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9 examples of machine learning in action

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9 examples of machine learning in action

The term “machine learning” makes it sound like computers will solve problems for us without much human guidance. We’re not quite there yet. But, some fascinating careers are paving the way for artificial intelligence to help us all out in our daily lives and at work.

Machine Learning Engineers and Data Scientists that specialize in machine learning get to work in pretty diverse industries. That’s one of the best things about a career in programming or data science — you can take those skills just about anywhere. It also means that you can work in a field that excites you or one in which you feel like you’re making a positive contribution.

This article will show you examples of machine learning in action. We’ll also help you understand what machine learning is used for and how you can learn the skills required to be a part of this exciting industry.

What is machine learning used for anyway?

Machine learning isn’t as hard to understand as you might think. In short, it involves using pattern recognition software to find trends in data, building models that explain the trends/patterns, and then using the models to predict something. The more a computer program “learns” about a data set, the better it predicts the outcome of a new set of data.

For example, if you fed a machine learning algorithm a bunch of images containing flowers or people, it would learn from the labeled data and be able to discern whether the next image it processed was a flower or a person. In effect, it gets better the more it’s used because each new piece of data is a “learning” opportunity for the machine.

In another post, Hillary Green-Lerman, one of our Data Scientists, takes a closer look at what machine learning is, explaining how:

“Machine Learning is about using the data you already have to make predictions. This sounds really fancy, but most of the time, the ‘prediction’ is really just a label.”

9 machine learning examples

Machine learning careers are on the rise, so this list of machine learning examples is by no means complete. Still, it’ll give you some insight into the field’s applications and what Machine Learning Engineers do.

1. Image recognition

As we explained earlier, we can use machine learning to teach computers how to identify an image’s contents. You know when you’re asked to find all the buses, crosswalks, or traffic lights in a series of nine pictures online? You’re not just verifying you “aren’t a robot,” you’re actually helping to train a machine learning algorithm on image recognition with your answers.

2. Speech recognition

Speech recognition is being improved by machine learning algorithms as well. The number of applications that use speech inputs is staggering. From your word processor to your smart speaker to the automated system on a local utility company’s call center, voice recognition is critical. It reduces friction for users and even increases accessibility to a wider population.

3. Virtual personal assistants

Whether you’re talking to Siri, Alexa, or Google, virtual assistants use machine learning to get better at giving you answers. These services use speech recognition technology, but they’re also using machine learning to capture data on what you’re asking for, when, and how often they get it “right.” Machine learning utilizes all of these data sets to improve the services provided and helps inform and guide the companies’ decision-making.

4. Customer service reps

When the little chat box pops up next time you’re shopping online, the “person” who answers might not be a person at all. Many companies have switched to using chatbots that deploy conversational AI to answer customers’ questions. These AI use machine learning to improve their understanding of customers’ responses and answers. Whether the input is voice or text, Machine Learning Engineers have plenty of work to improve bot conversations for companies worldwide.

5. Social media algorithms

This one probably comes as no surprise. People talk about “the algorithm” all the time.

Think about all the data captured on your social media account — what you like, the posts you engage with, the times of day you’re most active, what ads you’ll click on, and more. Machine-learning algorithms use all that information to customize your social media feeds and better market to you.

6. Fraud detection

When your credit card use seems a little different than usual, a machine learning algorithm can flag it for you. Rather than having people investigate strange occurrences manually, machine learning builds a model of your spending and can even temporarily freeze accounts when it predicts you’re not the one doing the spending.

7. Streaming recommendations

Ever wonder how Netflix seems to know just the right show to recommend? It’s because they too use machine learning to suggest your next binge-watch based on your previous watch history. Similarly, Spotify will pull together suggested playlists based on your listening preferences, and YouTube suggests related videos to the one you just watched. While much of it can be marketing, it tailors the customer experience and makes it better for all.

8. Traffic predictions

Whenever Google Maps (or your preferred navigation system) gives you an estimated time of arrival, it’s using machine learning to predict your trip’s duration. First, Google uses machine learning to build a model of how long certain trips take based on historical traffic data. Then, it uses that data based on your current trip and traffic levels to predict how long it’ll take to arrive at your destination. They’ve even partnered with DeepMind to further improve their graph neural networks.

9. Analyzing medical imaging

Radiologists and doctors need to analyze a monumental number of scans. This often leaves them tired, which can sometimes lead to errors. Fortunately, machine learning can help.

