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.
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.
Ready to test your knowledge of current events? Get started here.
Find all of our Learning Network tutorials in this video playlist.
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.
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.
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.
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.
Modern businesses collect and generate huge amounts of data, and they rely on data professionals to help them make sense of it all. Still, not every company needs the multidimensional skills of a Data Scientist. For many smaller companies, a Data Analyst is more than enough. So, if you’re considering getting into the field, now’s a great time to do so.
But, before you sign up for a career in data analytics, you’re probably wondering how much a Data Analyst makes. Below, we’ll explore the average salaries for Data Analysts by location, industry, and experience level. Or, if you’d rather jump right into building the skills you’ll need to excel in this career, check out our Data Analyst Career Path.
Data Analyst salaries based on location and industry
According to ZipRecruiter, the average salary for Data Analysts in the U.S. is $67,294 per year. Still, your salary as a Data Analyst will depend on your location. LinkedIn and Indeed tell us that the average Data Analyst’s salary ranges from $63,000 to $71,053 a year.
To break it down even further, Data Analysts in North Carolina have the lowest average salary at $49,690. Data Analysts in states like New York, New Hampshire, Massachusetts, D.C., and Washington generally earn slightly higher than the given average. Still, in most states, you can expect at least $60,000.
Industries with a higher demand for Data Analysts tend to provide higher salaries. For example, CareerFoundry found that Data Analysts in the mining industry can earn as much as $117,000. Other high-paying industries include information technology, healthcare, finance, insurance, and professional services.
Data Analyst salaries based on experience
Of course, your experience will also influence your salary as a Data Analyst, as well as your responsibilities. Entry-level Data Analysts design business solutions based on the insights they derive from their data and earn about $54,272 on average.
Mid-level Data Analysts with 2 – 4 years of experience earn a slightly higher salary at $70,123 and perform many of the same tasks as their entry-level counterparts. Senior-level Data Analysts with 4 – 6 years of experience take on bigger projects and help train new analysts. Once you get to this point, you can expect a salary of around $87,713.
Lastly, the highest-paid Data Analysts are consultants who work directly with a company’s executives, managers, and clients. These analysts, with 6 years of experience or more, can earn an average of $106,234.
Still, once you launch your career as a Data Analyst, there are several steps you can take to demand a higher income. Indeed recommends building on your technical expertise by learning more programming languages, creating side projects, and transitioning into data science or data management fields.
What do Data Analysts do?
As we explained above, Data Analysts work in a variety of industries. They may be most closely associated with the financial industry because of its heavy reliance on data. There’s also a great demand for Data Analysts in healthcare, marketing, retail, insurance, and technology.
Generally, Data Analysts take large amounts of data in any of these fields and analyze it for trends and patterns — making predictions and finding insights that can better inform a business’s decision-making.
A Data Analyst should be good at handling numbers, details, and managing multiple tasks. You’ll also need to know how to present your findings in a way that your teammates (both technical and non-technical) can understand.
Data analytics itself is changing in instances where big data is involved. Big data refers to any set of data so vast that the standard programs and methods are not adequate to process it or analyze it. If you can show a prospective employer an understanding of the changes happening in the data analytics field, you could land a higher role with more responsibility and compensation.
How to become a Data Analyst
Ready to kick off your career as a Data Analyst and start chasing the salaries listed above? First, you’ll need to learn programming languages like SQL, which is used to query data from relational databases, and R or Python, which are used to organize, analyze, and visualize data. Use any of the courses below to start learning these languages:
Or, if you’d rather build all of the skills you’ll need at once, check out our Data Analyst Career Path. We’ll teach you how to use the languages above, along with libraries and frameworks like pandas and NumPy, to analyze datasets and communicate your findings. Plus, as you complete the Path, you’ll create projects that you can use to build a portfolio, and we’ll even give you some tips on passing your technical interviews once you’re ready to start looking for an entry-level position.
