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The Gift
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Word of the Day: perpetuity
This word has appeared in 52 articles on NYTimes.com in the past year. Can you use it in a sentence?
Setting Boundaries at Work
In the same way that guardrails and barriers protect us when we’re driving on the road and keep us safe, we need boundaries to keep ourselves safe. Boundaries help you maintain a level of control of your work life, your relationships, and what you give your time to. Boundaries help you direct your energy on what matters most, what you can and should prioritise, what you’re able to do and help you avoid burnout. In this article, we’re going to provide some guide on how to set boundaries at work and give you essential tips to ensure parties adhere to them.
What are boundaries?
A boundary is a limit that you set up to help individuals understand how to navigate various situations and interactions with you. These boundaries can be tangible (physical) or intangible (emotional and mental).
Physical boundaries
Physical boundaries refer to your personal space and have to do with your body, and what you are comfortable with. An example of this is choosing to work in a conference room (away from people) if you want to focus on a particular task. This can also take the form of saying “no” to a late night out because you know how your body responds to lack of sleep. And finally, this can also look like scheduling breaks in your workday to get fresh air, regroup, and come back fresh and energised to continue at work.
Emotional boundaries
Emotional boundaries speak to how you prioritise your feelings, thoughts, ideas and having them respected. They also mean not feeling forced to adopt other people’s thoughts, opinions and struggles or challenges that you don’t have the capacity to take on or are comfortable with. In the workplace, this can look like choosing not to discuss your personal life (or certain aspects of it) with colleagues, not taking responsibility for other people’s feelings. You are only responsible for your actions. Stand up for yourself, defend your choices or say something if you are unjustly criticised.
Why are boundaries important at work?
To do the best at work, you need to be in the right mental space – which means setting healthy boundaries. There is only so much any one person can do and sometimes, your boundary will look like saying “no” to one thing so that you can say “yes” to another.
Boundaries at work help define the roles and responsibilities each person has. They also help you avoid burnout, feeling resentful, unsatisfied in your job, and often have a negative impact on your mental health.
But boundaries help from strong and healthy relationships. And a happy employee who feels safe and respected at work is bound to want to do more.
Tips for setting boundaries at work
It’s one thing to know your boundaries. If your colleagues don’t know your boundaries, they will without malice or bad intention infringe on them because you didn’t communicate these ahead of time.
The most important thing you need to establish is what is important to you. Ask yourself what your boundaries are to ensure you are happy and productive at work. You need to know what is important to you. If family and personal time is important to you, set time aside for when you deal with work related issues like replying to emails or taking calls outside of work hours. This helps you separate your work and personal life
- Communicate your boundaries
Once you have set your boundaries up, communicate these with your team, manager, and other co-workers. This lets them know in advance what is acceptable and not acceptable to you. Have clear and honest conversations about these. And if you feel they are disrespecting your boundaries, be proactive. Have the often-difficult conversations explaining that they stepped on your boundaries, how that made you feel, and the impact of their actions.
Don’t wait for issues to pile up for months and then let them all out at once. Speak about it as soon as it happens and remind them of your boundaries
- Create structures to support your boundaries and keep them in place
It can be difficult for people to understand your perspective on things. You are obligated to perform certain tasks at work. On other occasions, you may be asked to do more than what your role is. Explain your work loads, high priority tasks and explain that doing a new task will mean another will fall down the task list as you can’t do both.
Clear boundary structures will allow for less infractions on your boundaries so your boundaries need to be strong, and you will need to ensure they are solid.
Have a game plan on how to respond to those instances when someone will cross your boundaries.
Many people fear that if they begin setting boundaries for themselves, people will see them as not being a team player, being rude, selfish, and not doing your job. You worry about the potential repercussions of saying “no” to certain tasks and requests. But, if something is outside your scope of expertise, this is when you need to say “no” and delegate that task to someone who is more adept at the work.
