optionalg / learner-profiles

Profiles of DataCamp learners

DataCamp Learner Profiles

Terms like "beginner" and "expert" mean different things to different people, so these learner profiles make the course's intended audience concrete. Please amend or add to these profiles as you build courses by filing an issue or pull request in the GitHub repository.

Profiles have five parts: the learner's general background, what they already know, what they think they want to do, any special needs they might have, and how the course will help them. To make the last part of the profiles concrete, these profiles describe how DataCamp's "Introduction to the Unix Shell" will (or won't) help each learner.

Anya Mid-career programmer Wants to analyze network traffic	Catalina Statistics professor Wants courses for her students	Jasmine Early career policy researcher Wants to teach
Mohan Graduate student Wants quick solutions	Pina Curriculum developer Wants to maintain courses	Thanh Statistician Wants to build tools
Yngve Financial analyst Wants to stay competitive

Anya

1. Anya, 40, has lived in Kraków her whole life. She is raising two teenage children on her own, and as the time nears for them to leave home, she is contemplating a career change.

2. Anya has been programming since she was a teenager. She is comfortable using C, Java, Ruby, SQL, Unix, and Windows, but has no prior experience with Python or R, and has not done mathematics since her undergraduate calculus class.

3. Anya would like to learn how to analyze Internet and telecoms traffic data, both so that she can tell if the work her team is doing is making things better and because she would like to try something new.

4. Anya can only study for an hour in the morning before her kids wake up. (She has found that she is usually too tired at the end of the day for things to stick.)

5. DataCamp's "Introduction to the Unix Shell" will not teach Anya anything that she doesn't already know.

Catalina

1. Catalina, 56, is a professor of statistics in Chile. She teaches graduate and undergraduate courses in her own department, and also manages a course for approximately 300 medical students on stats and data analysis.

2. Catalina's research focuses on analysis of spatial data in epidemiology. She has used Excel and SAS for years, and recently started working in R. She is excited by its possibilities, but is the only one in her department who has switched.

3. Catalina would like to start teaching R in the course for medical students, but does not have time to develop all the materials herself.

4. Catalina and her students have a good understanding of English, but most of their computers are slower and have less memory than top-of-the-line machines in Europe and North America.

5. This course and others like it could be the "flipped" part of Catalina's flipped classroom. However, the university has to pay commercial rates for bandwidth, so she would prefer to use materials that can handed out on USB drives and run locally on learners' machines.

Jasmine

1. Jasmine, 28, did a commerce degree at the University of North Carolina, and then an MBA at Georgia State. In the three years since completing it, she has been doing health insurance policy research for an underwriter.

2. Jasmine did a stats class as an undergrad and another in grad school (which covered almost exactly the same material). She uses Excel every day, and is comfortable doing simple operations in SAS.

3. Jasmine would like to start teaching data analysis at her alma mater. Her boss has given her two afternoons a week of work release to do this, and she wants to level up her statistical and computing skills as quickly as she can.

4. Jasmine is partially deaf, and strongly prefers written and visual material to spoken material.

5. This course will give Jasmine a basic understanding of the Unix shell so that she can help her students solve the problems they encounter using the university's systems in their statistics courses.

Mohan

1. Mohan, 23, is a graduate student in urban planning in Mumbai. His thesis work focuses on predicting traffic disruption caused by construction.

2. Mohan did two programming classes as an undergraduate, both using VB.net. He's good at building ten-page programs, but doesn't understand that larger ones aren't just more of the same. He also did two statistics classes, neither of which covered any methods invented after 1970.

3. Mohan doesn't want to learn data science: he wants to solve homework problems in his urban planning courses, some of which are poorly specified and rely on data sets that the professor has never actually explored.

4. He doesn't have the time or the patience to work patiently through a sequence of courses. Instead, he wants (and needs) to jump directly to a cookbook method that will give him the right answer.

5. This course won't be of much use to Mohan, as it doesn't include code he can copy, paste, and tweak to solve particular homework questions.

Pina

1. Pina, 31, has a PhD in behavioral economics, and joined DataCamp eight months ago as a curriculum developer

2. Pina used a wide variety of statistical and machine learning methods in her research. She has used Python, R, MATLAB, SAS, Stata, SQL, and a variety of other tools, but prefers R these days.

3. Pina spends half her time developing new DataCamp courses and the other half fixing and upgrading ones that have already been deployed.

4. Pina's partner is doing a second post-doc in museum studies, so Pina wants to be able to travel frequently and work from wherever she finds herself.

5. This course won't teach Pina anything she doesn't already know about Unix, but she may pick up a couple of ideas from it about teaching. The most important thing for her is having documentation around the course that will help her make fixes and changes without breaking continuity.

Thanh

1. Thanh, 35, has an undergraduate degree in psychology with a minor in statistics. He now works for the Quebec Ministry of Education, where he helps administer programs for children with learning disabilities.

2. Thanh uses classical statistical methods every day. He taught himself the basics of R, and then used DataCamp's courses to learn more.

3. Thanh is about to join a consortium that is analyzing different approaches to special education. As part of this, he wants to start building tools that other consortium members can use.

4. Thanh is fluent in Vietnamese and French, but only has high school English (supplemented by a solid technical vocabulary).

5. This course will show Thanh how to build shell scripts, and is a step toward building robust software.

Yngve

1. Yngve, 33, did a PhD in astrophysics, then switched careers to financial analysis. He now works a major shipping company in Sweden, where his job is to forecast losses due to delays, accidents, and piracy.

2. Yngve works with large, heterogeneous datasets every day using a variety of statistical methods and tools. He is an expert MATLAB user, and has taught himself a bit of R (mostly so that he can use ggplot2).

3. Yngve wants to stay on the leading edge of his field, so he is looking for advanced training.

4. Yngve's friends would describe him as "very focused": he always wants to dive straight into the content of a course, and has no interest in getting to know his instructor or fellow students.

5. This course is not suitable Yngve, since he learned everything in it while still an undergrad.

---

(Images courtesy of RoboHash.)