Many of the computer programming languages you learn about are general-purpose. You can use them to build all types of applications. However, other programming languages are designed for a specific task and become well-known because they do that task more efficiently or make programming the solution easier. R is one of these specialized programming languages.
R is a programming language created by statisticians for statistics, specifically for working with data. It is a language for statistical computing and data visualizations used widely by business analysts, data analysts, data scientists, and scientists. Let’s look at more details of the R language to see what makes it different.
What makes R unique?
R is unique in that it is not general-purpose. It does not compromise by trying to do a lot of things. It does a few things very well, mainly statistical analysis and data visualization. While you can find data analysis and machine learning libraries for languages like Python, R has many statistical functionalities built into its core. No third-party libraries are needed for much of the core data analysis you can do with the language.
But even with this specific use case, it is used in every industry you can think of because a modern business runs on data. Using past data, data scientists and data analysts can determine the health of a business and give business leaders actionable insights into the future of their company.
What is R used for?
Just because R is specifically used for statistical analysis and data visualization doesn’t mean its use is limited. On the contrary, it is a widely-used programming language. Academics, scientists, and researchers use it to analyze the results of experiments. In addition, businesses of all sizes and in every industry use it to extract insights from the increasing amount of daily data they generate.
Fintech
Fintech companies are companies that deal with financial services. R is used at many of these types of companies because money and statistics go hand-in-hand. Banks use the R language to create credit risk models and conduct other types of risk analysis. It is also used for fraud detection, mortgage modeling, volatility modeling, client assessment, and loan stress test simulations.
Research
The R programming language is widely used in academics and research. For instance, Cornell University teaches R in courses that require statistical computing. The University of California teaches students statistics and data analysis by introducing them to R, and many other universities do as well.
Retail
In retail and e-commerce, R is used for risk assessment and to create marketing strategies. For example, R’s machine learning capabilities are used to improve cross-selling and suggest better-related products at checkout to increase profits and sales. R is also used for sales modeling and targeted advertising in retail. Both Amazon and Flipkart use the R programming language for data analytics.
Government
The National Weather Service uses the R programming language to predict disasters and to forecast the weather. They also use the visualization features of R to create weather forecast images. In addition, the FDA uses R to evaluate drugs, perform pre-clinical trials, and predict possible reactions caused by the food products they review.
Data journalism
Data journalists use data to tell a story. They are journalists and data scientists who pull insights about our world and how we live from public data. This can be information from local government and police sources to tell a story about crime, financial data to show the state of a country’s economy or any other type of data that reveals an interesting pattern in how our world works. R is a popular language for data journalists because it gives them the ability to find these insights and generate stunning graphics that tell the story.
Social media
Social media has always been a data-heavy industry. We are tracked everywhere we go online. Every single action is stored in some database, waiting for an analyst to pull insights from it. Most social media sites’ only source of profit is the data they have on their users and targeted advertising. The R programming language is used for social media analytics, segmenting potential customers, and targeting ads.
Healthcare
R is heavily used in genetics, bioinformatics, drug discovery, and epidemiology. For example, in drug discovery, R is used to crunch the data gathered in pre-clinical trials and determine how safe a drug is. In epidemiology, it is used to predict how a disease will spread in a pandemic.
Manufacturing
Many companies use the R programming language to analyze customer feedback to help them improve the products they create. The Ford Motor Company uses R to analyze consumer sentiment about its vehicles and improve their design. John Deere uses R to determine how many spare parts and products they need to produce based on crop yield and other data.
Learn more about R programming
Ready to jump into the exciting world of data? Start with Learn R to learn how this powerful programming language works and become a data expert. You can then take your education further by learning how to analyze data with R or one of the other courses available in our R programming language course catalog.
