Looking for some advice to build a data science portfolio that will put you ahead of other aspiring data scientists? Don’t miss these useful tips. Why Have a Portfolio at All? Even though the demand for data scientists is high, the competition for entry-level positions in this field is tough. It should come as no surprise that companies prefer to hire people with at least some real-world experience in data science.
When you already have some experience with Python, building your own portfolio of data science projects is the best way to showcase your skills to potential employers. But where do you begin with developing your very first Python project? First, Why Develop a Data Science Project? There are a number of career development benefits to creating your own data science project in a language such as Python: Studying.
Python is a simple yet powerful programming language that’s a must for beginners and advanced programmers alike. Here’s why. High-level programming languages have one goal in mind: to make your life as a programmer easier. Messy syntax and obscure keywords? Forget about it. With languages like Python, you can get away with understanding just the basics of programming, enough to begin writing your own scripts and apps. And since Python developers are high in demand, Python is a great language to learn if you want to pursue a career in software development or big data.
There I was—at Nvidia Deep learning & AI, the most prestigious deep learning event, waiting for my hands-on training to begin. It felt great to be there! But as I waited for things to start, observing the others who sat around me, I realized something: most of the attendants were men! In a crowded hall where around 200 people were waiting for a lecture, less than 10% were women. Where were the rest, and why was I one of the few female representatives who attended this conference?
Knowing how to improve SQL query performance is an important skill, especially when working with with large databases. In this article, you’ll learn how to write more efficient SQL queries to get results faster. The biggest difference between SQL and other languages is that SQL is a non-procedural language. In a non-procedural language you specify the results that you need but not the methods used to get it. The advantage of a non-procedural language is that it is easier to write programs, therefore it is common for non-programmer business users to generate reports from SQL queries.
Looking for a data science job? Then you’ve probably noticed that most positions require applicants to have some level of Python programming skills. But how are they going to test this? What are they going to ask? Let’s prepare you for some interview questions! Why Do Data Scientists Need Python? Data science goes beyond simple data analysis and requires that you be able to work with more advanced tools. Thus, if you work with big data and need to perform complex computations or create aesthetically pleasing and interactive plots, Python is one of the most efficient solutions out there.
So, you’ve finally landed your first technical job? Congrats! But you go to the office and find that there are millions of things to memorize, tons of command-line magic to perform, and strange jargon being thrown around among your team members that you simply can’t keep up with… How do you manage all of this without going crazy? Of course, your hard skills count the most, but you’ll need more than that to be really good at what you’ll be doing.
In this comprehensive beginner’s guide, we’ll look at how to install Python on three major operating systems, choose a Python IDE, and run your code. Would you like to start coding in Python but don’t know where to begin? Maybe you’ve graduated from an online course like Python Basics and now are looking to continue your Python adventure on your own machine. But first, why Python? The answer is simple: Python is a very easy-to-learn and powerful programming language.
An increasing number of fintech companies are using Python for data analysis. But what makes Python so special? And why is it a better language for data analysis compared to traditional software? Python is quickly becoming the most popular coding language in the world. Currently, it’s perching comfortably in the fourth spot after Java, C, and C++ on the Tiobe Index of Language Popularity. And the Popularity of Programming Language Index ranks Python as the most popular programming language in the world in October 2018.
Installing database software like PostgreSQL, Oracle, or SQL Server can seem like a complicated task, but it really isn’t! These days, most relational database management systems come with installation wizards that make the process much simpler. In this article, we’ll look at how to install PostgreSQL and test that the installation is working. Overview: PostgreSQL Installation Steps We’ll complete the following tasks: Downloading the PostgreSQL package. Installing and configuring PostgreSQL.
Being data-driven is a must for companies these days. If you think differently, you might as well pack it in now. Here’s why. Companies are always trying to outdistance each other, winning more clients and gaining the most profit. They burn a lot of time in building strategies and working on tactics, but their actions may not bring the expected results. Why not? Because they don’t start with data.
Who do you think is the naughtiest character in South Park? You’ll know the answer by the end of this article—and I’m sure you’ll be surprised! In the previous article of this series, I showed you how to use R to analyze South Park dialog. We mostly focused on the show overall. This time, I’ll take a closer look at the most famous South Park characters. We’ll see how much they talk and how their sentiments change across the show.