Machines can be trained to analyze medical imaging (like CT scans and MRIs) to identify any anomalies. For example, the technology developed by Infervision uses machine learning to diagnose cancer in patients more accurately. It’s an impactful way to put image recognition to task in service of improving healthcare.

How to get started with machine learning

Depending on what you want to do with your machine learning skills, you could take a few different learning approaches. Since machine learning is a subfield of data science, you’ll want to start by learning programming languages that are popularly used in the field. These languages include Python, R, and SQL. Use any of the links below to start learning these languages:

Once you’ve mastered these languages, check out any of the following courses to learn how to use them for machine learning:

If you’re looking for a more cohesive approach, our Data Scientist Career Path might be right for you. It’ll take the guesswork out of what to learn and in what order. It’ll also prepare you for other types of tasks, in addition to machine learning work.

What is React used for?

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What is React used for?

React has been growing in popularity and has become the JavaScript flavor of choice for many programmers due to its ease and speed. But what exactly is React, and what is React used for? This article will dig into what React is and how it creates effective user interfaces (UIs).

What is React?

React, also known as React JS, is a JavaScript library used to develop user interfaces. The user interface is what you interact with when you use a site or application. For example, think of when you rate a service by giving it five out of five stars. A developer may have used React to build the icons you selected, to dictate how the stars respond when you select them, or to determine how the data related to your choice is collected and used by the site.

As mentioned, React is a JavaScript library. Let’s break that down. JavaScript is a programming language used to develop websites. In the context of web design, a library is a collection of prewritten code. You can use these prewritten snippets of code to execute common functions in JavaScript. You can learn how to program with JavaScript in our Learn JavaScript course.

What makes React unique?

React is unique in that it allows you to break down the development of a complicated user interface/user experience (UI/UX) into simpler, smaller components.

If you’ve ever used a web template to build a site, you’ve likely noticed that you didn’t have to manually write the code to create headers, dropdown boxes, image boxes, or other modules. Instead, you simply had to select what you wanted and put it where it worked best. React allows you to use prewritten code for user interfaces in a similar way. However, instead of manually coding every aspect of a user interface, you can simply find what you need in the React library and include it in your design.

What is React used for?

React speeds up the process of creating user interfaces due to its diverse assortment of prewritten code. You can use this prewritten code to design a wide range of interactive functions in JavaScript more efficiently. Here are some examples of what React is used for:

Allowing users to interact with and view images

With React, you can design how users see images and what happens to them on the web page when users take specific actions.

For example, you can set up a carousel of images that automatically rotates, showing the next image when the user clicks the right or left edge of the image. You can also decide whether to incorporate arrows indicating whether the user is going to the next image or the previous one.

Manage how text appears on a page

When a page needs to display text — either text entered by an end-user or inputted by the page’s designer — React can be used to ensure it fits within a specific area.

For example, if you need a user’s name to fit inside the user’s avatar, you can use code from the React library to ensure the text is sized correctly and doesn’t overlap the edges of the avatar. You can also designate a specific space within the avatar for the text to go, so it doesn’t cover the avatar’s image itself.

Pick date ranges on a calendar

If you’ve ever used a booking website and had to choose dates for visiting an area, staying at a hotel, or flying round trip, you may have been using an interface designed with React. React can make it possible for the end user to choose the time frame or number of days and include features that allow dates to be highlighted when users hover over them.

Select items from a column of choices

React can be used to enable users to choose options from a column on the left and shift them into a column on the right that indicates the options they are interested in. The positioning of the columns — left/right or right/left — can also be adjusted, as can the buttons the user clicks on to indicate their choice.

In addition, React can decide what happens during the selection process. For example, a button can change color when the user hovers over it, or a choice can be highlighted after it has moved from one column to the next.

Automatically generate charts

With React, you can include automatic chart generation within a web app. You can generate a chart from input coming in from a variety of data sources. Charts can then be rendered as an image that the user can download.

A chart’s colors, formatting, spacing, and other aesthetic elements can automatically be set using React.

Design input fields for web apps

React can make it easier for end users to enter information in data fields on a web app by including features that make data entry more convenient. For instance, you can use React to set up rules that interpret abbreviations as numbers, such as “k” for 1,000 or “m” for 1,000,000. You can also give users the option of deciding the currency symbol they would like to use. If there needs to be a limit on the value of what users can enter, you can use React to set maximum and minimum values.

