Data science is a field that can lead to many different pathways, so choosing the right curriculum based on your existing skill set and picking a specialty within the broader field of data science is crucial.
In the world of data science, there are four core pieces: acquiring information, organizing the data, discovering interesting knowledge, and presenting the results to help inform future actions. Data scientists are talented people who tame unstructured information to achieve these four key pillars.
While data science may seem intimidating to some, what many don’t realize is just how accessible, important, career-building and lucrative the field can be for many people. If you enjoy mathematics and statistics, appreciate practical business thinking or just like to present ideas in meaningful ways that will have an impact, then data science is for you.
Select the Right Learning Path
To be successful in the field, it’s important to learn the right skills by selecting the ideal learning path for you—whether that entails taking a single data science course or pursuing a full degree program.
For Siva Devarakonda, director of data science at Noodle.ai with a background in electrical engineering, taking a data science course was critical to launching his data science career. “You cannot teach someone from scratch; it takes going through a data science course, which then exposes you to a variety of areas that you might not have considered before,” Devarakonda says.
Ask yourself these key questions to figure out which learning path is the best fit for you:
- What are the basic skills required?
Your path should broadly involve strong foundational knowledge in math, statistics, programming, data management, machine learning, and data visualization and communication. From there, you can build on this base by specializing in a specific area of data science that makes sense for you and/or your company.
- What is your current skill level?
Understanding what you already know, as well as what you still need to learn, is important to determine your path in gaining the right skills. How familiar are you with mathematical and statistical principles? Do you already know any programming languages? These are key questions to ask as you self-assess. Take our quiz to find out.
- What role are you aiming for?
You don’t have to be a data scientist to be in the field of data science. “A person who wants to go into data science should really look at how they are going to drive value,” says Devarakonda. “There are lots of opportunities and gaps where data can be used.”
Four of those opportunities include the roles of data steward, data engineer, data scientist and data analyst:
- A data steward manages the data an organization collects. This role—which requires the least amount of technical training and only some basic legal expertise—ensures that data processing, policies and guidelines are aligned with those of the organization and comply with broader policy and regulatory obligations, such as the General Data Protection Regulation (GDPR).
- Data engineers are responsible for the development, construction, maintenance, and testing of databases and large-scale processing systems, or architectures. They also wrangle the data into shape—called normalizing—so data scientists can use it.
- Data scientists enable businesses to make better decisions by helping them interpret data, whether by spotting opportunities, reducing costs, focusing targeting efforts and/or crafting forward-looking strategies. Data scientists can also help an organization pick the right problems to solve.
- Working closely with data scientists, successful data analysts collect data, organize it and present the information in charts, graphs and tables that can be easily digested by the broader organization.
- Do you have time and mind space to put into this?
Consider the hours and effort that will be needed to focus your career on data science. If you work full-time, taking courses in your free time at your own pace or signing up for short-stint boot camps might be the best options.
- Can you afford it?
Online courses can give you access to some of the best universities in the world at a reasonable cost. With technology-enabled online learning, obtaining new skills and advancing your career are more cost-effective and flexible than ever before. Also, your employer may sponsor your continued education, knowing it ultimately will benefit the company. Whatever your budget is, there are options.
Earning a Degree
If you find yourself seeking a deeper dive into data science based on your answers to the questions above, consider pursuing a degree. The two top online degrees below are designed to provide learners with a world-class data science education from some of the top data scientists around the globe.
The University of Illinois
The University of Illinois offers a Master of Computer Science degree consisting of courses focusing on data science. This flexible and affordable master’s degree is designed so that students can complete it fully online at their own pace in order to balance personal and professional commitments. With the Master of Computer Science in Data Science (MCS-DS), students take graduate courses from one of the top five computer science programs and the top library and information studies program in the country, as ranked by U.S. News & World Report.
In addition to learning how to treat data itself scientifically (data curation), as a complete computer science master’s degree, the MCS-DS also teaches the algorithms and processes behind data science so students learn how to utilize computing power, specifically cloud computing, as a scientific instrument for big data exploration of increasingly massive datasets. This degree gives students who have some technical background access to the computational and statistical knowledge needed to turn big data into meaningful insights. At the same time that students build expertise in four core areas of computer science—data visualization, machine learning, data mining and cloud computing—they also learn key skills in statistics and information science. Most learners complete the degree in less than three years, although it can be completed in as little as one year or, if needed, as many as five years. Apply by February 15 to join the summer 2019 cohort.
The University of Michigan
The University of Michigan is developing an applied master’s program in data science, designed for people who want to become data scientists through hands-on projects in programming, statistics, data analysis, information visualization and machine learning. The Master of Applied Data Science degree program is fully online and project-based, allowing learners to gain the skills needed for today’s data-driven workplace with the flexibility to earn a meaningful degree while employed.
Working with authentic industry data sets from top companies, students will build a portfolio of projects to showcase skills to employers from day one. Students will learn the systems and techniques to help their organizations overcome data overload and make winning decisions. Building knowledge in data ethics and persuasive communication, students will set out on a path to become leaders in the ever-changing data science field. Graduates from the University of Michigan School of Information, ranked No. 1 among among information schools in Information Systems in the United States, have a 98 percent job placement rate in the field of their choice and go on to become data scientists at Google, Facebook and Amazon. Applications open in January 2019.6