Welcome to the entering and transitioning topic for this week! Any inquiries concerning beginning, learning, or moving into the data science field should be directed to this thread. Among the subjects are:
Resources for learning (such as books, guides, and videos)
Conventional education, such as classes, degrees, and electives
Alternative forms of education, such as boot camps and online courses
Questions for a job search (such as applications, resumes, and career possibilities)
Simple inquiries (such as where to begin and what comes next)
Visit our wiki’s FAQ and Resources pages while you wait for community responses. Additionally, you can look up answers in previous weekly threads.
I recently earned admission to both the MADS program at U Mitch and the OMSA program at Georgia Tech, therefore I’m currently attempting to decide which to enroll in.
I have some coding expertise with Python, R, and front-end stuff, but my background is in UX and product design.
I wanted to know whether each institution has a solid reputation or if there is anything that can be stated about the caliber of either program, as you are the ones with greater expertise in the sector.
Hello, six applied minors are available for the undergraduate Data Science degree at my college. I have (kind of) eliminated the three since they are in extremely specialized fields—Biological Analytics, GeoSpatial Analytics, and Health Analytics—that I was never initially interested in. Acturial/Risk Analytics, Data Engineering, and Computational Mathematics/Analytics make up the final three. Which of these three minors should provide me with the greatest flexibility in terms of pay and professional advancement? I appreciate the replies ahead of time.
Unless you genuinely commit time and effort to becoming an expert in one of those fields, none of those minors will have a substantial impact on your course.
I’m a geospatial analytics/data engineering specialist, and since I’m just interested in one area of analytics, having a specialty has helped me land jobs. You will probably join the throng of other college students attempting to get into the tech industry if you are unable to identify a niche that interests you. Therefore, don’t focus too much on job growth and comp because your skills (cloud, databases, scripting, etc.) are for those things. Try each of those things and choose the one that interests you the most.
I understand. I have to graduate as soon as possible, but time and money are not on my side. I can’t try them all because the coursework for these minors doesn’t truly overlap. I’m leaning somewhat toward actuarial and risk analytics because I’m interested in finance. However, I find data engineering to be intriguing as well, which brings me to my next query: what precisely is the role of a data engineer, and what kind of industry requires one? Thank you once more for your response.
I see now that you’re pressed for time. I believe undergraduates don’t give data engineering much thought, which is a really good question.
Data engineers use data pipelines to move, modify, and change data. They provide this data to analysts, ML models, data scientists, and others. To handle this data challenge at scale, data engineers must leverage cloud architecture, SQL, Python, Spark, and numerous other distributed querying languages.
Automation is key for data engineers. You handle a large portion of the background work so that others can provide analytics without worrying about how the data gets there. Just search for “data engineer” on LinkedIn to see that every sector needs one.
If you need to graduate as soon as possible, I think Data Engineering is a great option because need is growing, but every undergrad wants to be a software engineer. You can make 6 figures out of undergrad, but maybe not a magnificent seven SWE salary. Additionally, because you can’t get a “Data Engineering” degree, you’ll get way more out of the projects and skills you learn that are specific to DE. I bet that if you ditch the React app, and make a full life cycle analytics project including data pipelines, you are going to kill entry level/internship interviews for DE roles.