Create interactive map views

Using APIs, such as Google’s map API, you can use React to alter how a map looks to an end user based on the choices they make. For instance, you can make the map larger or smaller as the user zooms in, or you can display more or fewer street details and landmarks depending on the zoom level.

Because React features prewritten JavaScript, you can potentially use it to do anything JavaScript can do. In addition, React is open source, so with the right knowledge, you can create your own solutions and have them included in React’s library. To get started coding with React, you can enroll in our Learn React course. With our courses, you’ll not only get the knowledge you need to code in React and other leading languages, but you’ll get the experience needed to create a compelling portfolio to begin your career as a programmer. Get started for free today!

Preparing for a Data Engineer interview: Questions and more

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Preparing for a Data Engineer interview: Questions and more

While pursuing a career as a Data Engineer, one of the biggest hurdles you’ll face is the interview process. You can think of an interview as a verbal skills test in which your interviewer asks questions about your technical knowledge and problem-solving ability.

To do well in your Data Engineer interview, you’ll need to be well-prepared — and we’re here to help. Below, we’ll explore some of the skills and knowledge you’ll need to excel in your new career and some of the most commonly asked Data Engineer interview questions.

Data Engineer skills

Before applying to your new job as a Data Engineer, you’ll need to acquire key skills. The good news is that you don’t need to undertake a traditional degree program. Instead, you can take online courses related to data engineering or data science to fill the gaps in your knowledge.

To become a Data Engineer, you’ll need to be familiar with certain programming languages. Most Data Engineers will have a good grasp of Python. Depending on their specific role, they might also have experience with SQL (to access databases), R, or other languages. Frameworks like Vue.js or Flask are also a plus.

After you’ve learned the technologies and skills you’ll need for the role, you’ll want to practice. Even experienced programmers will often participate in larger open-source coding projects to stay current, learn new skills, and improve their ability to work with someone else’s code.

You can also practice your skills by undertaking projects that’ll help you gain practical experience and brush up on the skills you’ll need to discuss during your interview. If you need help finding data-driven project ideas, check out our Data Scientist Career Path.

Technical Data Engineer interview questions

As we explained earlier, many of your interviewers’ questions will be designed to assess your proficiency with the technical knowledge and skills required for data engineering. You might even be asked a question you weren’t expecting, but it’s important that you don’t panic or guess. Instead, explain that you don’t know the answer and outline how you’d approach finding a solution.

To help you prepare for your upcoming interviews, we’ve compiled a list of some of the most common technical Data Engineer interview questions:

  • Do you have any experience with ETL frameworks?
  • Have you designed a data system using Hadoop?
  • Can you describe what Hadoop frameworks are and how to use them?
  • What’s the difference between a NoSQL database and a relational database?
  • Can you define data modeling?
  • What type of data is stored in NameNode?
  • What functions are a part of Secondary NameNode?
  • What command would you use to view the structure of the database in MySQL?
  • How would you use MySQL to search for a string in a particular column?

Scan through the job posting you applied to and see if you can narrow down the questions you’ll use to practice. For example, if a job uses MySQL but doesn’t mention anything about Hadoop, you can skip the Hadoop questions for now.

Conceptual Data Engineer interview questions

Along with the technical questions above, you’ll probably be asked about more general concepts and ideas in your interview. These questions help your interviewer see how good you are at communicating and how well you can work with a team.

The answers to the conceptual questions likely won’t require as much memorization or review as the technical questions. Instead, you can practice these once or twice to make sure you have an appropriate example, process, or fact.

Here are some of the conceptual questions you might be asked in your Data Engineer interview:

  • How would you define data engineering?
  • Have you ever used an existing database for a new and exciting purpose?
  • What programming languages are you comfortable using?
  • Can you name three skills you think are most important for a Data Engineer and why?
  • In your new job as a Data Engineer, where would you start when developing a new product?
  • What qualities do you think make a good Data Engineer?
  • Can you tell us about a time that you used your data engineering skills to solve a problem?
  • How would you bring value to our organization?

Preparing for your Data Engineer interview

Don’t try to cram for your interview the night before. You’ll want to have a few days (at least) to review questions, practice your answers and even brush up on your coding skills. If you know any Data Engineers, ask them to help you rehearse.

You should also spend a little time on the company’s website and do a couple of Google searches to see where they might have appeared in the news recently. You’ll want to know as much as you can about the company so that you can tie your skills back to their products, services, and clients when they ask you questions.