Python is a programming language frequently used by scientists and data analysts to build applications. Why? Because it’s easy to use and has few rules. But simply installing Python isn’t enough—you also need a good interactive development environment (IDE) to program in. So what are the best Python IDEs for data science? Let’s find out! (Note: all IDEs presented here support Windows, macOS, and Linux.) 1. Enthought Canopy Enthought Canopy is one of the best Python IDEs for scientists and engineers.
Halloween is not only the spookiest day of the year but also a great opportunity for some good old-fashioned pranking! We’re self-proclaimed pranksters, true, but this time you’re lucky. We’re out for a party, so you won’t be getting tricked today—sorry to disappoint 🙂 In any case, we hope to see you next time you decide to learn data science. Have a happy Halloween!
Buy courses individually or in packs! Find out what courses are in each course bundle and learn the skills you need. For the first time in the history of Vertabelo Academy, you can get them with 70% discount! At Vertabelo Academy, you can buy courses individually or in bundles. Bundles, to put it simply, are packs of courses that teach you one technology (e.g., SQL) or one particular topic (e.
How much SQL do you know? Test your knowledge with this spooky crossword to find out! Contest Rules Downloadthe Vertabelo Academy SQL crossword. Solve tasks and unlock the secret solution. Send your answerto email@example.com before 👉 November 1, 2018. Wait for the prize to be drawn and, if you’re lucky, win a course 💜 One lucky winner will be drawn among the users who send us the correct solution, and they’ll be contacted by email within 7 days of the contest closing.
Heat maps are a great way to visualize patterns in data, but some businesses avoid them because creating them seems challenging and time consuming. Well, it’s not. Do you know what the most popular programming language currently is? According to the PYPL Index, it’s—you guessed it—Python. And our serpentine friend was also crowned the best programming language in 2018 by Linux Journal readers. Why all the buzz? Because Python is simple and easy to learn.
Share a pic of your DIY jack-o’-lantern or halloween costume to win a spooky prize. Halloween is upon us! And there’s lots of costume parties and trick-or-treating to be had. But if you’d just like to chill at home, we invite you to join us in our online festivities—and possibly even win a course bundle of your choice! This Halloween season, Vertabelo Academy is hosting a jack-o’-lantern and costume contest.
Visualizing data using mediums like graphs, charts, and diagrams allows businesses to make better sense of the massive amounts of information they receive. Rather than disseminating sheets of data in number form, visual depictions allow you to more quickly and intuitively convey ideas and concepts to your team. Stephen Brobst, CTO of Teradata, tells us: “Seventy percent of the sense receptors are in the eyeball. Nothing is as powerful as visualizing data.
Technologies are constantly developing, and so is the labor market. Here are some tech jobs born in the 21st century. I vaguely remember a time when people in public transport read books, talked with each other, or simply looked at the scenery rolling past their windows. Now, we’re all occupied with our mobile phones. It’s no surprise, really—with smartphones, we can do almost everything: chatting, shopping, working, watching TV series, learning, and much more.
Typical business users make decisions based on gut feelings, but this can’t get them so far. In this article, we’ll look at how learning to write basic SQL queries helps your company become a data-driven organization. Businesses face many decisions. Do we increase our advertising budget in one region or the other? Are certain products selling quickly enough? What we should do if they aren’t? Most of these decisions are driven by intuition, but organizations that make the most business impact use data-driven decision-making.
Microsoft SQL Server is one of the most popular professional database servers on the market. In this guide, we’ll help you install SQL Server on the Windows operating system together with SQL Management Studio. How to Install SQL Server 2017 We’ll install SQL Server 2017 in this guide. You can download it for Windows and Linux, but you can’t install Microsoft SQL Management Studio on Linux at the moment, so we recommend you stick to Windows.
Data Scienceand Big Data are the biggest industry buzzwords in 2018. Experts believe that artificial intelligence (AI) systems will continue to reign supreme in the technology marathon through 2019. “More than 40 percent of data science tasks will be automated by 2020.” –Gartner The data science trends for 2019 are essentially a continuation of some of the key trends of 2018, including areas such as: Machine learning (ML) Artificial intelligence (AI) Big data Edge computing Blockchain Digital twins Serverless computing Because data science is so vast and challenging to navigate, we’ve compiled a list of the most popular data science articles that dominated the industry over the past 12 months.
In this article, I’ll help you write and execute your first SQL query. Let’s jump right in! Running an SQL query for the first time is not a complex task, but it can seem intimidating at first if you’re a complete beginner. But once you get past that initial roadblock, you’ll be able to focus on learning SQL and writing more interesting queries to meet your business needs. The Ingredients You’ll need these three things to run an SQL query:
R is an extremely powerful and lucrative language for data science, and as of 2018, it’s one of the most popular programming language choices for data science professionals. R is an open-source programming language that’s widely used by data miners, statisticians, and data scientists to perform statistical computing as well as data analysis. Given R’s increasing popularity, R professionals are faced with plenty of career options and future possibilities.