“No” is a full sentence and doesn’t need an explanation. Decide who needs an explanation. It’s tough and you may worry about how you will be perceived, but if you say “yes” when you want to say “no”, people will keep asking. It will take time and practice but remain firm in your stance and make sure those lines do not become blurred.
We are not robots that can work and work without breaking down. Even robots need regular maintenance to function. Likewise, take leave and time off when you need it. You’re entitled to take leave and have earned it. Make time for self-care. Take time off. Enjoy it. And set that out-of-office message and enjoy time away from work. Trust us, the building will still be standing when you come back.
Remember, boundaries are important and there isn’t anything unusual about having them and doing what you need to do to ensure they aren’t stepped on.
Want To Work In Data Analytics? Here’s How To Break Into The Field
Nearly every industry utilizes data in some capacity, which is why there’s such a high demand for data science professionals. With mind-boggling amounts of data at our disposal, the world needs folks who can make sense of all the stats and figures.
One in-demand career in data science is a Data Analyst, someone who uncovers what’s happening behind the numbers, and answers questions with data. Data Analysts use programming languages and other tools to work with large amounts of data and communicate their findings — and you might have exactly the skills and traits you need to enter the field.
Codecademy’s data science career paths are an awesome place to start if your ultimate goal is to get a job. We’ll guide you through all of the technical skills that specialists in these professions use, plus give you practice projects that you can use to build a professional portfolio.
The newest career path, Business Intelligence Data Analyst, is the quickest way to learn the data analytics skills necessary to get a job in the field. It’s tailored for beginners, and you’ll learn how to code like a Data Analyst with SQL and Python. So if you haven’t taken a math class in years or have never written a line of code, we’ve got you covered.
The role of a Data Analyst
You can’t always tell what a person does all day based on their job title alone — and that’s definitely true in the data science domain. For example, a Data Scientist and a Data Analyst are technically different jobs, though the terms are often used interchangeably. While a Data Scientist is an umbrella term that could refer to careers like a Machine Learning Specialist or Inference Specialist, a Data Analyst focuses on answering questions using data. (BTW, if you’re interested in pursuing those other data science specialties, we have career paths that will walk you through step-by-step how to become one.)
A Business Intelligence Data Analyst, for example, uses statistics and analytics to write reports and build dashboards so that organizations can turn data into actionable insights. In today’s data-driven world, every kind of business needs BI Data Analysts who are experts at taking huge amounts of data, investigating it for trends, and telling a meaningful story that informs business decisions.
Compared to other data science roles, BI Data Analysts typically don’t need as much programming experience. But there are still some key coding and technical skills that you need to have in order to collect, manipulate, analyze, and interpret data:
- SQL: Short for “Structured Query Language,” SQL is a standard database management language that’s used to query and manipulate data in relational databases like spreadsheets.
- Python: With Python’s built-in modules and libraries (like Pandas and MatPlotLib), BI Data Analysts can use the general-purpose programming language to analyze and visualize data.
- Microsoft Excel: Business and spreadsheets go together like PB&J. As a BI Data Analyst, you’ll need to know how to seamlessly load data into Microsoft Excel and use it to answer numerical questions.
- Tableau: “The business world is run on dashboards,” Michelle says. You should know how to use Tableau, the data visualization software that’s standard in business intelligence. Knowing how to compose a Tableau dashboard that tells a clear, coherent story is a must-have for BI Data Analysts, she says.
You’ll learn how (and when) to use all of these data analytics tools in the BI Data Analyst Career Path. If you’re starting from scratch, or have never been super comfortable with math and numbers, don’t stress: We’ll guide you through everything you need to know to use these programming languages and tools.
3 traits that make successful Data Analysts
Here are some personality traits and soft skills that will help you shine as a Data Analyst.
Domain knowledge
Good news for career-switchers: Your past work experience and domain knowledge is your secret weapon when you’re trying to land a BI Data Analyst job, because you’ll be able to contextualize even further what data means to a business, Michelle says.
