Lectures related to Data Collection and Analysis in Geomatics

Air Pollution Data Analysis

Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.

Statistical Analysis: Hypothesis Testing and Distribution Models

Covers statistical analysis techniques, hypothesis testing, and distribution models using R software.

Statistical Analysis: Boxplot and Normal Distribution

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Genetics: Project R #2

Explores the analysis of genotypes and variants data through a Genome-Wide Association Study, focusing on the association between genetic variants and phenotypes like height.

Statistics for Data Science: Introduction to Statistical Methods

Covers the fundamental concepts of statistics and their application in data science.

Understanding Data Analysis

Covers the fundamentals of data analysis, statistical methods, and practical applications.

Data Science Essentials: Pandas, Numpy, Matplotlib

Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Data Visualization: Techniques and Applications

Explores data visualization techniques, design impact, and interactive applications for effective information communication.

Data Analysis Techniques: Amplitude Shift Keying and Graphical Methods

Covers amplitude shift keying and various data analysis techniques using Jupyter Notebooks.

Structuring exploratory spatial data analysis

Explores the structured approach to exploratory spatial data analysis, emphasizing the importance of analytical frameworks and the Visual Seeking Mantra.

Data Visualization: Techniques, Tools & Concepts

Covers data visualization techniques, tools, and concepts for effective data representation.

Super-vision: Celebrating EPFL's Doctoral Theses History

Explores EPFL's doctoral theses history, data visualization, and the innovative D3 approach.

Economy-wide material flow analysis: from exercises to projects

Explores Economy-Wide Material Flow Analysis methodology and applications in real-world projects using Jupyter notebooks.

Visualizing Data: Techniques and Applications

Explores techniques and applications of data visualization, emphasizing the importance of effective communication and unconventional examples.

Data Science Essentials

Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.

Data Visualization & Storytelling

Delves into data physicalization, expressiveness, feminist visualization, and the balance between exploration and explanation in data visualization.

Introduction to Applied Data Analysis

Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.

Introduction to Machine Learning: Course Overview and Basics

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

PCA: Directions of Largest Variance

Covers PCA, finding directions of largest variance, data dimensionality reduction, and limitations of PCA.

Principal Component Analysis: Dimension Reduction

Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.