The question of whether one can pursue a certain profession with or without a degree is not new in an era where skills-based certifications have gained so much recognition as to be listed as a requirement for certain positions. Yes, bachelor’s, master’s, and even Ph.D. qualifications still remain to be valid. However, the job market demands much more. Recruiters need you to demonstrate that you possess the specific skills and/or experience required for a particular position.
We all know that experience is highly valued in the data science field. Even so, there is a path you’ll take to gain the required experience plus skills, and that’s what we discuss in this article. We shall also be looking at the place of the Data Scientist course and why you should or should not consider it in your quest to pursue a data science career.
Data science career with a degree
Many professionals in the data science field have a graduate degree, master’s degree, and few have attained the Ph.D. level qualification. Those aspiring to take up leadership roles should consider earning a master’s or doctoral qualification along with the required skills and experience.
While some schools offer a data science degree program, most professionals come from mathematics, statistics, IT, or computer science background. To pursue a data science career with a degree, you need to:
1. Earn a relevant qualification
Earn a bachelor’s degree in IT, Computer Science, math, statistics, or a related field. Though not offered by many institutions as the program is relatively new, a data science degree may present the best option for you. This is because it will equip you with the skills required to perform complex analyses on datasets. These include statistics, analysis techniques, computer programming, and other data science and domain skills all under a one-degree program. Also, a program that teaches interpersonal skills will help you develop the ability to communicate, understand, and interact with people, a much-needed skill in technical fields like data science. Finally, consider a program with practical exercises and a capstone project at the end so that you will gain both theory and practical knowledge.
If you are considering advancing, undertaking a master’s degree in a related field will be in order.
2. Gain some experience
Experience counts a great deal in the data science field; thus, it is vital to consider options that will build your data science skills and competence. This doesn’t have to be an employment position, it may take some time before you land one. Consider volunteering or taking up an internship role, particularly within your domain.
While at it, also consider working on projects. Apart from the project, you will have undertaken during your studies; your portfolio needs to have other personal-initiative projects you have done to build skills like programming with R and Python; SQL, statistics and probability; and visualization, which are essential in data science.
3. The downside
Most new programs are yet to develop curriculums that cover data science skills like computer science, statistics, and mathematics in-depth and comprehensively. Secondly, degree and master’s programs require substantial investment in terms of time and finances.
Data science without a degree
Is it possible to pursue a data science career without a degree?
While a degree makes sense particularly for networking, landing a data science position requires a demonstration of relevant skills and practical experience, which you can acquire without undertaking a degree program. There are plenty of resources online and offline available for those aspiring to become data scientists. What’s more, you stand a good chance in the job market because you will have a clear career path, and all your effort will be targeted at gaining relevant skills and experience.
First things first, you need to be aware of the skills required to become a data scientist. These are:
- Math and statistics to be able to handle
- Programming skills, particularly in Python and R
- Data mining and analysis
- Machine learning
- Domain knowledge
Once you are aware of these basic skills, here is a simple roadmap you can take to prepare for a career in data science.
1. Learn programming
Programming is at the heart of data science. Programming helps data scientists to organize unstructured data. Some fundamental concepts you need to grasp include Python and R languages, SQL scripting, fundamental data preparation algorithms, as well as object-oriented programming.
2. Take an online Data Science certification course
Data science is all about working with data. A comprehensive data science course will help you master concepts on data collection, preparation, storage, statistical analysis, and modeling.
The advantages you will have with taking up data science courses over a degree program is that they are self-paced, way cheaper, and flexible but still provide you with a structured curriculum that will help you achieve milestones in your data science career systematically.
3. Work on projects
There are several real-world projects you can work on to sharpen specific data science skills, at least after completing some modules. When selecting a project, think about problems you would like to solve or a topic that interests you, find a data set, and try to apply the techniques you have learned. Remember, you will need both data science skills and domain knowledge in your future career. While at it, identifying a mentor, could be an industry expert, tutor, or mentor, to assess your project will go a long way.
Networking with other professionals and industry experts aligns you with data science culture. Think about building knowledge by learning from others. As a source of knowledge, also consider reading books, blogs, journals, and watch videos in data science.
Conferences, online forums, professional networking sites, and
Is a degree a requirement for a Data Science career?
As we have seen, you do not have to possess a degree to pursue a data science career. A degree only helps you to easily transition into data science. You should note that some recruiters will often place a minimum educational qualification in their job description. Still, others will emphasize proof of skills and experience. The fact is, the data science field is growing at an exponential rate; thus, the demand for professionals in the field is set to increase now and in the future.
Some professionals opt to gain skills and certifications, secure a job, and go back to school to earn a degree. Others prefer building relevant skills through certifications and practice. Whichever way you choose to go about it, understand that data science is a multidisciplinary field, so be sure to acquire the necessary skills and experience as they matter most.