As global business becomes more data-oriented than ever before, the demand for data scientists has soared. Jobs in this space now offer handsome compensation packages and provide excellent career opportunities.
Students with analytical and mathematical talents are increasingly attracted to lucrative careers in data science. The work can be incredibly satisfying for the right individuals, and involves digging into statistical data, creating algorithms, and analyzing huge data sets.
So it’s not surprising that you’ll need some specialized technical education in order to get hired as a data scientist. A data science degree will get you there, but it’s expensive - and since most are 4-year programs, it also takes a significant amount of time. So you’ll need to choose wisely.
Selecting the right program for your specific needs can be a tough decision, so we’re to help you consider your options. We’ll discuss what you need to consider when selecting a degree, which degree subjects are best suited to a career in data science, and also introduce you to more specialized education paths, such as online data science bootcamps, that could get you hired more quickly at a lower cost.
Factors to Consider When Choosing a Data Science Degree
There are some factors that you must consider before choosing a degree program.
- Choose a Specialization: Investigating and deciding on the right degree program should begin with determining which path you want to go down. Some specialized roles include data scientists, data analysts, machine learning engineers, statisticians, and data architects.
- Consider The University: The data science degree you choose is important, but so too is the university. It should have a good reputation and align with your requirements. The university you select will determine the kind of mentors available and the specific curriculum you’ll follow.
- Check out The Curriculum: The program curriculum should be comprehensive enough to offer a broad range of optional modules. It should include important subjects like computation, statistics, micro-econometrics, and focus on data-intensive computing technologies. You should choose a program that gives you the opportunity to design data processing solutions and communicate data finding during the course.
- Placements and Internships: Does the course improve your prospects of getting a job? By the end of the course, you should be able to secure a placement at a well-known company.
- Networking Opportunities: The program should have a strong alumni network and excellent industry ties. Networking will allow you to gain valuable experience and should boost your chances of getting hired.
- Value Among Recruiters: Do your research and determine if the program is respected and valued within the data science industry. Investing your time and money in a degree that nobody cares about is the last thing you want.
- Cost of The Program: Although some of the more respected universities and courses will cost more, they may also provide you with a better chance of getting hired. Investing in your education is always a wise move and you shouldn’t look to scrimp. Only consider cost as a last resort, when weighing up similar degrees that you’re struggling to decide between.
Data Science Bachelor’s Degree
Earning a bachelor’s degree is a popular starting point for many aspiring data scientists. This is your chance to learn everything about the field in a well structured and traditional study program.
Not many colleges and universities offer a specialized data science degree. So, you have to choose a major that can translate into a data science career. Statistics, computer science, engineering, mathematics, and IT are some of the common majors that can lead to jobs in data science. Out of these, statistics and mathematics are preferred by most employers.
Since there is no road map to becoming a data scientist, your goal should be to acquire the skills needed for this role. Apart from picking the right major, you should also focus on course structure and what topics are covered. Look for classes that provide exposure to data science and data analytics.
As a budding data scientist, you should be looking for the following classes:
- Computer Science
- Statistical Computing
- Fundamentals of Statistical Data Science
- Applied Time Series Analysis
- Introduction to Programming
- Programming and Problem Solving
- Analysis of Categorical Data
- Data Structures and Programming
- Algorithm Design and Analysis
- Introduction to Artificial Intelligence
- Machine Learning
These are just some examples. There will be many other classes, depending on your program and school, which can benefit you.
Data Science Master’s Degree
You don’t need a master’s degree to become a data scientist. But some students want to extend their education and gain a deeper understanding of data science principles. It really depends on your individual needs. If you can afford further education and are in no rush to start your data science career then a master’s degree could be ideal for you.
A master’s degree can be useful if you’d like to specialize in a specific area. The following institutions offer a master’s degree in data science:
- Columbia University
- Georgia Institute of Technology
- North Carolina State University
- New York University
- The University of Rochester
With a postgraduate program, you’ll learn analytical tools, computational data analytics, clean coding, problem-solving, and statistical tools.
