Concept

RStudio

Related lectures (19)

Introduction to R Programming for Genetics & Genomics

Introduces a course on Genetics & Genomics, focusing on R programming with interactive exercises.

R Programming: Conditions, Loops, Functions & Graphics

Covers conditions, loops, functions, and graphics in R programming with practical examples.

Introduces functions in Python, covering predefined and user-defined functions, formal and effective parameters, and the importance of docstrings.

Experimental Research Design: T-Test Analysis

Explores digital lesson development, experimental research, t-tests, ANOVA, and statistical analysis using R.

Python Programming Basics

Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.

Recursive Functions: Examples and Applications

Explores recursive functions, including factorials and Fibonacci sequences, and their scope and namespaces.

Air Pollution Data Analysis

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

Introduction to Continuum Mechanics

Covers scaling, mathematical modeling, tensor notation, and Python exercises in Jupyter notebooks.

Error Analysis and Interpolation

Explores error analysis and limitations in interpolation on evenly distributed nodes.

Floating Point Representation in Computers

Covers the representation of real numbers in a computer using floating point representation and the dangers of significant digit cancellation.

Boolean Types and Control Structures

Explores boolean types, logical operators, and control structures in Python, emphasizing the evaluation of expressions and the use of relational operators.

Natural Language Processing Basics

Covers the basics of Natural Language Processing, including tokenization, part-of-speech tagging, and embeddings, and explores practical applications like sentiment analysis.

Jupyter Notebooks for Numerical Analysis

Covers the transition to Python and Jupyter notebooks for Numerical Analysis at EPFL, including interactive exercises and graded tests.

Heat Equation: Diffusion and Temperature Distribution

Explores heat diffusion, temperature distribution, and thermal equilibrium in complex systems using the heat equation and Jupyter Notebook simulations.

Critical Data Studies: Reproducibility and Renku

Explores the significance of reproducibility in data science and introduces Renku, a platform for managing data-driven projects.

Numerical Analysis: Introduction to Computational Methods

Covers the basics of numerical analysis and computational methods using Python, focusing on algorithms and practical applications in mathematics.

Experimental Design and Analysis

Covers the basics of experimental design and analysis, focusing on statistical techniques like ANOVA, regression, mediation, and moderation.

Algorithmic Composition: Semester Project Milestones Log in to Mediaspace to watch this video

Covers semester project milestones in Algorithmic Composition, exploring musical concepts, technical tools, and final deliverables.

Introduction to Renku Log in to Mediaspace to watch this video

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

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