Data science is an interdisciplinary field that involves using statistics, machine learning, artificial intelligence, and data visualization to extract information from data sets. In many ways, it’s the marriage of big data and statistics. To be a good data scientist, you’ll need to know how to work with both structured and unstructured data. Big data refers to datasets that are too large or complex for traditional database management tools. Unstructured data refers to bits of text attached to some aspect of the dataset – for example, comments left on a blog post about a product or service. Both structured and unstructured data have their place in the world of business analytics and are important for most companies.
Benefits of pursuing data science:
There are many benefits to pursuing a data science degree. A data science degree can provide you with the skills and knowledge necessary to pursue a career in data science. Additionally, a data science degree can also help you develop important critical thinking and problem-solving skills. Pursuing a data science degree can also help you better understand data and how to effectively use it to make decisions. The degree is offered by a range of universities. It is more commonly available at undergraduate level, but there are increasing numbers of postgraduate courses. Courses generally focus on statistics and mathematics as well as computer science and programming.
Some institutions, such as Oregon State University’s School of Electrical Engineering, Civil and Environmental Engineering, Computer Science & Physics (ECEP), offer combined degrees in data science. These combine traditional degrees like electrical engineering or computer science with data science core classes in one program. Other departments offering integrated programs include Computer Science at North Carolina State University and the Department of Mathematics at the University of Wisconsin-Madison Department of Statistics. Data Science is also offered as part of the MSc Economics and Econometrics program
Now, when it comes to data science, what is the better take? Certifications or Masters?
The second issue to think about when choosing between an undergraduate data science degree or certificate program is which skills you want to learn, and which types of experiences you would like to get, both in the classroom and out. Because there are thousands of data science degrees and certificate programs you could choose from, beginning your program selection process with an emphasis on course offerings and costs helps you to filter out a vast majority of programs that are either overpriced or that do not offer courses that you want to pursue. There are also more specialized certificate programs–those that deal with applied statistics or mortgage analysis, for instance–that might be appealing to you if you are already working in data science, or you would like to add concentration to the masters degree that you are currently pursuing.
While the breadth of knowledge does not quite match a masters in data science, data science bootcamps provide deeper immersion than most certificate programs. Masters programs also offer great networking opportunities, since you get to engage with professionals in the data science field, building up a portfolio that can be useful in the real world. If you think that eventually you might want to get a Masters, try looking at Certificate programs that have courses you can transfer to more advanced degrees.
You will need a minimum of a bachelor’s degree and over five years experience in data science to qualify for every track, whereas others require a masters or prior certification. Students are eligible to receive the data science masters certificate with any bachelor’s degree, as well as prior training in computer programming and quantitative classes like calculus or linear algebra. The Graduate Certificate in Data Science and Business Analytics is designed for working professionals, offering evening classes and the option of completing the program at either a full-time or part-time schedule.
Conclusion
The Certificate allows students to explore applied data science topics they might not cover as part of a masters degree, with courses on analytics for marketing, sports performance, risk, networking, and text. The Open Groups Career Certification program for data scientist professionals (Open CDS) is a competency-based certification with no traditional coursework or exams. Not having a degree in Data Science helps candidates demonstrate they are more than ready to become a Data Scientist: having an online data science certification with lots of hands-on projects and a GitHub account proves you are practicing Data Science skills.
The best way to approach learning data science is by taking the modular approach in and learning it via shorter, certificated, high-quality MOOC courses, which likely provides more hands-on, practical knowledge about data science concepts, for much less money when compared with the masters degree program in data science. Knowledge about Deep Learning, Neural Networks, Data Mining, Regression, and other similar concepts is not required, but it is better to be aware of Deep Learning. Data analytics bootcamps are usually used either to increase productivity in a current job, or to learn the skills needed for transitioning into a new career.