Optimizing for digital learning

Course Creation at DataCamp

Kelsey McNeillie

Instructor Success Manager

Online vs. offline learning

One-sided engagement
Different learner demographics
Learners fit learning around busy schedule

Bar plot showing that nearly 60% of DataCamp learners are working professionals, approximately 25% are learners, around 12% are academics, and the rest are classified as other

Bar plot showing around 45% of DataCamp learners are learning to advance their current career, around 35% are looking for a new career, about 15% are interested in data science, and less than 5% are using DataCamp for school

course description

Prerequisites

Identify learners with optimal qualifications
- Select 1 - 3 prerequisites
- Introductory courses may have fewer
- Case studies and advanced courses may have more

Biomedical Image Analysis course

Cleaning Data in R course

Screenshot of the prerequisite course for Biomedical Image Analysis, Intermediate Python

Screenshot of the prerequisite courses for Cleaning Data in R: Joining Data with dplyr and Introduction to Data Visualization with ggplot2

Course Roadmap

Screen Shot of the course roadmap available on Trello

Analogy: a similarity or comparison between two objects

R packages are like apps, and CRAN is like the App Store

Heuristic: a mental shortcut that eases the cognitive load of information

Signal and noise - it's like trying to hear someone across a crowded room. Remove the noise and you can understand easily what they are telling you.

Let's practice!

Course Creation at DataCamp