Reviews for Programming/Data Science courses
R for Data Science
Type: Online (book)
Source: Hadley Wickham
Time: N/A
Cost: Free
Description: This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. For example solutions please visit https://jrnold.github.io/r4ds-exercise-solutions/ and/or https://brshallo.github.io/r4ds_solutions/
Link: http://r4ds.had.co.nz/
Text Mining with R: A Tidy Approach
Type: Online (book)
Source: Julia Silge and David Robinson
Time: N/A
Cost: Free
Description: This book serves as an introduction of text mining using the tidytext package and other tidy tools in R. The functions provided by the tidytext package are relatively simple; what is important are the possible applications. Thus, this book provides compelling examples of real text mining problems.
Link: https://www.tidytextmining.com/
Mastering Shiny
Type: Online (book)
Source: Hadley Wickham
Time: N/A
Cost: Free
Description: This book is designed to take you from knowing nothing about Shiny to being an expert developer who can write large complex apps that are still maintainable and performant. You’ll gain a deep understanding of the reactive programming model that underlies Shiny, as well as building a tool box of useful techniques to solve common app challenges.
Link: https://mastering-shiny.org/
Hands-On Machine Learning with R
Type: Online (book)
Source: Bradley Boehmke and Brandon Greenwell
Time: N/A
Cost: Free
Description: This book provides hands-on modules for many of the most common machine learning methods. You will learn how to build and tune various models with R packages that have been tested and approved due to their ability to scale well.
Link: https://bradleyboehmke.github.io/HOML/
Python for analysts
Type: Online
Source: Tom Ewing (Tommo565)
Time: N/A
Cost: Free
Description: The author wrote this a couple of years ago when they first starting out with Python and their career as a data scientist. They had come from a background of SAS and Excel but discovered how easy, intuitive and powerful Python was for data analysis and data science and wanted to create their own training course to both share the awesomeness of Python with others, and also as a means to document and share their learning.
Link: https://github.com/Tommo565/python-for-analysts
Introduction To Python Programming
Type: Online
Source: Avinash Jain, The Codex
Time: 1.5 hours
Cost: Free
Description: This course is a one-stop-shop for everything you’ll need to know to get started with Python, along with a few incentives. We’ll begin with the basics of Python, learning about strings, variables, and getting to know the data types. We’ll soon move on to the loops and conditions in Python. Afterwards, we’ll discuss a bit of file manipulation and functions. By then, you’ll know all the basics of Python.
Link: https://www.udemy.com/course/pythonforbeginnersintro/?LSNPUBID=JVFxdTr9V80&ranEAID=JVFxdTr9V80&ranMID=39197&ranSiteID=JVFxdTr9V80-uu8owEoJwWMbF5_k7IDR_Q
Python Data Science Handbook
Type: Online (book)
Source: Jake VanderPlas
Time: N/A
Cost: Free
Description: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
Link: https://jakevdp.github.io/PythonDataScienceHandbook/
Think Stats: Probability and Statistics for Programmers
Type: Online (book)
Source: Allen B. Downey
Time: N/A
Cost: Free
Description: If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
Link: https://greenteapress.com/thinkstats/html/index.html
Think Bayes: Bayesian Statistics Made Simple
Type: Online (book)
Source: Allen B. Downey
Time: N/A
Cost: Free
Description: If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you’ll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you’ll begin to apply these techniques to real-world problems.
Link: https://greenteapress.com/thinkbayes/html/index.html
An Introduction to Statistical Learning with Applications in R
Type: Online (book)
Source: Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
Time: N/A
Cost: Free
Description: As the scale and scope of data collection continue to increase across virtually all fields, statistical learning has become a critical toolkit for anyone who wishes to understand data. An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning. Each chapter includes an R lab. This book is appropriate for anyone who wishes to use contemporary tools for data analysis.
Link: https://www.statlearning.com/
SQL Tutorial
Type: Online
Source: w3schools
Time: N/A
Cost: Free
Description: W3Schools create simplified and interactive learning experiences. Learning web development should be easy to understand and available for everyone, everywhere! W3Schools is a school for web developers, covering all the aspects of web development.
Link: https://www.w3schools.com/sql/
Natural Language Processing – Stanford University
Type: Online
Source: Dan Jurafsky
Time: N/A
Cost: Free
Description: A thorough introduction to the theory underpinning natural language processing tasks. A good basis for more specialised applications. Note: more recent courses from Stanford are now also available on YouTube.
Link: https://www.youtube.com/playlist?list=PLLssT5z_DsK8HbD2sPcUIDfQ7zmBarMYv
Geocomputation with R
Type: Online (book)
Source: Robin Lovelace, Jakub Nowosad, Jannes Muenchow
Time: N/A
Cost: Free
Description: This book is for people who want to analyse, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization and geospatial capabilities.
Link: https://geocompr.robinlovelace.net/
Data Camp courses
Type: Online
Source: datacamp
Time: 4 hours
Cost: £Monthly or yearly subscription approx £200
Description: Online interactive platform teaching a wide range of coding and data science courses, including python, machine learning, R, and many more. The courses can be run on your browser and are taught using videos and interactive tutorials.
Link: https://www.datacamp.com/