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Colby Schrauth Courses
Beginner's Guide to Data & Data Analytics, by SF Data School
4.5 (26,862 Reviews)
Provider: Udemy
Time: 1.5h- 2024
$14.99
Visit
Most Recent Review
Information technology has transformed so rapidly (even before AI) that I have been spinning my wheels. Where does one start? How does one deal with terminology let alone harness the benefits? The creators of this course, equally overwhelmed by it, worked through it all for themselves. One of their products is this excellent class. This does not require you to learn to write computer programs. Rather, you learn what the most frequently used programs are and how to employ them in ways relevant to your needs. The course developers break down information on data storage and formatting (ex, Excel). Then they instruct students about programs that process the data formats into usable results (charts, graphs, etc). Until I participated in a recent work project, I had no clue about the interoperability of Excel with other software. This class is exactly what I needed to learn how data storage and processing function. I highly recommend it.
- Review by Jennifer Smith on Beginner's Guide to Data & Data Analytics, by SF Data School
Instructor Bio
Co-Founder of The San Francisco Data School, and Analytics Team Lead at Square. Previously, a Lead Instructor for Data Analytics at General Assembly San Francisco, and an Instructional Associate for Columbia University’s MS in Applied Analytics.
The world of data is incredibly massive. For anyone looking to start their journey in a data profession, it can quickly become an overwhelming endeavor. No one knows this better than Colby Schrauth.
Colby took a non-linear path to becoming a data professional. His educational background is Finance, but he’s spent the majority of his professional career in Business Development roles – selling payroll to small businesses for ADP, helping large enterprises understand the value of online communities with Lithium Technologies, and more. However, the goal of becoming a practitioner of data persisted throughout these experiences.
Along the path to becoming a data professional, Colby was constantly battling internal thoughts of discouragement:
• I don’t have a Computer Science background, will I ever be taken seriously?
• What data tools should I learn, and how do I get started?
• The data ecosystem is complicated and evolving quickly, will I be able to keep up?
The list goes on, and on. Here’s the good news, this real-world experience is what makes him the ideal teacher for those who wish to forge their own path in the world of data. Colby believes that anyone with patience and a deep desire to learn can develop a concrete understanding of data and how to work with it. He’s on an entrepreneurial mission to share the epiphany moments he’s had along the way, and create a linear learning path so that others don’t have to learn the hard way, like he did.
