1) Python
2) R
4) SQL (sqldf package on R or Sequel Pro)
5) Mirador for quick data visualization and statistics (also caravel from AirBnB, Trifacta Data Wrangler, plotly, Lyra, Shiny R, Bokeh Python)
Also tensorflow in the browser
6) Weka for quick machine learning and Orange for quick machine learning and visual programming (also rattle package in R)
8) High performance computing and distributed computing (Spark, Hadoop, Scala)
9) Slack (for team communication)
10) Github or bitbucket (for version control and issue tracking)
11) NoSQL, Scala/Spark and Hadoop
12) Trello for time management
13) Data sharing (AWS or Dropbox)
14) Reproducible data science using Jupyter notebooks
15) Developer documentation using Doxygen
16) Docker for containerized data science (link)
17) Virtual machines (VirtualBox) and run Ubuntu UNIX in the VM
Download the Ubuntu ISO file here
18) Configuration as code (AirFlow)
19) Automated machine learning (TPOT, auto-sklearn)
20) Reproducible research using knitr and rmarkdown