For example, if you worked in restaurants for 15 years, you know how a restaurant operates, what makes restaurants successful, and what different data points represent in food service. Your domain knowledge would give you an edge if you were applying to a job as a BI Data Analyst in restaurants, because you “understand the relationship between the numbers on the page and the real-world values,” Michelle says.
So whether you have experience in the arts, medicine, engineering, food service, education — you name it, your past jobs or passions could serve you in a BI Data Analyst role.
Clear communication
Being able to translate complicated data topics into a clear story that makes sense to a wide range of audiences is a huge asset for BI Data Analysts. For example, a BI Data Analyst might have to share their findings with non-technical departments that may not be fluent in data vocab and concepts. On top of that, you have to know what the most relevant information is for a particular group; you wouldn’t talk to the company’s leadership team about data the same way you would your peers, for instance, Michelle says.
Most of us have practice tailoring our communication to different audiences within the workplace, Michelle says. “Those soft skills are immediately transferable,” she says.
Curiosity
The most important soft skill for a BI Data Analyst to have is curiosity and enthusiasm to ask questions, Michelle says. It’s one thing for a BI Data Analyst to create a data summary or pull performance numbers for a company — that’s all part of the job. But a really successful BI Data Analyst will take it a step further by segmenting data in different ways, asking questions about what the data really means, and considering alternative data stories that could come out of data.
Curiosity is also what makes the job exciting, Michelle says. “You’re always asking and answering questions, and that feels empowering,” she says. “The ability to take a bunch of observations [and] a dataset and turn it into something that’s actionable — that feels good.”
What to expect when you apply to a Data Analyst job
Ready to start job-hunting? Before you apply, you’ll need to prepare a Data Analyst resume that includes your technical skills, past work experience, relevant courses you’ve taken, and data science projects you’ve completed. Don’t forget to read the job description closely and see what the required technologies and tools are so you can list the ones you know on your resume. It also helps to take the extra time to write a Data Analyst cover letter — not only will a cover letter showcase your communication and storytelling abilities, but it also is your chance to express why you’re the best candidate for the role.
Along with your resume and cover letter, you’ll be expected to provide a portfolio of Data Analyst projects you’ve completed. Your portfolio is your opportunity to provide tangible proof of all of your skills and accomplishments. If this is your first time applying to a Data Analyst job, you can absolutely use Codecademy projects in your portfolio. In Codecademy’s BI Data Analyst Career Path, you’ll get to complete four projects that you can use in your Data Analyst portfolio, and we also have lots of other data analysis projects you can complete and add to your portfolio.
Making it to the interview is a super exciting, but sometimes intimidating, stage of a job application. As part of a Data Analyst job interview, you’ll probably have to complete a technical interview where you’ll be asked to solve a data problem using code. It sounds nerve-wracking, but the most important thing to remember is that interviewers want to see how you’d approach solving the problem, not necessarily the exact right answer. Hot tip: Start practicing for your technical interviews by reviewing these common interview questions for Python and SQL, and complete these Python and SQL code challenges.
Beyond that, you might be asked to answer open-ended questions about common data concepts and how you’ve applied them in the past. The hiring manager will also ask you behavioral questions about why you want to become a Data Analyst, how you handle problem-solving, and what interests you about the organization. Be sure to read this blog about common data scientist job interview questions to get familiar with the relevant behavioral and technical questions you might face.
Start your journey to becoming a Data Analyst
Feeling inspired about the career possibilities within data science? Get started today with Codecademy’s new BI Data Analyst Career Path — it’s the fastest way to jumpstart a career in data analytics. You’ll learn the coding concepts and tools that BI Data Analysts use in their jobs, and get hands-on practice creating portfolio-ready projects with Python, Excel, and Tableau.
As you’re thinking about your next career move, be sure to check out these blogs for tips on what to include on your Data Analyst resume, how to build a Data Analyst portfolio, and common Data Analyst questions you’ll be asked in a job interview.
