Lectures related to Understanding Data Analysis

Data Visualization: Techniques, Tools & Concepts

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

Delves into the 'digital turn' in history, examining historical research using digitized newspapers and exploring text reuse, word embeddings, and data visualization.

World of Data: Visualization and Ethics

Explores data visualization's significance in communication and cognition, along with ethical considerations.

Cognitive processes for data exploration

Explores cognitive processes in data analysis, focusing on visual thinking and simplification to extract insights from data.

Visualizing Categorical Data: Methods and Examples

Explores tools for visualizing categorical data to detect patterns and trends.

Air Pollution Data Analysis

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

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.

Data Wrangling and Analysis

Covers a homework assignment on data wrangling and analysis using Python's pandas library for real-world datasets.

Recent Advances in Structural Learning for Graphical Models

Covers recent advances in structural learning for graphical models, including Gaussian models, mixed models, and extreme events.

Vectorworks: Design Suite 2022

Explores the tools and features of Vectorworks Design Suite 2022 for design and visualization.

Headline Analysis: Language Impact & Success

Explores the influence of language on headline success through real-world data analysis and statistical testing.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

LabVIEW: Data Processing and Visualization

Introduces LabVIEW for data processing and visualization, covering topics like waveform synchronization and color lookup tables.

Statistical Analysis: Hypothesis Testing and Distribution Models

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

Infiltration using the Horton method

Covers the principles and applications of infiltration using the Horton method.

Representativeness, Reliability, and Contribution

Discusses data quality evaluation, reliability, representativeness, and process contribution in Life Cycle Assessment.

Collaborative Data Science: Tools and Techniques

Introduces collaborative data science tools like Git and Docker, emphasizing teamwork and practical exercises for effective learning.

Big Data: Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, typical architecture, challenges, and technologies used to address them.

Introduction to Renku

Introduces Renku, a platform for collaborative data science, emphasizing reproducibility, shareability, reusability, and security.

Data Visualization: Principles and Practices

Emphasizes the importance of data visualization techniques and practices for effective data analysis and communication.