We’ve said it before, but we’ll say it again — keep practicing. Many interviews involve in-depth questions about specific programming languages as hiring managers need to know you can utilize their tech stacks. To help you prepare, we’ve created a course designed to help you pass the technical interview with Python. Once you finish that, explore our other programming courses to fill in any gaps in your knowledge.

What does a product manager do?

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What does a product manager do?

Product Managers play a central role in bringing solutions to life by managing the successful development and launch of a product. They often serve as a liaison between the company’s goals as outlined by executives and the engineers who use those goals to create effective products.

In other words, a Product Manager plays a pivotal role that includes:

  • Maintaining a high level of focus
  • Stakeholder management
  • Product success

While a Product Manager may not get involved in specific coding decisions, they maintain a high-level perspective and encourage developers to move the product in the right direction.

In the video below, Pat DePuydt, a Web Developer from Washington D.C., takes a closer look at a Product Manager’s role. Read on (or watch the video) to learn more about their responsibilities and required skills.

Product Manager skills

To help you better understand a Product Manager’s duties, Pat provides an example:

Imagine a DevOps team tasked with building a web app users can use to book appointments. The team’s Product Manager will need to engage with various stakeholders (e.g., devs, executives, etc.) throughout the ideation, creation, and testing of the product. For example, they may be in charge of ensuring:

  • The app has a user interface that suits the needs of end-users from a functional perspective.
  • The app’s color scheme and layout are aesthetically pleasing for end-users.
  • The appointments users book with the app properly interface with an internal database, an API, or a customer relationship management (CRM) system.
  • The app functions as designed, meeting the expectations of all stakeholders.

To fulfill the responsibilities outlined above, a Product Manager needs to have a balance of technical, interpersonal, and conceptual skills to guide their team in the right direction. Let’s take a closer look at these skills and how they manifest in a Product Manager’s day-to-day.

Maintaining a focus on high-level objectives

Keeping high-level objectives in mind is essential to ensure the end product is both effective and aligned with the organization’s goals. An app can work very well and even be appreciated by end-users, but it still wouldn’t get the job done if it didn’t help advance organizational objectives.

Say a company’s executives decided to create an application that facilitated faster online ordering for a restaurant’s takeout menu. There are many factors the Product Manager would have to keep in mind throughout the app’s development, including:

  • Ease of use by customers
  • An accurate selection of menu items
  • Convenient payment options
  • Delivery options
  • Extra elements that may make the user experience more enjoyable, such as the ability to leave notes for the driver or enticing images of menu items

But, if the DevOps team started to get too heavily involved in making the menu as comprehensive as possible, the objective of designing “faster” online ordering may be compromised. The Product Manager would have to recognize this pitfall, identify why it’s happening, discuss possible solutions with their team, and report on this hiccup in the process to C-level executives.

Making ideas come to life

In the video above, Pat goes on to explain how a Product Manager needs to be able to take an idea and envision the technologies, systems, and procedures required to make it happen. This requires discernment. A Product Manager shouldn’t agree to take on the development of every single project without carefully considering its feasibility.

This requires an in-depth understanding of the capabilities, processes, and individual skill sets of those on the DevOps team. It also necessitates a deep familiarity with the technologies available to the team and a general understanding of how they work and what they can do.

An adequate depth of understanding requires a degree of technical fluency. While discussing a Project Manager’s role in our forums, Richie W., one of our Senior Product Managers, explains how they need to understand:

  • How APIs work
  • How microservices work
  • Systems design
  • The difference between client vs. server
  • Databases
  • Tech debt

Richie goes on to explain how Product Managers need to be familiar with SQL because “a large part of the job is understanding data and having the ability to query on your own.” Check out our Learn SQL course if you want to learn how to use the programming language to query databases and manipulate data.

Lastly, if you’re looking to become a Product Manager in the tech industry, Richie suggests building a few apps yourself:

“The best way to understand technology is to build something simple. I’d recommend you go through Codecademy’s web development path, for instance, and work through one of the web projects.”

Learning how to build an app will give you a better understanding of your team’s dependencies and processes. Take your first steps into web development by learning how to build a website.

Guiding the development process

A Product Manager has to make decisions that improve the quality of the end product and the speed with which it gets developed, ideally without significantly sacrificing one for the other. This requires them to understand how long different processes take to complete. They also need to understand each stage of the development process, including how long they’ll take.

Then, as the process unfolds, they need to check in with developers to see if things are shaping up the way they should. At times, this may involve connecting with the team lead to see if there are any roadblocks the team needs to huddle around to overcome.

