Why data analysis?
The power of data and the information therein is entering the heart of almost any section of society. We are discovering that processes can be better understood and controlled, predictions made, causal effects estimated and decisions optimized. Reliable results follow when studies have been appropriately designed, data carefully gathered and analyzed. Scientists and professionals stay ahead if they keep learning from their data. They add tremendously to their market value when data analytic skills merge their subject matter expertise.
We aim to provide insight in the basics of statistical research while developing the technical skills to come to results with statistical software. Blended learning with hands-on sessions on PC’s or laptops allows participants to gain firsthand experience in applying the knowledge.
Target audience and adaptive training trajectories
Our courses target professionals and the academically trained, who wish to become confident data analysts, refresh their knowledge or discover new areas of research. The program’s modular architecture facilitates flexible entry and adaptive training trajectories.
- Module 1 - Getting Started with R Software for Data Analysis
- Module 2 - Design and Analysis of Randomized Clinical Trials => This course is offered as a microcredential only.
- Module 3 - Drawing Conclusions from Data: an Introduction
- Module 4 - Getting Started with Python for Data Scientists
- Module 5 - Exploiting Sources of Variation in your Data: the ANOVA Approach
- Module 6 - Getting Started with NVivo for Qualitative Data Analysis
- Module 7 - Leverage your R Skills: Data Wrangling & Plotting with Tidyverse
- Module 8 - Dynamic Report Generation with R Markdown
- Module 9 - Explaining and Predicting Outcomes with Linear Regression
- Module 10 - Mastering R Skills: Selected Topics for Successful Programming
- Module 11 - Multilevel Analysis for Grouped and Longitudinal Data
- Module 12 - Machine Learning with Python
- Module 13 - Building Interactive Apps with Shiny© in R
- Module 14 - Artificial Neural Networks: from the Ground Up
- Module 15 - Time-to-Event Analysis (Survival) with applications to Health sciences and Industry
All information and the registration form are available on the website of the Academy for Lifelong Learning of the Faculty of Sciences (ICES, UGent)
The "KMO-portefeuille" is a support measure of the Flemish government. It offers financial support to entrepreneurs for training and consulting.
Ghent University is recognized as a service provider. This way you can save up to 30% on the registration fee for our trainings.