process called a 409A valuation to determine the “fair market value” of a startup company’s common stock. The valuation can depend on lots of factors, like the company’s assets or cash flow, and companies do this annually (or sooner, if there’s a major event like a merger or financing).
A lot is hypothetical
The value of a stock is contingent upon so many other variables that are out of your control as an individual. “The main thing that people want to understand when they’re given an equity package and an offer is: What is the value of this?” Danny says. The truth is, at private or pre-IPO companies, it’s tricky to answer that question because it’s all hypothetical.
For example, say you’re considering a job at an early-stage pre-IPO startup, and your compensation package includes a number of stock grants. Technically, the value of the stock is all based on the 409A valuation, and you can’t trade it on the stock market yet.
In a sense, purchasing or exercising stock options involves betting on the future of the company. There’s a chance that there could be “an amazing upside” to buying stock, Danny says. If the company goes public and the stock becomes very valuable, that could result in a profit and windfall for stock owners. “But never think about equity as guaranteed,” he adds.
They’re time sensitive
Time is an important factor when it comes to stock options. Typically, employees have to work at a company for a set period of time before they’re allowed to exercise their right to purchase stocks. Stocks usually vest over a 4-year period with a 25%-year cliff, meaning each year you’re at the company, you can exercise 25% of the number of stock options you were granted.
Another common scenario: Your company gives you “restricted stock units” or RSUs, which are yours as soon as you vest, but don’t technically have a tangible value until a future date. (If the company is public, then the RSUs you’re granted each month do have a tangible value.) In order to reap the benefits, you’d have to stay at the company until the vesting period ends.
And should you decide to leave the company, there’s usually a 90-day window that you have to exercise your stock options.
There are tax implications
Keep in mind that whatever you decide to do with your stock options will impact your taxes. Make sure you know what type of stock that your employer offers so you know how it’ll be taxed: “Non-qualified stock options” get taxed as part of your annual income, whereas “incentive stock options” can get taxed at a different (in some cases lower) rate when you sell the stock.
Consider your personal risk profile
There’s a lot to take in here, and these are just some starting points for many more questions. So it’s wise to consult a professional financial advisor if you’re not sure what to do. What you do with your stock options is very personal, and boils down to how much risk you’re willing to assume. Someone who’s highly risk-averse might prioritize a higher salary with fewer stock options because it’s guaranteed money in the bank.
So what you can see here is that when working memory demands are low (easy problems), people respond pretty fast and don’t make a lot of errors, regardless of anxiety. But when they need to use more of their working memory on the hard problems (High WM demand), anxiety starts to get in the way. That’s why you see such a big difference between the individuals with high math anxiety (HMA) and low math anxiety (LMA) in the control condition on the hard problems. In the expressive writing condition (called “EW” here, but it’s really not gross at all!), those with low math anxiety perform pretty much the same as in the control, but the individuals with high anxiety perform much better, and, statistically speaking, they look the same as those with low anxiety!
Why Does Expressive Writing Work?
Why does this work? Well, we don’t know exactly. There are a few possibilities (and all of these may actually play a role here).
1) Expressive writing may allow individuals to better organize and understand their emotions, leading to more effective coping mechanisms.
2) Expressive writing may free up working memory by allowing the individual to psychologically distance themselves from the source of stress.
3) Expressive writing may serve as a type of distributed cognition, allowing the individual to stop monitoring, knowing that they can pick that stress back up later (sort of like writing your grocery list on a piece of paper so you don’t have to keep it in mind… until you lose the paper).
A Word of Caution
It should be noted that this is only one study on a specific population (college students) in one domain (math). If these variables changed, it might affect how much expressive writing is needed in order to get these same effects. Still, given that this is a relatively easy intervention that takes little prep and little time, it might be worth trying to see if students who are struggling with various types of performance-related anxiety might benefit. If you do try this technique, let us know how it works for you or your students!