Ensuring a minimum viable product

A minimum viable product (MVP) is a product that consists of only its most essential features, without any bells or whistles. Basically, a Product Manager needs to ensure that a product does what it’s supposed to by the project’s deadline. There are always additional features that can help polish a product, but they’re not always worth the time they’d take to develop. Plus, as Pat explains, if a product’s core utility doesn’t resonate with its audience, no amount of polishing will make it a success.

Measuring success

Another critical element of guiding the development process is understanding how the target market will receive the product. This involves collecting data on both the market and the product’s technical performance.

One of the best opportunities to gather data about a product is when it is tested and fails. Failures often yield insights that are more helpful than those derived from successful test runs.

To pull insights from tests and measure the success of a product, a Product Manager needs to know:

  • Which data sets to gather
  • How to get the appropriate data during the testing phase
  • How to present the data to the DevOps team
  • How to use the data to improve the next iteration of the design

Factoring in competition

A Product Manager must also consider the competition while plotting the course of a project. The objective is to keep an eye out for products that can accomplish the same thing yours does but better, faster, or cheaper. The Product Manager then has to make sure their product can compete with their competitors.

How to become a Product Manager

In sum, Product Managers play a critical role in the development process — serving as a guide, coach, source of ideas, and more. Still, if you’re considering a career as a Product Manager in the tech industry, you’ll need a degree of technical knowledge and skills to properly manage your DevOps teams.

To start building the technical skills you’ll need in your career as a Product Manager, check out our Code Foundations Skill Path. We’ll walk you through the basics of computer science and programming as you learn how to code with popular languages like Python and JavaScript. After that, continue building your skills with any of our programming courses and tutorials.

Should I learn R?

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Should I learn R?

If you are new to programming and trying to decide where to start, the choices can seem endless. There are so many programming languages to choose from. How do you know which one is for you?

The R programming language may be one of the languages you ran into in your search. And you might be wondering if R is the language for you. To help you decide, let’s take a look at why someone would want to learn R, what it is used for, and how easy it is to learn.

Why should I learn R?

R is the programming language for data. It was designed for statisticians and is specialized for statistical programming. There are a multitude of libraries that give the language capabilities in data visualization and machine-learning. You might think this specialization limits the usage of R. Still, it is actually a popular programming language used in just about every industry you can think of.

Modern business runs on data. Every company has potential insights that would remain buried in the terabytes of data generated every year if it wasn’t for data analysts and data scientists. In fact, businesses of all types and sizes choose to unlock these insights in their data with the R programming language. So let’s look at some of the things you can use R for.

What is R used for?

R is one of the most in-demand programming languages in many industries. Here are some places R is used:

Healthcare

R is used in drug discovery to analyze the data in pre-clinical drug trials and to predict how a pandemic will spread in epidemiology. It is also used in genetics and bioinformatics.

Fintech

Fintech businesses use technology to handle money, and R is widely used in this industry. For example, quantitative analysts use R to devise trading models that automatically invest clients’ money in the stock market. In addition, banks use R to create credit risk models, fraud detection models, mortgage models, and loan stress test simulations.

Weather

The National Weather Service uses R to predict disasters, forecast the weather, and create weather forecast graphics.

Research

Academics and researchers use the R programming language extensively. Just about every course at Cornell involving statistical computing teaches R. University of California students are introduced to R to study statistics and data analysis.

Retail

Retailers and e-commerce businesses use R to assess risk and create marketing strategies. R’s machine learning technology capabilities are used to increase profits and sales through cross-selling and suggesting related products at checkout. Retailers also use R to model sales and target advertisements. The data analytics departments of Amazon and Flipkart both use R.

Manufacturing

Many companies use the R programming language to analyze customer feedback and improve their products. To improve the design and appeal of Ford’s vehicles, Ford analyzes consumer sentiment using R. With the help of R, John Deere can calculate how many spare parts and products are necessary based on crop yield and other data.

Social Media

Data abounds in the social media industry. Every time we use the internet, we are tracked. Each and every action is recorded in some database, waiting for an analyst to examine it. In many cases, a social media site’s only source of revenue is the data it has on its users and targeted advertising. R programs are used for social media analytics, segmenting prospects, and targeting ads.

Can I learn R on my own?

Of course, you can. In fact,many working programmers don’t have a computer science degree and have learned how to program outside of college. While many programming jobs do require a degree, it does not have to be in computer science. Programmers are in such high demand that programming skills are often all you need to get the job.

