In 2012, the year when data scientists became the talk of the town, the New York Times published an article that highlighted the power of data science. It’s something that has made the rounds in the industry, and it started like any other interesting story:
A man walks into Target and asks for the manager.
The man, seething, holds on to several coupons mailed by the store to his teenage daughter and demands an explanation. Caught unaware, the manager takes a closer look at the coupons and sees advertisements for maternity clothes and baby furniture. Flustered, the manager quickly apologizes to the father.
Days later, the manager calls the man to, once again, express his regret over the seeming blunder. Instead of being met with anger, however, the man replies in embarrassment: “I had a talk with my daughter…It turns out there [have] been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”
Although this may seem like something straight out of a marketing campaign, it’s actually a true story. It turns out Target’s data analyst team at the time observed that women in their second trimester of pregnancy tended to buy more unscented lotion than other customers.
By gathering data on each shopper’s purchasing habits, the team was able to come up with a pregnancy-prediction model that, as the name implies, can guess who’s expecting and who’s not. The store then sends ads that are targeted at expecting moms. One of them was the daughter in question.
Why Learn Data Science?
In recent years, data science has gone from geek to chic. It isn’t surprising why.
While the story above happened nearly a decade ago, it remains a perfect example of why, to this day, there’s still a war for data science talents.
From analyzing consumer needs to driving marketing strategies, data scientists serve as key players for the success of organizations. At a time when data is the world’s most valuable commodity, professionals who can unlock its value are critical. The problem is that the demand for data scientists has far outpaced the available supply.
According to industry platform Quanthub, the 2020 job market faced a shortfall of around 250,000 data science professionals, and it’s expected to grow in coming years. Striving to fill this gap are several training resources created to democratize and demystify data science.
Among these is Dataquest, a data skills learning platform designed to bring today’s hottest job title to anyone looking to jump into the data science world for as low as $0.
Inside Dataquest: What’s In It For Me?
If there’s a simple definition of a data scientist, it would be this: a data scientist is someone who spends the day solving problems with data.
Just like a proper scientist, a data science professional follows a certain process: they assess a problem, devise a solution to the problem, and then use the available tools and strategies to best deliver the solution.
It was the same process that led self-taught data scientist Vik Paruchuri to Dataquest.
How Dataquest Began
The story starts with a problem. The problem was this: Vik Paruchuri started as a chronic job-hopper, switching from job to job with the hope of finding something that would spark his interest. After years of doing so, he found his passion in data science. To enter the field, however, he needed to get some training.
This put him in a dilemma. He can either go back to college and earn another degree—this time in data science—or go the opposite way and teach himself the ins and outs of data science. Because Vik had previously found the public education model “boring and de-motivating”, he opted for the latter path.
And although he eventually succeeded, he knew that there had to be a better way to make data science training more accessible yet affordable, and more flexible yet structured.
Enter, the solution: two years after his first job as a machine learning engineer, Vik slowly built a platform that met both formal and self-paced learning models at their halfway point. In 2015, Vik founded Dataquest.
Who Is Dataquest For?
Dataquest, as the name implies, is for individuals who are on a quest to equip themselves with data-related skills and knowledge. Put simply, it’s a skills training platform for data learners. These include the following:
- Data professionals who are seeking to grow or finetune their skill sets
- Professionals whose roles involve working with data
- People who are interested in learning data science whether out of curiosity or personal learning interests
Because it’s designed for a wide range of learners, Dataquest likewise offers a multitude of learning options.
What Can You Learn from Dataquest?
Depending on which group of data learners you identify with, you can choose the Dataquest Career Paths or the Skills Paths. Both tracks are fully online and comprise a catalog of courses designed to equip you with the depth of knowledge that you need to reach your data-learning goal.
Career Paths
The Dataquest Career Paths train two groups. First, they’re designed for data professionals who wish to refresh their skills. Second, they prepare beginners who wish to secure one of three career outcomes: data analyst, data scientist, and data engineer.
Because the programs also cater to the uninitiated, the content is structured to dive deep into the fundamentals of the corresponding fields and help you secure a relevant entry-level role in the industry.
- Data Analyst in R. Because it’s specially built for statistical computing, R is fast becoming the lingua franca of data analysts. Covering 20 courses, this program explores how to use R to clean, visualize, analyze, summarize, and report data to derive powerful insights. You’ll also navigate modern R workflows with RStudio and Tidyverse packages and learn how to use tools like Git and SQL databases.
- Data Analyst in Python. Python has a strong reputation for being the preferred language for data analysts and data scientists alike, for good reason. Python emphasizes data mining, processing, and visualization, all of which comprise the majority of the data analysis life cycle. Take this program to learn how to effectively use Python to analyze and visualize data.