The Fastest Way To Learn Data Analysis — Even If You’re Not A “Numbers Person”
If you still get anxious thinking about math quizzes and stay far away from numbers-heavy fields, then data analytics might seem way out of your comfort zone. But here’s the thing your math teachers probably never told you: You don’t have to be a math whiz or a “numbers person” to work with data.
Data analytics is all about the process of collecting and analyzing data for insights. A Data Analyst often works with numerical data and stats, but that doesn’t mean they’re doing complicated arithmetic in their head. “In fact, you’ll come to find that a lot of data science is situating numbers in their context,” explains Michelle McSweeney, Codecademy’s Data Science Domain Manager. A Business Intelligence (BI) Data Analyst, for example, is someone who uses statistics and analytics to write reports and build dashboards that help organizations turn data into actionable insights.
In other words, a Data Analyst’s job is to figure out the story behind the numbers, and then use those numbers to answer questions.
BI Data Analysts have to be able to interpret and contextualize numbers so that a wide range of audiences and stakeholders can understand what they mean. This requires a high level of data literacy — a term which may sound intimidating, but just refers to an ability to read, understand, and leverage data. “Numbers without a story don’t tell us much,” Michelle says. “So if you consider yourself a ‘words person,’ you are probably in the right place, because the best analysts turn numbers into insights and stories.”
Think you may want to work with data? The good news is that nearly every industry uses data to deliver business insights and inform decisions. And if you want to get started right away, Codecademy’s new BI Data Analyst Career Path is the quickest (and lowest code!) route to a career in data analytics. You’ll dive into the types and quality of data, and why human oversight and critical consideration is essential in the world of data. Plus, we’ll teach you how to use the technical tools and programming languages that BI Data Analysts use. By the end, you’ll be ready for an entry-level job in the field.
Most importantly, the BI Data Analyst Career Path is made for those of us who are not “numbers people,” and we’ll guide you through everything you need to know in a practical, data-first way, Michelle says.
While BI Data Analysts may not be doing math on the regular, they do need to understand some programming in order to work efficiently with data. Here are the various programming languages and technical tools that you’ll learn to use in the BI Data Analyst Career Path.
SQL
SQL is a programming language that’s designed for managing and querying data stored in relational databases. SQL is often recommended to coding beginners because it has a very readable, English-like syntax. Even newbie programmers who’ve never written code could probably tell what a snippet of SQL code does just by reading it.
For example, this is some SQL code for a movie database that you’ll work with in this Career Path:
SELECT *
FROM movies
WHERE year BETWEEN 1980 AND 1990;In the BI Data Analyst Career Path, you’ll learn how to use SQL to query and manipulate data. Don’t stress if you’ve never taken a SQL course before — our path is beginner-friendly, and we’ll cover everything from the fundamentals of the language to advanced SQL techniques that are used to solve business problems.
Python
Python is a wildly popular data science programming language with a concise and intuitive syntax. The cool thing about Python is that there are tons of libraries and built-in functions that enable you to write code quickly and easily. In Codecademy’s BI Data Analyst Career Path, you’ll use data science tools like Python Pandas, seaborn, and MatPlotLib to manipulate data and create compelling data visualizations.
Be sure to check out all of Codecademy’s Python courses to see what else you can do with this versatile programming language.
Excel
The spreadsheet software Microsoft Excel is used to store, display, and analyze data. There are lots of useful built-in Excel functions that allow you to complete basic computations with numerical data, like finding averages, sums, or maximum and minimum values. In the BI Data Analyst Career Path you’ll learn the basics of handling, analyzing, and visualizing data in Excel, plus work on data analysis projects using real-world datasets.
If you’re just looking to get better at using Excel, you can take the free Codecademy course Learn Microsoft Excel for Data Analysis to brush up on Excel’s filtering tools and formulas that are used in data analysis.
