After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
This DataCamp course has been developed for the use of University of Helsinki by Tuomo Nieminen and Emma Kämäräinen, under the supervision of adj. prof. Kimmo Vehkalahti. The corresponding HY course is titled Introduction to Open Data Science (IODS). The core themes of the course are open data, reproduciple research and data science.
Prerequisites
There are no prerequisites for this course
Curriculum
Course outline
1
Regression and model validation
Data wrangling, simple regression, multiple regression, regression diagnostics
- Reading data from the web100 XP
- Scaling variables100 XP
- Combining variables100 XP
- Selecting columns100 XP
- Modifying column names100 XP
- Excluding observations100 XP
- Visualizations with ggplot2100 XP
- Exploring a data frame100 XP
- Simple regression100 XP
- Video: Linear regression50 XP
- Multiple regression100 XP
- Graphical model validation100 XP
- Video: Model validation50 XP
- Making predictions100 XP
2
Logistic regression
Regression for binary outcomes, training and testing a (predictive) model, cross-validation
3
Clustering and classification
Datasets in R, Linear Discriminant Analysis (LDA) and K-means clustering
4
Dimensionality reduction techniques
Principal component analysis (PCA), Correspondence analysis (CA)
5
Analysis of longitudinal data
Graphical Displays and Summary Measure Approach, Linear Mixed Effects Models for Normal Response Variables
R
Helsinki Open Data Science
Course
Complete
