Data Analytics Coding Fundamentals

by Martin Monkman

Data Analytics Coding Fundamentals

The course book for BIDA302 […] Latest update: 2023-09-03 This book is based on the lessons for BIDA302, “Data Analytics Coding Fundamentals”, offered at the University of Victoria’s Continuing Studies Department. From UVic Continuing Studies website This course will explore the fundamentals of coding and scripting for Data Analytics. You will develop the ability to script and code for basic tasks in Data Analytics in common data analytic tools such as R, Python, and Excel. This will allow you to import and export data appropriately and perform fundamental data manipulations and to automate … Read more →



by Abdoul Aziz Berrada


This is a minimal example of using the bookdown package to write a book. The HTML output format for this example is bookdown::gitbook, set in the _output.yml file. [...] L’écriture de programmes (ou programmation) est une activité très créative et gratifiante. Vous pouvez écrire des programmes pour de nombreuses raisons, qu’il s’agisse de gagner votre vie, de résoudre un problème difficile d’analyse de données, de vous amuser ou d’aider quelqu’un d’autre à résoudre un problème. Ce cours part du principe que tout le monde doit savoir programmer, et qu’une fois que vous saurez programmer, vous ... Read more →


Financial Data Science

by Prof. Dr. Ryan Riordan & Teaching Assistants


This bookdown contains the teaching materials for the projectcourse Financial Data Science at the LMU Munich. The files have been set up by Lisa Kaminski. [...] Here you will find the course pages for the projectcourse Financial Data Science. The course is offered regularly in the summer term and aims at providing in-depth knowledge about the programming language Python and its most important libraries for data analysis. Furthermore, the course introduces the topic of database management and the process of retrieving, aggregating and manipulating data using SQL. Students will learn to ... Read more →


Data Analysis in Medicine and Health using R

by Kamarul Imran, Wan Nor Arifin, Tengku Muhammad Hanis Tengku Mokhtar


Data Analysis in Medicine and Health using R […] We wrote this book to help new R programming users with limited programming and statistical background. We understand the struggles they are going through to move from point-and-click statistical software such as SPSS or MS Excel to more code-centric software such as R and Python. From our experiences, frustration sets in early in learning this code-centric software. It often demotivates new users to the extent that they ditch them and return to using point-and-click statistical software. This book will minimise these struggles and gently … Read more →


Making Sense of Data with R

by Yi Shang


This is the companion book of the course ED 101 Making Sense of Data offered in the Department of Education at John Carroll University. […] Step 1: Log in to your JCU (google) email account Step 2: Click here or type the short URL: to open a new R notebook in Colab. To check if this is really an R notebook (instead of python), click on the “Runtime” tab, then click on “change runtime type.” And you should see this: Now hit “Cancel” and go back to the notebook. Try typing a line of code in the cell, such as: To run this line of code, either hit the play button: Or … Read more →


Introduction to R for Data Science: A LISA 2020 Guidebook

by Jacob D. Holster


Introduction to R for Data Science: A LISA 2020 Guidebook […] Data science is emerging as a vital skill for researchers, analysts, librarians, and others who deal with data in their personal and professional work. In essence, data science is the application of the scientific method to data for the purpose of understanding the world we live in. More specifically, data science tasks emerge from an interdisciplinary amalgam of statistical analysis, computer science, and social science research conventions. Although other programming languages such as python exceed R in general popularity, R … Read more →



by cristianbonavida


Nos propusimos trasncribir al lenguaje R y Python los apéndices del libro Pobreza y Desigualdad en América Latina de Gasparini, Cicowiez y Sosa Escudero que originalmente fueron escritos para Stata. […] Nos propusimos trasncribir al lenguaje R y Python los apéndices del libro “Pobreza y Desigualdad en América Latina” de Gasparini, Cicowiez y Sosa Escudero que originalmente fueron escritos para Stata y que permitían replicar los datos e información presentados por los autores en el texto. Cada capítulo consta de un apéndice con códigos que permiten llevar a la práctica los conceptos … Read more →


Bio Ciencia de Datos

by jp_6


Curso libre de ciencia de datos y modelos en R/Python. Este es un ejemplo mínimo del uso del paquete bookdown para escribir un libro. […] Curso abierto de ciencia de datos y modelos en R/Python. Con aplicaciones en ciencias actuariales y … Read more →



by 罗飞


R语言学习笔记 […] 作为一名10多年工作经历的公卫人,在实际工作感受越来越明显的是,公共卫生的研究对于数学,尤其是统计学的知识需求越来越大。现在看国外的文章,没有数学基础,几乎看都看不懂。使用统计学方法不可避免地又会使用到统计软件。传统的SAS, Stat 和 Spss等均有自身的优缺点。其实主要是要收费啊!! R语言从诞生到现在,不停的发展壮大,愈来愈完善,关键是开源、免费,还有各种最新的统计方法的包。在2020年新冠疫情期间,我从湖北回来后的隔离期间,学习了Python,学了2个礼拜感觉对于自己的工作来说,R好像更为实用点。之后我开始零散的学习R语言。大半年过去了,现在感觉因为没有系统的学习,知识点有点混乱,平时写代码的时候,常常会忘记一 … Read more →