Tableau
Tableau is the go-to visual analytics platform in business intelligence. The user-friendly application enables you to build attractive, interactive visualizations and dashboards that tell a story with data. We’ll teach you how to use Tableau to import, manage, and visualize data in the BI Data Analyst Career Path. You can also check out the free course Learn Tableau for Data Visualization, to get more practice building Tableau dashboards.
Get started becoming a BI Data Analyst
To reiterate: You don’t need to be good at math in order to become a BI Data Analyst. However, there are some important data-specific skills you should have under your belt, like knowing how to get around a dataset, assess the quality and completeness of data, and join data together, Michelle says.
A good BI Data Analyst is someone who’s curious and open to asking questions about data and exploring what the numbers in a dataset really mean, Michelle says. “You might be surprised how much of your job will be just cleaning, joining, and exploring data to discover the most interesting bits,” she says.
Think you could have a career as a BI Data Analyst? Jump in right now and start the BI Data Analyst Career Path — it’s the quickest way to launch a rewarding and lucrative career in data analytics.
One last thing: While you’ll be writing code in the BI Data Analyst Career Path, the lessons are designed for beginners, so truly anyone interested in becoming a data professional can take it. By the end of this path, you’ll understand how and when to use industry-standard data analytics tools like Python, SQL, Tableau, and Microsoft Excel to answer business questions with data. You’ll even get to complete projects that you can use in a portfolio when it comes time to apply for jobs.
As you work through the BI Data Analyst Career Path, be sure to connect with your fellow learners and job seekers through Codecademy forums. Who knows? Maybe you’ll discover you’re a “numbers person” after all.
BI Data Analyst | Codecademy
If you want to get started working with data as quickly as possible, this path is for you. With business intelligence (BI) data analytics, you will dive in to working with data leveraging tools like Excel and Tableau as well as Python and SQL. By focusing on generating reports and driving insights,…
5 Entry-Level Data Analytics Jobs & How To Get Them
When you’re applying for your first job in tech, it can be intimidating and even discouraging to read the years of required work experience that are listed in job descriptions. After all, the only way to get work experience is by, well, working. Fortunately there are lots of entry-level tech jobs you can get with no experience, even within in-demand fields like data analytics.
Data Analysts are one of the most in-demand positions in tech; in fact, the Bureau of Labor Statistics forecasts that Data Scientist and Statistician will be some of the fastest-growing occupations over the next decade. As companies embrace digital technologies, they create more and more data that can be used to leverage business decisions. Organizations need Data Analysts who understand how to put data to work.
Wondering where you should start? With Codecademy’s beginner-friendly Data Science career paths, you can focus on learning the skills you need to get a job. The newest career path, Business Intelligence Data Analyst, is designed for absolute beginners and is the quickest, lowest-code way to get a job in tech. By the end of the path, you’ll be proficient in all of the technical tools that a BI Data Analyst uses, and be ready to apply for an entry-level position.
Read on to learn more about the roles that will help you break into data science, plus the technical skills you need to get hired and start gaining valuable work experience.
Business Intelligence Data Analyst
One of the quickest ways to launch a career in data is by becoming a Business Intelligence (BI) Data Analyst, which is a data professional who turns data into insights for an organization. A BI Data Analyst needs to know some programming with Python and SQL, plus be proficient in tools like Microsoft Excel and Tableau. They use these technologies to analyze data, write reports, and build dashboards that communicate their findings.
If you think this is the career for you, consider starting the BI Data Analyst Career Path today. We’ll walk you through everything you need to know — from basic statistics to SQL — to master data analysis. You’ll get hands-on practice cleaning, manipulating, and visualizing data with Python Pandas and MatPlotLib, and we’ll help you create a BI Data Analyst portfolio that you can use in job interviews. This path is beginner-friendly and you don’t have to be good at math or a “numbers person” to understand these skills.