- Data Scientist in Python. You’ll be hard-pressed to find a data scientist who isn’t familiar with Python. Learn to use Python and its libraries to complete an end-to-end data science project cycle. Because data science is a step further from data analysis, this program consists of 31 courses that cover end-to-end data analysis before diving deeper into data science.
- Data Engineer. Dubbed the next sexiest job of the century, data engineers ranked eighth in LinkedIn’s Emerging Jobs Report. While data scientists make it their business to make data useful, data engineers build the pipelines that data scientists rely on. Therefore, they focus on another thing entirely: to make data usable. Take this program to skill up on Python programming, SQL databases, and data pipeline-building.
Skills Paths
The Dataquest Skills Paths have data professionals in mind. The programs are skills-focused and are shorter than the Career Paths. This allows learners with an intermediate understanding of data analysis to quickly upskill and expand their skill set. Dataquest currently offers 11 skills paths. Let’s cover some of them below.
- Machine Learning. If you want to further your career, acquiring machine learning skills is the way to go. Take it from tech heavyweights like Google, Facebook, and IBM, all of which are pouring money into the development of AI and machine learning. Therefore, it’s not surprising why the demand for AI and machine learning specialists is high, even topping LinkedIn’s Emerging Jobs Report. Take Dataquest’s Machine Learning Introduction with Python and supplement it with the Machine Learning Intermediate with Python program to solidify your skillset.
- Data Analysis and Visualization. Both Python and R are well-equipped with graphing libraries that provide high-level interfaces for data visualizations. So, Dataquest designed two Skills Paths for both tools. Depending on the skill you want to improve, you can either take Dataquest’s Data Visualization with R or opt for the Data Analysis and Visualization with Python program.
- APIs and Web Scraping. Aggregate all sorts of data without getting blocked by learning about APIs and web scraping. Dataquest offers two paths for those who wish to master these data extraction techniques. Choose from either of these programs: APIs and Web Scraping with R and APIs and Web Scraping with Python.
- Probability and Statistics. Before there was data science and machine learning, we had probability and statistics. The latter serves as the basis for the former. Strengthen your foundations by taking either or both of Dataquest’s programs: Probability and Statistics with Python and Probability and Statistics with R.
The Guided Projects
Having technical knowledge is the minimum requirement to become a data scientist. Take your learning further by gaining practical skills with Dataquest’s guided data science projects. These projects get you working on real-world data science problems to stimulate your problem-solving and research skills.
As you progress, the challenges will increase in difficulty and decrease in guidance. You’re encouraged to create a Github repository where you can showcase your projects and demonstrate your skills to potential employers.
Below is a sneak peek of some of Dataquest’s exciting guided projects.
- Visualizing Earnings Based on College Majors. Analyze the success of students who graduated from college between 2010 and 2012 using the Jupyter notebook and pandas.
- Analyzing Stock Prices. As day trading gains popularity day by day, the ability to analyze stock prices for smarter investment is becoming more important. Experience working with stock data here.
- Star Wars Survey. See which Star Wars movies received the best and worst response from movie-goers. By the end of the project, you’ll have practiced cleaning and mapping values in pandas and computing summary statistics.
A Risk-Free Start to Data Science Training
Dataquest comes with two subscription plans, and herein lies one of Dataquest’s most appealing features. Aside from having a comprehensive portfolio of data-centric programs to hone your skills, you can also start your training for free.
- Free Plan. When presented with many options, it’s best to follow the golden rule: free options first, paid options later. Dataquest does not skimp on training resources. True to its goal of bringing data science to the masses, Dataquest offers data learners the chance to access some of its interactive courses without having to pay out of pocket. These include hundreds of practice problems and exclusive offers for free course launches.
- Premium Subscription. If you’re ready to commit to more structured learning, then you can opt for the premium subscription. Depending on your resources, you can either choose to pay $49 per month or $399 per year (heads up, the annual plan saves you $189 a year). Both plans will grant you access to the complete Dataquest course catalog and over 30 guided projects. You’ll also benefit from premium community features and career services.
Bringing Data Science to the Masses
Based on Dataquest’s 2020 Student Outcomes Report, of the 656 Dataquest learners surveyed, 97 percent recommended Dataquest for career advancement.
Of them, 90 percent transitioned to data-centric roles, reporting an average annual salary increase of $30,000. Dataquest’s learning paths received the most praise, followed by its guided projects.
In 2015, Vik Paruchuri started Dataquest with the simple goal of bringing data to the people. Six years later, Dataquest has trained over one million learners on their quest to advance their careers.
Another story is in the works: one million learners walked into Dataquest and asked for a better future. Most found theirs. Be one of the next million. Start fresh and start free with Dataquest.
About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication.
