Below are various bioinformatics tools and software. Some are used in the course, some represented extensions from material taught in the course, and others are independent of the course itself (but relevant to bioinformatics!).
General Information Technology (IT) Tools
  1. Cloud workplace tools: oogle Drive + Forms +  Doodle + Trello + HipChat.
  2. Lab "internet of things" tools:  IFTTT and NEST.
  3. General forum for IT: Stackoverflow
  4. My lecture introducing R, RStudio, GIT and Unix here (knitr R presentation)

Bioinformatics ResourcesOn-line Courses
  1. MIT OpenCourseWare (fantastic resource of courses for computer science, statistics, systems biology, cancer, medicine, bioinformatics, … …. …)
  2. CodeSchool R Course (free with registration)
  3. JBStatistics video series on YouTube (some nice examples for Z scorest-distributionOne-mean t-test, binomial distributionhypergeometric distribution, chi-squared test
  4. Learn Statistics video series from Mike Marin (R specific)
  5. Great Course from J Akey at University of Washington – Genome Sciences
  6. EBI Sponsored On-line Courses (coverage of genomics technologies)
Machine Learning
  1. Undergraduate Machine Learning (Nando de Freitas, UBC)
  2. Graduate Machine Learning (Nando de Freitas, UBC)
  3. Deep Learning (Nando de Freitas, UBC)
-omic projects
  1. The Cancer Genome Atlas (TCGA)
  2. TCGA Data Portal
  3. International Cancer Genome Consortium (ICGC)
  4. ICGC Data Portal
  5. UCSC Cancer Genomics Hub
Bioinformatics Tools
  1. PubMed (with a quick tour of European PubMed via an EBI video)
  2. Google Scholar
  3. National Centre for Biotechnology Information (NCBI) 
  4. European Bioinformatics Institute (EBI) with a video touring its resources
  5. UCSC Genome Browser
  6. UCSC Cancer Browser
  7. Integrative Genomics Viewer (IGV)

ProgrammingA survey of different programming languages and their “raison d’etre”The R Language
  1. R
  2. R Studio
  3. Bioconductor
  4. Bioinformatics and Computational Biology Solutions Using R and Bioconductor
  5. R Manuals
  6. R Metabook
  7. R Inferno
  8. Advanced R (Good clean coverage of R)
  9. Google’s R Style Guide
  10. CodeSchool R Course (free with registration)
  11. A second on-line course for R basics from Datacamp.
  12. An on-line course sponsored by O’Reilly Publishers Inc. for R basics.
  13. Compilations of tutorials here and here
  14. R cheat sheet
  15. A catalogue of BioC packages
  1. Python, the programming language
  2. A beginner’s guide to programming (with Python)
  3. Interactive Development Environment: Thonny (Python 3.5 comes with it)
  4. Alternative IDE but very hard to install: PyScripter (the textbook shows examples with it but that doesn’t really matter)
  5. On-line Python shell
  6. How to think like a computer scientist (via Python): A tutorial/textbook for beginners with Python. 
  7. The BioPython Project
Cloud Computing
  1. Amazon Cloud Computing
  2. Illumina Basespace Cloud Computing
  3. Google Genomics
Code repositories
  1. GIT (Git Manual)
  2. Github
  3. BitBucket
  4. Google Code
NGS analyses
  1. Galaxy
  2. Introduction to High Throughput Sequence Analysis in R/Bioconductor
  3. Illumina Sequencing in depth tutorial
  4. Sequencing by Synthesis (movie top right)
  5. EBI course on Next Generation Sequencing
  6. EMBO course on NGS Data Analysis
  7. Canadian Bioinformatics Workshop of NGS Data Analysis