Quality Assurance Data Analyst
You might’ve heard the saying, “garbage in, garbage out” before in data science. Basically, it means that data analysis is only as good as the data being used, and even the most advanced data algorithms are useless without quality data. A Quality Assurance (QA) Data Analyst is responsible for monitoring the quality of data that an organization uses. For example, they would be cleaning up messy data so it’s accurate and complete and validating data, which means checking that data actually measures what we think it is measuring.
You’ll learn all about how to clean and validate data and why it’s so important in the BI Data Analyst Career Path. If you want to take a closer look at the data-cleaning methods that Data Analysts use, you could also check out our courses How To Clean Data With Python and Handling Missing Data.
Data Steward
A Data Steward (sometimes called a Data Custodian) is another role that’s concerned with data quality and data governance, which Google Cloud defines as all of the steps that an organization takes to “ensure data is secure, private, accurate, available, and usable.”
Data Stewards ensure that members of an organization follow internal standards and processes for data collection, management, and analysis. In the new BI Data Analyst Career Path, you’ll learn all about the ethical considerations of data collection and how to apply the principles to your work.
Consumer Insights Analyst
Lots of companies turn to data analysis to better understand their consumers and clients. A Consumer Insights Analyst gathers data about consumer behaviors through a variety of research methods, and analyzes it to find potential shortcomings or opportunities for businesses to improve their relationship with consumers.
Consumer Insights Analysts typically use programming languages like SQL to query and join data, and may use BI tools like Tableau to create reports and dashboards. (BTW, we have a free course Learn Tableau for Data Visualization that will teach you the basics of data setup in Tableau.) Being able to tell a clear story with complicated data is key, because a Consumer Insights Analyst works closely with non-technical teams (like marketing) to develop strategies based on trends in data.
Junior Data Analyst
Taking an entry-level junior position is one way to gain on-the-job experience that you’ll need in order to get in the door. For example, a Junior Data Analyst typically works closely assisting Data Analysts and gets an inside look into how data influences business decisions. To learn more about how to make the leap from an apprentice, intern, or other junior position to a full-time employee, check out this blog post of tips from people who’ve done it.
These are just some of the exciting jobs you can get when you’re starting out as a data professional. Be sure to check out the rest of Codecademy’s career paths and courses in data science — they’re all self-guided, so you can stop and start whenever you need and work at the pace that’s right for you. And when it comes time to start submitting job applications, we have tons of resources, portfolio projects, and interview tips that will help you feel confident landing that position.
BI Data Analyst | Codecademy
If you want to get started working with data as quickly as possible, this path is for you. With business intelligence (BI) data analytics, you will dive in to working with data leveraging tools like Excel and Tableau as well as Python and SQL. By focusing on generating reports and driving insights,…
Learn How To Become a Business Intelligence Analyst In Our New Career Path
Looking for the fastest route to a career as a Data Analyst?
Data jobs have been a hot topic for years, but not every company needs PhD-level expertise in machine learning or NLP. What businesses do need, according to Codecademy Data Science Domain Manager Michelle McSweeney, are people that can process large amounts of data to find insights that can help inform strategy and find new opportunities.
That’s why business analytics is booming — nearly every industry utilizes data to uncover insights and help make decisions. Business Intelligence (BI) Analysts can do everything from help marketing teams monitor and fine-tune their campaigns, work with sales and tech teams to find the underlying reasons behind a product’s success, and even partner with law enforcement to detect patterns and trends to help mitigate crime.
Another great aspect of BI is that there’s a low barrier to entry to all of those promising career opportunities — with the right training, you can become a BI Analyst in just a few months. Want to learn how? Check out our new Business Intelligence Data Analyst career path.
Who is the new path right for?
If you’re looking for the quickest path to becoming a Data Analyst, this path is for you. You can be ready to start applying to jobs within three months if you stay focused and committed to your learning, Michelle says.
But how do you know if BI is right for you?
If you’re naturally inquisitive and enjoy finding the answers to problems, that’s a good sign. Curiosity is the most valuable skill in any data profession, but especially BI. “Taking a bunch of observations from a dataset and turning it into something actionable feels empowering,” Michelle says. “But you need to be curious about looking in other areas and segmenting data in different ways. If you look at the data differently, does it tell a different story?”
