First training course on advanced data analytics (basic level) Gdańsk, February 6-9, 2024
From February 6-9, 2024, Gdańsk hosted the first training course on advanced data analytics (basic level) as part of the AdTrans project. This comprehensive course was designed to equip academic teachers with foundational skills in data analysis, tailored specifically for the fields of transportation and mobility. Here is an outline of the sessions:
Session 1: Introduction to Data Analysis
- Overview of Data Analysis
- Importance of Data-Driven Decision Making
- Basic Concepts: Data, Variables, Types of Data
- Engineering Examples
Session 2: Data Collection Methods
- Types of Data Sources
- Sampling Techniques and Their Impact on Study Types
- Case Studies on Data Collection in Engineering Projects
Session 3: Software Presentation
- Main Functions of SPSS (Statistical Package for the Social Sciences)
- Practical Work with SPSS
Session 4: Data Pre-processing and Data Quality
- Techniques for Cleaning and Handling Missing Data
- Outlier Detection and Treatment
- Duplicate Data Management
- Data Normalization and Scaling
- Practical Work with SPSS
Session 5: Exploratory Data Analysis
- Descriptive Statistics
- Data Visualization Techniques (Using Tools like Python, R, Excel, or SPSS)
- Analyzing Descriptive Statistics with SPSS
- Case Studies: Interpreting Data Graphs in Engineering
Session 6: Statistical Methods for Engineers
- Probability Distributions
- Estimators and Confidence Intervals
- Hypothesis Testing
- Engineering Examples
- Case Studies with SPSS (Select Method and Interpret Results)
Session 7: Regression Analysis for Engineers
- Linear and Multilinear Regression Analysis in Engineering Applications
- Logistic Regression
- Case Studies with SPSS (Select Method and Interpret Results)
Session 8: Practical Exercises
This intensive training course was attended by over twenty academic teachers from Austria, the Czech Republic, and Poland. Participants gained hands-on experience with SPSS, enhancing their ability to apply advanced data analysis techniques in their teaching and research. The course aimed to build a strong foundation in data analytics, enabling educators to foster a deeper understanding of STEM subjects among their students, particularly in the context of transportation and mobility.