Have you ever liked a TV show so much that simply watching it wasn’t enough anymore? Read on to discover how I used R to analyze South Park dialog and ratings! South Parkis an American TV show for adults that’s well known for being very satirical—the series has made fun of nearly every celebrity and isn’t afraid to be provocative. I literally watch the show every day. I also do lots of data analysis in R every day!
Information technology is one of the hottest industries in the world and offers thousands of job in each major city around the globe. If you’re a student or professional who wants to get IT skills and find your first job in the industry, Vertabelo Academy can help you get started. The range of IT jobs available is stunning—from software engineers to system administrators and data scientists, IT rules the job market.
The Vertabelo Academy Team has been working hard to release a brand-new course, and it’s finally here! Python Basics for Programming is a great place to start for anyone aspiring to become a software developer. Since our SQL courses, the Vertabelo Academy platform has been embraced by thousands of students who are eager to learn new technologies. After releasing Intro to Python for Data Science last month, we asked ourselves: why not create another introductory Python course, but this time from a software developer’s perspective?
Unfortunately, data isn’t always available in the exact structure you prefer. And there’s nothing more frustrating than having inconsistent, untidy data that produces biased results. Let’s take a look at how the Tidyverse can help. What is Tidyverse? Before you can conduct any analyses or draw any conclusions, you often need to reorganize your data. The Tidyverse is a collection of R packages built around the basic concept that data in a table should have one observation per row, one variable per column, and only one value per cell.
How much SQL do you know? Test your knowledge with this crossword to find out! Contest Rules Download Vertabelo Academy SQL crossword. Solve tasks and unlock its solution. Send your answer at firstname.lastname@example.org before👉 September 8, 2018. Wait and win a special prize 💜 Prizes will be drawn among the users who will send us the correct solution. Then winners will be contacted by email within 7 days from contest closing.
One of the oldest jokes in the business world goes like this: The CFO asked the CEO, “What happens if we invest in developing people and they leave us?” The CEO answered, “What happens if we don’t and they stay?” If you’re like the CEO and want to help your employees grow, this article will explain how you can do so with Vertabelo Academy. Vertabelo Academy has been around since 2015.
IT-related careers are some of the hottest in the industry, as they boast high wages and increasing demand. Have you ever considered learning to code but felt it’s impossible because you chose to study non-technical subjects? Think again—it’s actually never too late to learn how to code. Are you sure you want to do this? Currently, a computer science degree is not necessarily required to find a job in IT.
Indexes are one of the most misused and misunderstood entities in physical database design. A good understanding of indexes and how they solve database performance problems is necessary for any database novice. In this article, we’ll look at basic database indexes and their role in database development. To picture what an index is, consider a textbook. At the end of most textbooks is an index listing all the terms one can find in the text and the pages on which they appear.
Which influential data scientists are leading the charge? To help you keep up with the latest data science trends, we’ve compiled a list of the top data science and big data experts worth following. Putting Your Data to Work! Data science has long been a driving force in modern business, but even more so now with the wealth of data at our fingertips. Data is everywhere, thus, we need to learn how to make the most of it and get ahead in business.
Over the past three months, we’ve been working on something completely new. Please welcome our new course on Python data analysis! We got many emails from users like you with good feedback on our Introduction to R course. So first, I want to start off with a big thank you—reading your wonderful comments was like a burst of energy! We’re always looking to improve our offerings, and we greatly value your input.
Three years or three months? With all the 12-week bootcamps and coding schools out there, three years sound like a joke. “Enroll in our course today, and become an expert programmer!” “Start learning to code and jumpstart your programming career immediately!” Most probably, you’ve heard lots of claims like these if you’re interested in coding. Are they reassuring? Maybe. Frustrating? Sometimes. If you’ve been learning for a year and still feel like a newbie programmer while others are starting their careers in three months, you start to wonder: What’s wrong with me?
SQL wildcard allows us to filter data matching certain patterns in SQL. We use wildcards with the LIKE operator in the WHERE clause of an SQL query to filter data. In this beginner’s article, we’ll look at everything you need to know about basic SQL wildcards. If you like playing cards, then you know that wildcards can substitute any other card in your deck. Similarly, wildcards in SQL strings can substitute one or more characters.