It can also be a great choice if you’re considering changing careers but want to stay in the same industry. According to Michelle, your past knowledge and expertise can provide a unique perspective into your new role. “The combination of domain knowledge and the tools you’ll learn in this career path to really work with data is invaluable,” Michelle says. Not only will you know which questions to ask and where to look to find answers, but you’ll also have a better understanding of the real-world values of the numbers on the page. Plus, your communication and collaboration skills will help you work with different departments and tailor your messages for different audiences.
What’s more: Business intelligence is a promising field with tons of room for growth. “There are many career paths with this foundation, and learning these skills gives you an opportunity to branch out and grow in different ways,” Michelle says. You could utilize your insights from past experiences to pursue a job as an Analytics Manager or even keep building your analytics skills to become a Data Scientist.
And if you don’t consider yourself a “numbers person,” rest assured that you don’t need to be a math whiz to be a BI Data Analyst. “Analytics” might sound like it involves a lot of number-crunching, but Michelle explains that it’s more about understanding how to look at data and then telling the story behind those numbers.
What will you learn from the new career path?
Our new Business Intelligence Data Analyst career path will equip you with all the skills you’ll need to land an entry-level position in the field. You’ll learn how to use SQL and Python to manipulate and visualize data, and we’ll also show you how to use Excel and Tableau — two popular BI tools — to create clear and effective dashboards and reports. “The business world runs on dashboards, and composing a dashboard that tells a really clear, coherent story is an invaluable skill,” Michelle says.
After completing the path, you’ll be able to:
- Query and manage databases with SQL
- Use basic statistics to draw conclusions from datasets
- Create data visualizations with Tableau
- Clean and validate data
- Generate reports with data-driven explanations
- Clean, manipulate, analyze, and visualize data with Python and the pandas and matplotlib libraries to generate meaningful insights and reports
And as you complete the path, you’ll use these skills to build personalized projects that you can use to build a portfolio to share with hiring managers when you’re looking for a job. We’ll also help you prepare for the job hunt with advice from technical recruiters, interview prep courses, and other useful resources you can find in our Career Center.
Ready to jump into the world of data? Check out our BI Data Analyst career path!
How Max Used Online Learning to Shorten His Journey to a UX Career
Meet Max, who’s #LearningFrom a small town in Germany! Max has always dreamed of becoming a UX designer, but had limited access to traditional forms of education given his remote location. Read on to discover how Max made his dreams come true from home.
When I turned 18, I knew I wanted to pursue a career in UX design, but living in a small town with no nearby universities made that difficult. Instead of attending a traditional university, I looked for alternative education options. After doing some research online, I stumbled on Coursera. I first enrolled in the Google UX Design Professional Certificate, and it was a great experience for me. The content was structured and supported by many illustrations and real-world examples.
Through the Google UX Design Professional Certificate program, I learned new technical skills like prototyping, wireframing, and conducting UX research. After building my skills, I gained the confidence to apply for jobs in the field. I’m excited to share that I landed a UX design contract role at a Decentralized Autonomous Organization (DAO). I have also recently enrolled in the new Meta Front-End Developer Professional Certificate to continue upskilling. Learning is a never-ending cycle, so this is just the beginning!
I have now started my own online portfolio where I share examples of my projects at DAO in the hopes that it will help and inspire other learners like me.
Next, I am looking to turn some of my ideas and prototypes from the last few months into full-fledged products. Many thanks to all the lecturers and the entire Google UX team for the structured content and helpful guidance during the course.
For new learners who are living in an area with limited access to education, I would recommend that you consider learning from home with Coursera. I can tell you that it was absolutely worth it. This course gives me hope for my future and career, and most importantly, it has given me self confidence. That is priceless.
If you’d like to learn more about our distance learning programs, check out our website today.