So building R programming skills on your own at your own pace is always a great option. But if you are new to programming, it can be tough to know where to start. Our Learn R course is designed for beginners. It starts with concepts that anyone can grasp and takes you all the way to becoming  an R data analysis expert.

How quickly can I learn R?

The time it takes to learn R depends on the time you devote to learning and what you want to do with the language. A beginner-friendly course like Learn R takes about 20 hours to complete. So if you have an hour a day to devote to learning R, then you can complete the course in less than a month. Of course, if you have more time, you can complete the course even quicker. You may also find you really like the language and want to spend more time learning and take more courses.

Where to learn R

Now you should know a little more about the R programming language. So what do you think? Is it the language for you? It might be if you are interested in data analysis, data visualization, or machine learning. And R programmers are always in demand in multiple industries because every modern enterprise needs data analysis experts to provide insights that help businesses grow and thrive.

If R is your language of choice, then check out our Learn R course. This will teach you fundamental programming concepts using R. You will learn how to organize, modify, and clean data, create data visualizations, and know the basics of statistics and hypothesis testing. To take your R education even further, you can take our Analyzing Data with R Skill Path for more hands-on training in statistical programming. For a deeper dive into statistics, you can try Learn Statistics with R.

Introduction to ‘Film Club’

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Introduction to ‘Film Club’

Every week of the school year, we feature a short documentary film published in The New York Times. These films ask students to consider a variety of themes like ethics, civil rights, gender identity and scientific discovery. Each Film Club entry begins with an essential question to help frame the lesson, followed by a set of questions to help students connect the film to their own lives. This feature help students develop visual literacy skills and gives teachers another way to approach important issues.

Find all of our Learning Network tutorials in this video playlist.

Introduction to ‘News Quiz’

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Introduction to ‘News Quiz’

Every week of the school year, we publish a 10-question interactive quiz to challenge students’ knowledge of the week’s biggest news stories. The quiz invites students to select the missing words or phrases from selections of recent New York Times stories. It also challenges students to discern between real and fake headlines, and to match a mystery photo with the news story it depicts. Practicing with our weekly news quizzes can help students keep up with the news and get in the habit of following current events.

Find all of our Learning Network tutorials in this video playlist.

Indian Institute of Management Kozhikode partners with Coursera to launch four job-relevant certificate programs

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Indian Institute of Management Kozhikode partners with Coursera to launch four job-relevant certificate programs

Indian Institute of Management Kozhikode partners with Coursera - June 2021

By Betty Vandenbosch, Chief Content Officer at Coursera

Today, I am excited to announce four certificate programs in the high-demand fields of business, strategy, marketing, and product management from our new partner, the Indian Institute of Management Kozhikode (IIMK). 

IMK is one of India’s top-ranked management institutions. As the fastest-growing management school in India, it is widely recognized for continually innovating its curriculum and pedagogy to further its social impact. The school is a champion of gender diversity. With 54% women in its flagship Post Graduate Programme, IIMK has the highest percentage of women students at any Indian Institute of Management. 40% of its Board of Governors and 30% of its faculty are also women.  

“In our 25-year history, IIM Kozhikode has always sought to carve a unique space and keep itself relevant by constantly innovating and reinventing its content and delivery. This partnership with Coursera seamlessly dovetails with these ideals. Coursera, with its robust platform, AI-driven tools, and global reach, will be a great foil to IIMK’s commitment to the 3D’s — Digitisation, Diversification, and Disruption,” said Prof. Debashis Chatterjee, Director IIM Kozhikode. “As the field of education transforms dramatically in a post-pandemic world, this partnership, I believe, will provide great value to our domestic and global audiences. Together, we will introduce learners to new and refreshing perspectives as we pursue our motto of globalizing Indian thought and nurturing value-driven, fair-minded individuals.”

IIMK’s new programs are 6-8 months long and offer graduate-level, interactive learning, including live sessions with renowned IIMK professors and rigorous capstone projects.

  • Business Management — To prepare future executives, leaders, and entrepreneurs, this eight-month program teaches the frameworks, strategies, and tools needed to strategically drive business forward amid digital transformation.
  • Strategic Management — This program transforms working professionals into results-driven leaders by teaching them growth strategies, data-driven decision-making, and proven leadership tactics.
  • Marketing Strategy — Designed for marketers looking to advance to a leadership position, this program provides a broad snapshot of marketing, focusing on how to use data mining, AI, and automation to better understand and reach customers.
  • Product Management — This program teaches the hard and soft skills needed to excel as a product manager, from market research and prototyping to project management and product development. No technical background is required.