If you plan to learn SQL online but aren’t sure where to start, you’re in the right place. I evaluated the top 7 ranked SQL online courses to help you find the right solution. While summer’s a great time to relax and get away from work, it’s also an excellent opportunity to learn new skills—like SQL! Thanks to online schools, learning new tech skills is super easy, and you can choose from a variety of formats to suit your needs, like courses and tutorials.
Sometimes, SQL queries return lots of data you don’t need. In this article, we’ll look at a simple example of filtering SQL queries to reduce the complexity of your data. The key to learning how to filter data in SQL is understanding the very basics of Boolean algebra. That’s just a fancy term mathematicians use to describe expressions involving logical values (true/false) and their associated operators (and, or, not, etc.
R and Python are two of the most popular data science languages, but which one is better? And will Python replace R in the near future? Let’s find out! R vs. Python: the Basics First, some history. R first appeared in 1990; it was derived from the language S, a statistical programming language developed for statisticians. It was (and still is) commonly used in educational settings and is a favorite among biostatisticians.
Think summer is reserved for flying to warm places and hanging out at the beach? Sure! But it’s also a great time to learn new skills that you haven’t had time for. If you recently graduated from high school and want to get a head start on computer programming for college, learning SQL over the summer is a great opportunity. You have nothing to lose and everything to gain—SQL is actually really easy to learn, especially with so much free time over the summer.
Programmers commonly have many questions about R, a popular programming language in data science and analysis. R is used all over the world by professionals in the fields of data science, data visualization, data mining, and statistical analysis. But what exactly is R? Where did it come from? And why is it being used specifically by data science professionals? This article attempts to answer all these questions, including the most important of them all: Should you be learning R as well?
Why is June 21 the official start of summer? Let’s see how SQL can help us answer this question. The Summer Solstice Officially, June 21 is recognized as the summer solstice, the longest day of the entire year in terms of daylight. Why? Because on this day, the sun rises early and sets quite late. People in the Northern Hemisphere celebrate the summer solstice with feasts, bonfires, picnics, and traditional dances and songs.
In my previous articles, I explained how you can check for associations between two continuous and two discrete variables. This time, we’ll check for linear dependencies between continuous and discrete variables. You can do this by measuring the variance between the means of the continuous variable and different groups of the discrete variable. The null hypothesis here is that all variances between the means are a result of the variance within each group.
Have you ever wondered how you can deal with an overwhelming amount of data? How do you use it? How do you understand what it’s saying? And last but not least, how do you present your data to the world such that everyone understands your point? In this article, we’ll explore these questions to understand the importance of data visualization. Where are the data? When I want someone to understand my perspective, I try to visualize it precisely so I can communicate my thoughts.
Going from zero to one can be daunting in any endeavor. The same is true for learning new programming languages, even simple ones like SQL. In this article, we’ll take a look at some key insights that will help you understand the nuances of SQL queries. If you’ve never used SQL, you’re in the right place. When learning anything new, you’ll find that there are always some key insights or tips that can help you on your way.
As SQL users, we usually focus on writing queries that return correct results. However, there are more things to consider when you’re writing a query; one of them is query performance. In this article, we’ll look at some examples where query response time is critical. Scene One: 911 Call Center Let’s suppose we’re at a 911 call center, when the phone rings. One of the operators answers the call; a witness reports that a man has been shot.
Data science professionals frequently coordinate their workloads, host meetings to discuss and share ideas, and collaborate to solve problems. But all it takes for things to fall apart is a lack of clear communication. Data Science is a team sport that involves a variety of professionals working together to solve technological problems. However, you need good communication for your team to run like a well-oiled machine. You may be thinking that poor communication isn’t that big of a deal.
Will robots replace humans in the near future? As machine learning and artificial intelligence continue to grow in popularity, this question becomes all the more relevant. Which jobs will become extinct, and what will society looks like in the future? If you’re a data analyst whose worried about their job security, don’t worry—there’s still hope for you! In this article, we’ll take a look at the skills a data analyst can acquire to become a data scientist and rise above these pesky robots 🙂
Unlock the potential of data! With this course, you’ll learn about data analytics, data science, statistical analysis, and functions in the R programming language. This course is perfect for people who have no prior knowledge of computer science or R programming. With Introduction to R, you’ll learn to work in the R programming language as you enter the promising world of data science. Why R is so famous According to the TIOBE programming community index, which ranks the popularity of all programming languages, R is one of the hottest programming languages of 2018.