Coding for Data Science 2021/22 - R part

by Michela Cameletti


Notes for the R labs of the C4DS course @ Unibg […] You are reading the lecture notes of the R lectures for the Coding for Data Science (C4DS) course at University of Bergamo (academic year 2021/22). C4DS is the first module of the course named Coding and Machine Learning (see here for more details). The C4DS R lectures are designed for students who already have a programming background thanks to the first part of the C4DS course dedicated to Python. In this part of the module we will introduce R programming language for data science (including data manipulation, data visualization and … Read more →


R Coding for Data Science - 2020/21

by Michela Cameletti


Notes for the R labs of the R4CDS course @ Unibg […] You are reading the lecture notes of the R lectures for the Coding for Data Science (C4DS) course at University of Bergamo (academic year 2020/21). R is a great programming language especially designed for statistical analysis and data visualisation. The C4DS R lectures are designed for students who already have a programming background thanks to the first part of the C4DS course dedicated to Python. In the 5 lectures dedicated to R I will present you the basics of R for data manipulation, analysis and plotting. Enjoy the journey! In the … Read more →


JavaScript for R

by John Coene

JavaScript for R

Invite JavaScript into your Data Science workflow. […] This is the online version of JavaScript for R, a book currently under development and intended for release as part of the R series by CRC Press. The R programming language has seen the integration of many languages; C, C++, Python, to name a few, can be seamlessly embedded into R so one can conveniently call code written in other languages from the R console. Little known to many, R works just as well with JavaScript—this book delves into the various ways both languages can work together. The ultimate aim of this work is to demonstrate … Read more →


R for Data Engineers

by Greg Wilson


R for Data Engineers […] Years ago, Patrick Burns wrote The R Inferno, a guide to R for those who think they are in hell. Upon first encountering the language after two decades of using Python, I thought Burns was an optimist—after all, hell has rules. I have since realized that R does too, and that they are no more confusing or contradictory than those of other programming languages. They only appear so because R draws on a tradition unfamiliar to those of us raised with derivatives of C. Counting from one, copying data rather than modifying it, lazy evaluation: to quote the other bard, these are not … Read more →


Portfolio Construction

by Jian SHEN


Portfolio construction with R […] outline: portfolio: basic portfolio concepts portfolio construction: back-testing machine learning: data clean, transform, viz, exploratory ts modeling model model evaluation math: convex optimization The R session information when compiling this book is shown below: Some basic knowledge about finance, time series analysis, optimization (linear and convex), programming (python1 or R) would be preferred. Later I will add corresponding python … Read more →


A Minimal rTorch Book

by Alfonso R. Reyes


This is a minimal tutorial about using the rTorch package to have fun while doing machine learning. This book was written with bookdown. […] Last update: Sun Oct 25 12:05:18 2020 -0500 (79503f6ee) You need couple of things to get rTorch working: Install Python Anaconda. Preferably, for 64-bits, and above Python 3.6+. I have successfully tested Anaconda under four different operating systems: Windows (Win10 and Windows Server 2008); macOS (Sierra, Mojave and Catalina); Linux (Debian, Fedora and Ubuntu); and lastly, Solaris 10. All these tests are required by CRAN. Install R, Rtools and … Read more →


Practical Data Science

by Michael Clark

Practical Data Science

The focus of this document is on data science tools and techniques in R, including basic programming knowledge, visualization practices, modeling, and more, along with exercises to practice further. In addition, the demonstrations of most content in Python is available via Jupyter notebooks. […] Michael Clark … Read more →


Programación - Desarrollo de Aplicaciones Web

by Sergio Berdiales


Programación - Desarrollo de Aplicaciones Web […] Este documento incluye mis notas personales y ejercicios prácticos de la asignatura “Programación” del primer curso del Módulo de FPII de Desarrollo de Aplicaciones Web. Este módulo lo estoy cursando en el Centro Integrado de Formación Profesional de la Universidad Laboral de Gijón (curso 2019-2010). Además de hacer los ejercicios en los lenguajes requeridos durante el curso procuraré replicarlos también en los lenguajes que habitualmente utilizo en mi actividad profesional, R y Python. Los contenidos originales sobre los que realizo mis … Read more →



by 國立臺北大學 林茂廷老師


This is a minimal example of using the bookdown package to write a book. The output format for this example is bookdown::gitbook. […] 作業 70% 期末專題 30% 學習以下的能力及知識: 基礎Python語法 經濟模型/統計模型(含機器學習)所需面對的數學問題及其求解概念 電腦數值分析求解確定及不確定狀態下的極值問題 本課程雖無電腦程式基礎要求,但建議有基本概念(R或Python均可)。 基礎數學概念: 微分/積分/梯度等 確定狀態下的極值問題: 無限制絛件/有限制條件 基礎統計概念: 隨機變數/估計式/抽樣分配等 不確定狀態下的極值問題: 無限制條件/有限制條件 1. Install Python via Anaconda 連到點Download,下載對應自己系統的版本。(請安裝Pyhton 3.X版,其中X為數字 … Read more →


