Python is an interpreted, interactive, object-oriented, extensible programming language. It provides an extraordinary combination of clarity and versatility, and is free and comprehensively ported.
Learning to work in the terminal is a good skill to have for anyone working in the computer science field. And no programmer's experience is complete without learning the version control power of Git!
PowerShell (including Windows PowerShell and PowerShell Core) is a task automation and configuration management framework from Microsoft, consisting of a command-line shell and associated scripting language built on the .NET Framework.
Terminal (also referred to as Terminal.app) is a terminal emulator included in Apple's Mac OS X operating system. It originated in Mac OS X's predecessors, NEXTSTEP and OPENSTEP, and allows the user to interact with the computer through a command line interface.
GNOME Terminal is a terminal emulator for the GNOME desktop environment written by Havoc Pennington and others. Terminal emulators allow users to execute commands using a real UNIX shell while remaining on their graphical desktop.
Git is a free & open source, distributed version control system designed to handle everything from small to very large projects with speed and efficiency.
Python and R are the most commonly used programming languages. I've included additional IDEs (Integrated Development Environments) as well, two for Python (one with a desktop GUI, the other for the terminal) and one for R.
The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much...
Provides a versatile architecture for interactive computing featuring dynamic shell, data visualization, and parallel computing capabilities.
R is a free software environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be consider.
Matplotlib is a basic data visualization tool. SciPy is a great choice for manipulating data and TensorFlow is a fantastic platform if you are interested in machine learning (especially running with Keras.io and scikit-learn).
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible.
TensorFlow is an open source software library for machine learning in various kinds of perceptual and language understanding tasks.
Below are the most commonly used databases for raw data processing power. I've included a relational database and a noSQL database for handing document driven data, particularly useful in the big-data space!
PostgreSQL is a powerful, open source object-relational database system with over 35 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance.
pgAdmin is the most popular and feature rich open source administration and development platform for 
PostgreSQL, the most advanced open source database in the world.
MongoDB is a document database with the scalability and flexibility that you want with the querying and indexing that you need
The GUI for MongoDB. Visually explore your data. Run ad hoc queries in seconds. Interact with your data with full CRUD. View and optimize your query performance. Compass empowers you to make smarter decisions about indexing, document validation, etc.
I've seen the following used frequently for data visualization on the business side. Pick one or more!
D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Enhance your decision-making by transforming diverse data sources into engaging, interactive visual insights with tools like Power BI Desktop and a web service.
Tableau helps the world’s largest organizations unleash the power of their most valuable assets: their data and their people.
Microsoft Excel, part of the 
Microsoft 365 Copilot, is Microsoft's spreadsheet application. With the Microsoft Office Fluent user interface, rich data visualization, pivot table views, and professional-looking charts are easier to create...
Some people prefer using the cloud to do their dirty data-processing work. Pick one and go for it!
Apache Hadoop is a open source software framework that supports data-intensive distributed applications licensed under the Apache v2 license. It enables applications to work with thousands of computational independent computers and petabytes of data.
The Azure cloud platform is more than 200 products and cloud services designed to help you bring new solutions to life—to solve today’s challenges and create the future. Build, run, and manage applications across multiple clouds, on-premises, and at the edge, with the tools and...
Amazon Machine Learning allows developers to use machine learning. It provides visualization tools and wizards that guide you in the process of creating machine learning (ML) models. It makes it easy to obtain predictions using simple APIs.
