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Data Analysis Replication & Creative Extension
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Related lectures (35)
Introduction to Applied Data Analysis
Introduces the Applied Data Analysis course, focusing on data science tools and project work.
Collaborative Data Science: Tools and Techniques
Introduces collaborative data science tools like Git and Docker, emphasizing teamwork and practical exercises for effective learning.
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.
Data Wrangling with Hive: Managing Big Data Efficiently
Covers data wrangling techniques using Apache Hive for efficient big data management.
How People Learn II: Course Introduction and Overview
Introduces the course 'How People Learn II', focusing on educational concepts and practical applications in project-based learning.
Big Data Ecosystems: Technologies and Challenges
Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.
Principal Component Analysis: Dimension Reduction
Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.
Data Science Fundamentals
Covers the fundamentals of data science, the scientific method evolution, the role of a data scientist, and the significance of data as the new oil.
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 Science Fundamentals
Covers the fundamentals of data science, emphasizing breadth over depth and practical application in machine learning and data analysis.
Critical Data Studies: Reproducibility and Renku
Explores the significance of reproducibility in data science and introduces Renku, a platform for managing data-driven projects.
FAQ Course Design
MOOC: The Thymio robot as a tool for discovering digital science
Covers common questions about course content, target audience, and resources.
Project Management Essentials: Scope, Time, and Cost
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Covers essential project management aspects like scope, time, and cost, along with resource allocation, schedule optimization, and risk management.
Project Management & Innovation: Industrial Insights
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Covers industrial project management, scope and time management, risk management, and product development basics.
Digital Humanities Workflow
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Explores the workflow in Digital Humanities, emphasizing data collection and visualization.
Project Configuration Workshop
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Covers the configuration of a project management tool and defining project structures, geographical locations, and risks.
Air Pollution Data Analysis
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Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.
Master's Programs Overview: Statistics and Microengineering
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Outlines the master's programs in Statistics and Microengineering at EPFL, detailing their structure, courses, and career opportunities.
Data Science for Engineers: Part 2
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Explores data manipulation, exploration, and visualization in data science projects using Python.
Project Management: Planning and Scheduling
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Covers project management methodologies, network calculation, resource allocation, and monitoring-control in project planning and scheduling.
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