We are honored to partner with IIMK to expand access and allow anyone to learn the cutting-edge skills needed to advance their career from one of India’s leading institutions. By adding new university partners in India, we can better serve the country’s 11 million learners on Coursera.

 

For Most Latinos, Latinx Does Not Mark the Spot

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For Most Latinos, Latinx Does Not Mark the Spot

This essay, by Evan Odegard Pereira, age 16, from Nova Classical Academy in Saint Paul, Minn., is one of the Top 10 winners of The Learning Network’s Eighth Annual Student Editorial Contest, for which we received 11,202 entries.

You can find the work of all the winners and runners-up here.

For Most Latinos, Latinx Does Not Mark the Spot

“Don’t you mean Latinx?”

My white classmate had a confident look on his face. I was one of the only Latinos in the school, but that didn’t stop him from labeling me.

“No, I don’t.”

Silence followed, and his confidence turned into confusion.

“It’s complicated,” I added, trying to ease the situation and avoid a full-on rant.

The United States has always had trouble categorizing people of Latin American descent, and the term Latinx is just the most recent example. Created as a gender-neutral alternative to Latino or Latina, it has gained momentum over the past decade and is now used by politicians, universities and corporations eager to signal their awareness of this new term. Despite its good intentions, many Latinos, including myself, view it as problematic.

Latinx doesn’t work as an ethnic label mainly because it’s not even embraced by the community it describes; according to a 2020 study by the Pew Research Center, only 3 percent of U.S. Latinos use the term. Most haven’t heard of it, and those who have overwhelmingly reject it. Many of us find Latinx confusing or culturally offensive.

This is partially because of the term’s linguistic nuances. Latinx is an Anglicization of our language, an artificial label that defies the basic rules of Spanish pronunciation. To native Spanish speakers, Latinx feels foreign and imposed.

Conversations about gender inclusivity in Latin America have already been happening since long before the introduction of Latinx. Activists in Argentina have offered Latine as a non-Anglicized gender-neutral option which actually works in Spanish. Other accepted gender-neutral terms include Latin and Latin American. These alternatives prove that Latinx is simply not necessary.

Language changes over time, but such adaptations must be organic. Forced changes from outside our community are a form of linguistic imperialism, which centers the English language and perpetuates cultural erasure. At its core, this is an issue of linguistic self-determination. The Latino community doesn’t need politicians and corporations to “fix” our language; we can confront our community’s issues on our own terms.

It’s important that our society move toward gender inclusivity. But imposing an unwanted label on another community isn’t the right way to do that. While well-intentioned, the use of Latinx creates more problems than solutions, and makes Latinos feel ignored and disrespected.

To would-be allies, rather than rushing to embrace the latest progressive shibboleth, please step back and allow us the space to identify ourselves on our own terms. I am not Latinx. I am Latino, Latine, Latin or Latin American, and I’ll resist any attempt by someone else to define me con todo mi corazón.

Works Cited

De León, Concepción. “Another Hot Take on the Term ‘Latinx’.” The New York Times, 21 Nov. 2018.

Douthat, Ross. “Liberalism’s Latinx Problem.” The New York Times, 5 Nov. 2019.

Inocencio, Josh. “Why I Won’t Use Latinx.” Spectrum South, 6 Sept. 2017.

Lopez, Mark Hugo et al. “About One-in-Four U.S. Hispanics Have Heard of Latinx, but Just 3% Use It.” Pew Research Center, 11 Aug. 2020.

McWhorter, John. “Why Latinx Can’t Catch On.” The Atlantic, 23 Dec. 2019.

Politi, Daniel. “In Argentina, a Bid to Make Language Gender Neutral Gains Traction.” The New York Times, 15 April 2020.

Back-end programming languages: Which should you learn first?

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Back-end programming languages: Which should you learn first?

Back-end development can be an interesting and exciting career path. Like other Web Developers, Back-End Developers are in high demand. You can also expect to make a decent living, with the average salary for these developers being $122,445 in the U.S.

If you’re considering a career in back-end development, you’re probably wondering which programming language you should learn first. Ultimately, it depends on your career goals. There are multiple languages used for back-end development, and each has further applications in other fields.

To help you decide, we’ll explore some of the most popular programming languages used by Back-End Developers and their various applications. But first, let’s start by looking at exactly what back-end development is.