For today’s digest I teamed up with Dr Chiara Horlin who is a Lecturer (Assistant Professor) in Psychology at the University of Glasgow and an expert in neurodiversity and what role it plays in education. She has co-founded The Neurodiversity Network (see below) as a resource to support and represent neurodivergent students and staff. Before diving into the resources, it is important to know what neurodiversity is. So, I asked Chiara for a definition of neurodiversity and why it matters for education:
Neurodiversity is an understanding and a recognition that not all brains are the same or work the same way. Much of this world is built for a typical type of brain, for people that think in a typical type of way. But in reality we all think differently, we learn differently, we feel and we experience moods differently as well and these differences are completely normal. Sometimes these differences are given specific labels like ADHD or Autism, but understanding neurodiversity means recognizing and respecting these differences. It also means understanding that neurodiversity can bring huge benefits to those with learning and thinking differences. An acknowledgement and a respect for these differences can not only reduce stigma around differences, but can also support people to build unique strengths and capabilities.
All ability and disability must be considered in a social context and education systems are one of those social systems that can cause a difference to become a disability or disadvantage where one need not necessarily exist. Much of our education systems are not designed to support cognitive or learning differences, but due to necessity are targeted at a ‘prototypical’ student. Neurodivergent students will always fall outside this prototype and an inclusive approach to what learning looks like, and what achievement looks like is essential in supporting them. Neurodiversity must be considered in the context of strengths, differences and challenges, and the metrics of success adjust accordingly. Neurodivergent people may have skills particularly suited to further education beyond school, such as proficient memory skills, a focus on detail, creativity, as well as passionate interests. and a strong desire to acquire accurate knowledge. Neurodivergent conditions nearly always present heterogeneously and so there are vast differences in coping mechanisms and skills. However, even when able to flex these unique skills, students have been reported to have a heightened risk for academic and personal challenges, do not have their social or academic needs met, and thus might not reach their full potential.
From this it becomes clear that obtaining a full understanding of neurodiversity is important to support neurodivergent students in your classroom. Here are five resources to get you started.
This essay, by Norah Rami, age 17, from Clements High School in Sugar Land, Texas, 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.
Teach Us What We Need
My one year of sex education involved learning to spell abstinence (100 percent effective) and watching videos of teenagers regretting premarital S-E-X (I just felt so dirty!). For a class called sex education, sex was hardly mentioned without the word “never.” Rather than give me the tools to make safe decisions about my body, I, like many teenagers, was left in the dark by our inadequate sex education curriculum.
In my home state of Texas, sex education is optional, and, if offered, the course must be “abstinence-centered.” However, in the fall of 2020, Texas announced it would update its sex education curriculum for the first time in 23 years. My friends and I wrote to our representatives asking them to include consent, contraception, L.G.B.T.Q. identities and sexual harassment in the curriculum, but our calls fell on deaf ears. Teaching consent was out of the question as it would give “yes to sex as an option on the table for teenagers”; the mere phrase L.G.B.T.Q. was ignored; and sexual harassment was reduced to sexual bullying with the definition of “you’ll know it when you see it.”
The blunt truth is teenagers will have sex. Rather than ignore the given, our education system has the responsibility to give them the tools to be safe. When it comes to conversations about our bodies, teenagers don’t need shame or fear — we need guidance. In today’s world, where teenagers are exposed to sex through television and the internet with skewed perceptions of consent and contraception, it’s more important than ever to address these topics often thought of as “taboo.”
By working toward comprehensive sex education, we invest in the future, combating poverty and mitigating inequality. Our current sex education system has been costly. Abstinence-focused education has been shown to increase rates of teen pregnancy, a key factor in a heightened likelihood of poverty and maternal mortality. Texas, with its abstinence-centric education, has one of the highest teen pregnancy rates in the United States. Our deficient sex education curriculum is condemning our children. This is compounded in cases concerning L.G.B.T.Q. education, where students often lack further guidance from parents and peers; inclusion can protect the health of L.G.B.T.Q. students by increasing awareness of protection and sexually transmitted diseases, and even promote tolerance through simple acknowledgment. Furthermore, by including consent in our curriculum, students learn to value individual boundaries and create a safer world of respect and autonomy.