Основы обучаемых алгоритмов интеллектуальных систем

by Митрохин Максим Александрович


Учебно-методическое пособие включает набор лабораторных работ по созданию алгоритмов машинного обучения для решения практических задач. В издании содержится необходимый набор теоретических сведений по методологии анализа данных и используемых алгоритмах. Выполнение работ предполагает использование языка программирования Python 3.5. Лабораторный практикум подготовлен на кафедре «Вычислительная техника» и предназначен для обучающихся по направлениям подготовки 09.03.01, 09.04.01, изучающих дисциплины «Основы интеллектуальных систем», «Интеллектуальные … Read more →


Machine Learning

by Michael Clark

Machine Learning

This document provides an introduction to machine learning for applied researchers. While conceptual in nature, demonstrations are provided for several common machine learning approaches of a supervised nature. In addition, all the R examples, which utilize the caret package, are also provided in Python via scikit-learn. […] … Read more →


Gijón Air Pollution - An exercise of visualization and forecasting

by Sergio Berdiales


Gijón Air Pollution - An exercise of visualization and forecasting […] My name is Sergio Berdiales and I am a Data Analyst with more than ten years experience in Customer Experience and Quality areas. If you want to know more about me or contact me you can visit my Linkedin profile or my Twitter account. This is my final project for the Kschool Master on Data Science (8th edition). The main objective of this project is to show I can apply the acquired knowledge during the master’s course in a practical way . The Master on Data Science of Kschool is a 230-hour course which includes Python … Read more →


Hello Py: Python 程式設計

by Pyradise


Pyradise 是專注於 Python 教學的團隊,致力於分享學習經驗,推廣資料科學,人工智慧,讓更多人能參與到這波資訊與人工智慧的學習浪潮。 專注於技術,熱衷於教學的開發者,希望透過教學,傳遞出更多想法的帽子哥。 資料科學與推廣教育的愛好者,閒暇時喜歡長跑與乒乓球;是 2017 iT邦幫忙鐵人賽 Big Data 組冠軍。 前端工程師與設計師。 … Read more →


認識 R 的美好

by 郭耀仁


是郭耀仁,資料科學與推廣教育的愛好者,喜歡使用 R 語言與 Python 做資料科學應用,在台大資工系統訓練班開設多門 R 語言與 Python 的相關課程,亦與企業合作提供客製化的內訓課程;同時也是一個超棒的中文資料科學專欄 DataInPoint 的主編;這個專欄與波士頓的資料科學教學團隊 DataCamp 有行銷合作(Affiliate Marketing)。 如果您有 R 語言、Python、資料科學、教學、專案或顧問的需求,可以 email 與我聯絡 R 語言是一個高階的統計程式語言,她在 2017 IEEE 調查中排名位於第 6 名,1是以資料分析為主要目的程式語言中的最高位。其他熟為人知的像是 Matlab 排名在第 15 名、SQL 排名在第 23 名、 Julia … Read more →



by Miao YU


This is notes from yufree […] 这里的笔记主要来自于公开课笔记与相关教材的读书笔记,主题相对分散,但这些知识应该为当今科研人员的基本技能。 首先科研人员要有一定的数学与统计学功底,这是最最基本的工具学科。微积分、线性代数与数值方法是必须的数学工具,统计学工具则至少明白如何进行统计推断与预测。其余的要看应用,例如数论对密码学而言就是基础。 然后就是编程技能,编程方面首先要熟悉编程的思维方法,例如递归、迭代、条件语句等,也就是知道机器怎么运转。其次就是掌握一门高级语言,例如R、python或matlab,这样你可以快速实现自己的想法。 之后就是模型思维,懂得将实际问题抽象成一个概念问题或统计问题或仿真问 … Read more →


Climate Change Impact Assessment: A practical walk-through

by Conor I. Anderson and Karen L. Smith


A lab manual for students of Climate Change Impact Assessment […] This book is an open source document, hosted on GitLab (project page), and published using GitLab Pages, where you are probably reading it now. The book is automatically updated and republished every time changes are committed to the project, using the GitLab multi runner CI engine, and a Docker image with a distribution of Miniconda, including Python 3 and R. The book is built using the bookdown package (Y. Xie 2023) in R, and pandoc. Most of the code is executed in Python from within R using the reticulate package (Ushey, … Read more →




Main web site for Statistical Thinking for the 21st Century A commercially published version of this book (with an expanded version of Chapter 17) is now available from Princeton University Press: Statistical Thinking: Analyzing Data in an Uncertain World The open source version of the book is available in English and Spanish. Code to generate all of the figures and tables from the commercial version of the book is available in Python and R. Companions to the book for statistical programming are available for Python and R This project is maintained by statsthinking21 Hosted on GitHub Pages — … Read more →