Lectures related to Data Sources: Surveys and Techniques

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.

Metropolis-Hastings Algorithm: Implementation and Case Study

Explores the Metropolis-Hastings algorithm and its application in a transportation mode choice model.

Excel Upgrade: Advanced Functions and Data Analysis

Covers advanced Excel functions and data analysis techniques, including automatic recording and using Solver.

Research Methodology: Introduction

Covers research methodology, including journal production, anthropology, ethnography, survey methods, and digital studies.

Management of Fever in Children: Measurement and Examples

Explores the measurement and operationalization of outcomes in managing fever in children under five through examples and data collection approaches.

Data Science Essentials

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

Google Analytics 4: Understand & set up GA4

Introduces Google Analytics 4 and guides on setting it up for WordPress websites, emphasizing key differences and event tracking.

Data Issues in Research

Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Data Wrangling with Hive: Managing Big Data Efficiently

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

Data Analysis to AI and ML, Social Media

Explores the evolution from data analysis to AI and ML, emphasizing big data, machine learning, and social media interaction.

Atomistic Machine Learning: Physics and Data

Explores Atomistic Machine Learning, integrating physical principles into models to predict molecular properties accurately.

Data Analysis: KMnO4 Concentrations

Covers the analysis of KMnO4 concentrations using data from a CSV file.

Logistic Regression: Vegetation Prediction

Explores logistic regression for predicting vegetation proportions in the Amazon region through remote sensing data analysis.

Quantitative Surveys: Mobility and Urbanism MOOC: Mobility and urban planning

Explores quantitative survey methods in mobility and urbanism, including traffic counts and public transport surveys, complemented by qualitative approaches.

Introduction to Spark Runtime Architecture

Introduces Apache Spark, covering its architecture, RDDs, transformations, actions, fault tolerance, deployment options, and practical exercises in Jupyter notebooks.

Advanced Spark Optimization Techniques: Managing Big Data

Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.

Urban Restructuring in African Cities

Covers urban restructuring in African cities, emphasizing political will, participatory approaches, and social considerations.

Data Preparedness: Improving Response through Information Management MOOC: A Resilient Future: Science and Technology for Disaster Risk Reduction

Emphasizes the importance of data preparedness in disaster response and explores strategies for addressing information gaps and overloads.

Introduction to Data Stream Processing: Concepts and Applications

Covers the principles of data stream processing and its applications in real-time data analysis.