What is back-end development?

The back end of a website consists of web servers, applications, and databases. Back-End Developers write the code for applications that run on the webserver and queries that they embed in these applications to allow them to interact with databases.

The back end of an application provides data for the front end, which runs in the web browser and formats and renders raw data into the finished web pages you see. These applications are called APIs (Application Programming Interfaces) and usually return data in a JSON text format. Other back-end applications can generate complete web pages with only back-end code.

To learn more about the field, check out our article on a Back-End Developer’s role and responsibilities.

Finding the best back-end development language for your goals

Before we start looking at the programming languages you have to choose from, there are a few questions you should consider. What kind of back-end applications do you want to work on? Which industries do you want to work in? And since most of these languages also have other uses, what other types of development are you interested in?

Knowing the answers to these questions will help you decide as we look at each programming language. You might also want to ask a Back-End Developer for advice. Reach out to developers you know or find them on Stack Overflow and ask about their favorite languages.

Back-end development programming languages

Now that you know what back-end development involves, let’s explore some of the most popular programming languages used in the field. Each language listed below is used for back-end development, but we’ll also touch on some of their other applications.

JavaScript/Node.js

Until the creation of Node.js, JavaScript was originally a language used only in web browsers. Node.js is a JavaScript platform that can run by itself without a web browser. It’s used on web servers and allows developers to create complete back-end applications with JavaScript. There are also frameworks like Express that enable you to build back-end web apps and APIs with JavaScript.

With JavaScript’s wide range of applications in front-end development and Node.js extending its use into the back end, being familiar with both will allow you to build complete web applications without learning another language. This is great if you’re considering a career as a Full-Stack Developer.

Java

Java is a multipurpose, object-oriented programming language used extensively in business to build enterprise-scale web applications. So, if you plan on developing web apps in the corporate world, you’ll likely run into Java.

The Java Enterprise Edition (Java EE) provides web development technologies for enterprise developers like distributed computing, web services, and other features that make creating complete business applications easy. Java Servlets, JavaServer Pages, and the Spring Framework are commonly used for Java web development by big companies, small companies, and single developers.

Learning Java for back-end web development means you’ll be well-prepared for a career in enterprise development. It’s also a great choice if you’re interested in mobile development, as it lies at the heart of many Android apps.

Python

Python is a general-purpose, multi-paradigm programming language used for scripting, automation, data analytics, data visualization, machine learning, web development, and more. Its easy-to-read syntax and versatility make it a favorite among new developers.

Python is commonly used for back-end development, but with third-party frameworks like Flask and Django, you can use it to build complete web applications. Python’s especially popular among startups because these frameworks expedite the process from prototypes to live sites.

Along with back-end development, Python’s capacity for data analytics and machine learning means it’s a great choice if you’re considering a career in data science.

PHP

PHP, which stands for “PHP: Hypertext Processor,” is an open-source programming language created specifically for web development. Today, you can find PHP in over 75% of all websites that use a server-side scripting language.

PHP is easy for beginners to pick up because it can be embedded in HTML files and has many built-in functions that may not come with other back-end languages. It’s also used widely to develop content management systems and e-commerce platforms, like WordPress, Drupal, and Magento, so knowing PHP means you can also create plugins and themes for these and other widely-used CMSs written in PHP.

Ruby

Ruby is a general-purpose programming language used for scripting, DevOps, static site generation, and web development. Ruby’s popularity in web development stems largely from its Ruby on Rails framework, which gives developers a set of tools and reusable code that they can use to speed up development time. Many programmers learn Ruby simply so they can use Ruby on Rails to build and deploy web apps quickly.

C#

C# is a modern object-oriented, general-purpose programming language. Microsoft created it for development on the Windows operating system using the .NET framework, where it became the top web development language used on Windows in ASP.NET. The language has since been updated so that it can run on Linux and even Mac OSX. C# is a good choice for web development if you plan to develop applications for multiple operating systems.

Getting started as a Back-End Developer

There are many back-end programming languages out there, but hopefully, the information above will help you find the one that’s best for you. To get started with any of these languages, use the courses listed below:

If you’d prefer to learn everything you’ll need to know all at once, check out our Back-End Engineer Career Path. In this Path, you’ll learn how to program with multiple languages, use them to build projects that you can use to build a portfolio, and more. You’ll also earn a certificate to include in your resume upon completion.

Whichever path you choose, we’re happy to help you find your way and wish you the best on your back-end development journey.

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