AI News, Data Science: An Introduction
- On Sunday, September 30, 2018
- By Read More
Data Science: An Introduction
It is designed for the advanced high school student or average college freshman with a high school-level understanding of math, science, word processing and spreadsheets.
While some elementary data science skills will be taught, the point is not skill development, but rather critical thinking and problem solving development.
Data science--as a profession and as an academic discipline unto itself—is new, having been born in the first decade of the 21st century.
It is a child born of the mature parental disciplines of scientific methods, data and software engineering, statistics, and visualization.
As such, the student will be introduced to the parent disciplines and then given exercises that will fuse the parental disciplines into data science.
In addition, 'hacking' in the original positive sense of the term, is also a contributing parent to the data science child, even though 'hacking' is not taught as an academic discipline.
Obviously, a mature data scientist will be proficient in each of the parent disciplines, studying them individually and combining them to solve serious data problems.
This means data science is an advanced discipline, requiring proficiency in parallel processing, map-reduce computing, petabyte-sized noSQL databases, machine learning, advanced statistics and complexity science.
That is, a class that has three classroom-hours of instruction for 16 weeks—for example, 48 1-hour class periods.
There are 32 chapters, which allows for—averaged over the semester—one day a week for student project presentations, for reviews and help sessions, and for testing.
We image that there will be more lecture periods toward the beginning of the semester and more presentation and review days toward the end of the semester.
The book also assumes 1 to 2 hours of 'homework' per class period, which includes readings, assignments, study, and projects.
The book's philosophy is that as much will be learned about data science by doing team homework projects as will be learned during the lectures.
At this level (high school senior or first semester college freshman), it would be difficult for a single individual to complete these assignments alone.
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