While most teenagers won’t be using calculus anytime soon, sex education is pertinent both for their today and their tomorrow. It’s time to improve our outdated and inadequate system into one that doesn’t fail our students but rather empowers them to make educated decisions about their bodies.
When you start programming, it can be tough to decide which programming language to learn. Both Python and JavaScript are great choices for beginners, but what are the differences, and why would you want to learn one over the other? In this article, we’ll take a look at both languages to figure out which one suits you the best.
What is Python?
Python is a flexible, general-purpose programming language that’s a favorite of many developers because it’s concise and easy to read. It started as a language used for writing scripts and utilities, but it became popular and quickly spread to other uses. After all, it was created to be general-purpose.
Python is used for back-end web development to create web applications that run on the webserver. The language’s versatility allows developers to use a range of programming styles to develop both highly complex and simple web applications. Plus, Python web development frameworks like Flask and Django make the process even easier by providing prebuilt code that developers can include in their projects.
Python is also frequently used in data science, scientific computing, machine learning, computer vision, image processing, and more. Because of its easy-to-read syntax, many experts from scientific fields have developed third-party Python libraries that extend the language’s functionality.
This includes NumPy, which adds powerful numerical computational tools, and pandas, one of the most popular data analysis and manipulation tools. You can use SciPy, TensorFlow, or one of the many other machine learning libraries available in Python for machine learning. To visualize data in Python, you can use Matplotlib or seaborn.
Getting started with Python
Ready to start learning Python? Check out our Learn Python 3 course, where you can learn fundamental programming concepts while building software using the most recent version of the Python programming language.
Since there are many uses for Python, you probably won’t want to stop there. Where do you want your new Python skills to take you? If you’re considering a career in data analytics, take your first steps into the field by Analyzing Data with Python. You can then take your skills further and learn how to Analyze Financial Data with Python.
The first version of JavaScript was designed to be a lightweight, simple language used to add dynamic features to web pages. While Java, Flash, and Silverlight were also once used in web browsers, they fell out of favor, and JavaScript became the only programming language associated with front-end web development. JavaScript works with HTML and CSS to create dynamic, modern web pages.
JavaScript has been updated over the years, adding more features that enabled developers to do even more in the web browser. Many front-end development frameworks written in JavaScript allow developers to create complete applications that run in the browser, including React, Vue.js, and AngularJS. JavaScript has come a long way from its simple roots.
Today, you can use JavaScript for more than just front-end development. With tools like Node.js, you can run JavaScript on a web browser. This means that you can now build both the front end and back end of a web application without switching programming languages. Plus, with frameworks like Express, you can create your own back-end services and APIs.
JavaScript is also used in mobile development to create apps that run on both Android phones and iPhones. React Native is a JavaScript library that gives developers the ability to use HTML, CSS, and JavaScript for mobile application projects.
Getting started with JavaScript
Want to learn more about JavaScript? Our Learn JavaScript course will teach you all you need to know to start writing JavaScript code while learning basic programming concepts.
But there’s just so much you can do with JavaScript that not all of it can be contained in one course. Where you go from there depends on what you plan on doing.
A lot of beginning JavaScript developers gravitate toward front-end development. If that is the path you want to take, then our Front-End Engineer Career Path can give you the skills you need to build complete front-end applications. Or, you can start with back-end development in our Back-End Engineer Career Path. If you’re up for learning both at the same time, check out our Full-Stack Engineer Career Path.
Python or JavaScript? Which is the right language for you? You can build web applications with both, but with Python, you can create the back end of a web app, and with JavaScript, you can create both the front end and back end. Then again, with Python, you’ll also be able to do data analysis and machine learning and turn raw data into insights. Check out even more languages you can learn in our programming course catalog.
