Data science is a career that's here to stay and will only grow with the future. That's good news for anyone interested in the field because it creates job security, lucrative opportunities to use your skills, and a good salary. You can become a data scientist through Udacity's Nanodegree programs, and if you already work in the field, Udacity's courses in data science specialization help you advance your career, diversify it, and stay ahead of the game.
What Is a Data Scientist?
The short answer is that a data scientist is someone who finds meaning in information and puts it to use. More specifically, a data scientist collects data, cleans it up, analyzes and interprets it, validates its accuracy, and shares the findings with others within an organization to work toward common goals. A data scientist does all this using specific tools related to math, statistics, and machine learning as well good old-fashioned human intuition, reasoning, and creativity.
Who Would Make a Good Data Scientist?
Of course, anyone interested in the field would make a good data scientist, but certain traits and natural curiosities create a solid foundation for a career in data science. If at least a few of the following apply to you, you'd likely find data science to be a fulfilling career choice. These include if you:
- Have a strong interest or background in the business domain
- Are effective in written and verbal communication
- Enjoy math, statistics, and probability
- Have an interest in computer science and software programming
- Like to analyze and problem solve or have a hacker mindset
- Work well on your own but also collaborate with others to meet common goals
- Are very comfortable using the scientific method
What Kind of Jobs Do Data Scientists Have?
Data science is more of a broad term that encompasses a variety of job titles. The niche that's an ideal fit for you has much to do with your particular interests and strengths. Here are a few examples:
A data analyst is skilled in working with programming tools, visualizes data well and is an effective communicator.
A machine learning engineer is also effective with programming and has keen data intuition. This person is also adept with statistics, multivariable calculus, and linear algebra.
Data engineers are trained to deal with data wrangling, which means dealing with imperfections in data. They're also particularly skilled in software engineering and programming.
Then, there's the data science generalist who might be considered the jack of all data science trades. Programming is a critical skill as well as machine learning and data visualization. This person is good with statistics, has great data intuition, isn't intimidated by data wrangling, and has effective communication skills.
How to Get Data Scientist Certification
Udacity's School of Data lets you earn data scientist certification online in the form of a Nanodegree program, whether you're just starting out or seeking to hone your professional skills. Sign up for courses to learn specific skills such as Python and predictive analytics, or enroll in Udacity's Data Scientist Nanodegree program to build useful machine learning models and recommendation systems, and create solution-based projects that apply directly to the current data science industry.