There are some requirements to get into a master’s program, like a good GPA and a letter of recommendation. Also, you need to know exactly what you want to learn and why. Some students choose to work as an intern after completing their bachelor’s degree. This helps them pay for the master’s program.
Data Science Certification Courses
Not everyone wants to pursue a master’s degree. You can opt for a certification course instead. Even those who hold a master’s degree sometimes choose to do certification courses to update their skills and attract better opportunities.
There are several certification courses available online. You can also find certification courses that are offered by various universities and established companies.
Here are some of the more popular data science certification courses:
- SAS Certification
- SAS Certified Big Data Professional
- DASCA (Data Science Council of America)
- MITx (Statistics and Data Science)
- HarvardX (Data Science)
- IBM (IBM Data Science)
- Microsoft (Data Science Fundamentals)
- Microsoft (Data Science Core)
- GTx (Analytics: Essential Tool and Methods)
- UCSanDieoX (Data Science)
- IBM (Python Basics for Data Science)
Data Science Bootcamps
Bootcamps offer an alternative path to landing a well-paid data science job. They’re specialized education programs that are laser-focused on data science.
Because they’re more focused, online data science courses are cheaper than traditional degrees and take less time to complete. You’ll learn all the necessary skills you need to get hired as a data scientist at a top tech firm. Here are some of the platforms that offer data science bootcamps:
- Data Science Dojo
- Insight Data Science
Our Data Science bootcamp is unique thanks to our mentorship program and career coaching. You’ll meet with your personal data science mentor one-on-one throughout the course to talk through the curriculum and help you plan out your career. And as you wrap up the course, a team of career coaches will help you perfect your resume, portfolio, and interview responses.
We know this system works. Unlike traditional degrees, we guarantee a data science job within 6 months of graduation, or your money back.
Can You Become a Data Scientist Without a Degree?
The answer to this question is yes! Getting a degree is the most conventional way to become a data scientist. But many people are now opting for alternative paths like online courses and bootcamps.
Here are some steps that can be helpful in launching a career in data science without a degree:
- Gain Knowledge: Reading is a great way to acquire knowledge and shouldn’t be overlooked. You can gather information from reading data science blogs, books, and other online resources. Talking to people who are established in the field will also help you gain valuable insight into data science.
- Learn What a Data Scientist Does: Data science is a broad field. You should be aware of its subdomains and identify your interest areas. You should be familiar with the day-to-day work of a data scientist.
- Case Studies: Reading books provides you with a strong foundation in theoretical knowledge. But reading case studies provides more practical real-life insight. Learning both theoretical and practical skills is the key to mastering data science.
- Live Projects: Take on some live projects. This will add credibility to your knowledge. To find live projects, you’ll have to do some research. DataFlair is one of the platforms that can help you get started.
- Getting Certified: If you don’t have time to invest in a full degree program, then consider doing a certification course.
- Build a Portfolio: Your portfolio needs to be impressive. You should have a portfolio on sites like LinkedIn, GitHub, and Kaggle. Your portfolio should highlight all your skills, accomplishments, and experience in a visually appealing manner.
- Take Part in a Hackathon: Hackathons allow you to demonstrate your skills and abilities and build new connections with like-minded people.
Kickstart Your Data Science Career Today
Hopefully you now have a good understanding of your education options, and are even more motivated to join the ranks of professional data scientists who are changing our world.
Remember, a degree isn’t always necessary to land a well-paid job in big data. Aspiring data scientists can opt for more focused learning programs. If you have a passion for data and love problem-solving enroll in our data science bootcamp. You’ll receive one-on-one mentoring from established professionals and we’ll teach you everything you need to start your dream job in data science.
Launch Your Data Science Career
An online data science course aimed at helping you launch a career. One-on-one mentorship, professional guidance, and a robust community network are on hand to help you succeed in Data Science.