Fact-checked by Grok 2 weeks ago

CoCalc

CoCalc is a web-based platform designed for collaborative computation and , allowing users to work in real-time on documents and code across disciplines like mathematics, programming, and scientific research. Developed by , Inc., a founded in 2015 by mathematician and software developer William Stein, CoCalc originated as SageMathCloud before rebranding to reflect its expanded capabilities beyond SageMath-specific tools. It targets educators, students, and researchers, offering optional scalable compute servers with GPU acceleration as enhancements for demanding computational tasks. Key features include support for Jupyter Notebooks, LaTeX documents, SageMath worksheets, and a full Linux terminal, along with pre-installed environments for languages and libraries such as , , , , and . The platform integrates generative AI tools like for enhanced productivity and offers a course management system with automated grading via nbgrader, facilitating teaching workflows in computational subjects. Real-time synchronization, version history, and secure ensure seamless , making CoCalc a versatile tool for both individual projects and group-based learning.

History

Founding

CoCalc, originally known as SageMathCloud, was founded by mathematician William Stein in April 2013. Stein, a professor at the and creator of the open-source mathematics software system, launched the platform to provide a cloud-based environment for running and other open-source computational tools. This initiative stemmed from his frustrations with proprietary mathematical software, such as and Mathematica, which he encountered during his graduate studies at UC Berkeley and early academic career; these systems were expensive, closed-source, and difficult to integrate or understand internally. Stein aimed to create an accessible alternative that allowed users to engage with open-source mathematics software without the barriers of local installation or maintenance. The initial purpose of SageMathCloud was to serve as a hosted platform emphasizing collaborative access to tools, enabling real-time editing and sharing among users via web browsers. Shortly after its launch, the platform integrated as its core component, alongside basic cloud hosting features like file management, terminals, and support for document preparation. This addressed a key stagnation in SageMath's adoption since 2011, where installation difficulties had hindered growth, particularly for students and educators. Early development focused on building a browser-based desktop environment using technologies such as and , initially hosted on servers and Google Virtual Machines. In February 2015, established , Inc. as an independent Seattle-based startup to sustain and advance the platform's development. The company was formed to support the open-source mathematical software community through sustainable funding models, allowing to evolve beyond its academic origins while maintaining its commitment to free and collaborative computational resources.

Rebranding and Expansion

On May 20, 2017, SageMathCloud was rebranded to CoCalc, short for Collaborative Calculation in the Cloud, to better represent its expanding capabilities beyond the original focus on and to emphasize collaborative computing features. With the 2017 rebranding, CoCalc broadened its language support to include prominent environments like and , alongside Jupyter notebooks, enabling broader applications in and statistics. Around 2020, the platform introduced on-premises deployment options, allowing organizations to host CoCalc on their own clusters for enhanced data control and customization. By 2023–2024, CoCalc integrated AI assistants powered by large language models such as OpenAI's , Google's , Anthropic's Claude, and , facilitating code generation, error correction, and document summarization directly within the interface. User adoption grew steadily, with partnerships forming in , including a 2025 collaboration with to support quantum computing curricula through CUDA-Q academic materials. To address scalability, CoCalc updated its default environment to 24.04 in 2025, while maintaining support for 22.04 until mid-year, and enhanced compute servers with features like idle timeouts and spending limits for efficient resource management. CoCalc's development is maintained by SageMath, Inc., an independent Seattle-based company founded in 2015, which continues to contribute to its open-source components, including a shift to Kubernetes-based infrastructure for improved robustness and scaling.

Features

Computational Tools

CoCalc provides robust support for , an open-source mathematical software system that integrates numerous existing packages to facilitate computations in , , , , and related fields. As the foundational tool in CoCalc, enables users to perform symbolic and numerical calculations through interactive worksheets and Jupyter notebooks, with seamless access to its full capabilities without local installation. Jupyter notebooks in CoCalc offer enhanced functionality beyond standard implementations, including support for multiple kernels such as , , , , and , allowing users to execute code in diverse languages within the same document. A key enhancement is high-precision edit history via TimeTravel, which tracks thousands of revisions for easy navigation, recovery, and collaboration on notebook content. The platform's editor supports real-time compilation of documents, providing side-by-side previews with forward and inverse search for efficient editing and navigation. It includes export options to PDF and other formats, along with integration for embedding executable code from tools like SageTeX and PythonTeX to generate dynamic figures and computations directly in documents. Additional computational tools encompass terminals for command-line operations in a full 24.04 environment (as of June 2025), synchronized across users, and versatile code editors supporting dozens of programming languages including , , , , , and more. For compute-intensive tasks, CoCalc offers access to GPUs such as A100 and via dedicated compute servers, enabling accelerated processing for , simulations, and parallel computations in Jupyter notebooks or terminals. These tools support real-time collaboration, allowing multiple users to interact simultaneously.

Collaboration and Productivity

CoCalc enables real-time synchronous editing, allowing multiple users to collaborate simultaneously on Jupyter notebooks, LaTeX documents, and code files, with cursors and presence indicators visible to all participants for seamless interaction. Changes are synchronized instantly across users, merging edits in real time to minimize disruptions, while the platform's custom implementation handles conflict resolution through operational transformations and timestamp-based patching. Integrated version control via TimeTravel allows users to browse, compare, and revert to any historical state of files, ensuring robust tracking of collaborative changes without external tools. The platform incorporates built-in and commenting systems directly within projects and files, facilitating discussions without exiting the workspace. Side s support formatting, equations, image sharing, and @mentions for notifications, enabling focused conversations tied to specific content like cells or documents. This integration promotes efficient teamwork by keeping communication contextual and persistent across sessions. Productivity is enhanced through features such as hierarchical folders for organizing files, automated ZFS-based snapshots taken every few minutes for quick recovery, and TimeTravel for navigating file histories. A collaborative provides an infinite canvas for visual ideation, incorporating Jupyter code cells for live computations, and support, , freehand sketching, integrated , and time-travel versioning to foster dynamic group brainstorming. Additionally, the AI assistant, introduced in 2023, leverages large language models like OpenAI's , Google's , Anthropic's Claude, and to offer context-aware code suggestions, error explanations, and automated fixes directly within s and editors, streamlining development workflows. For educational settings, CoCalc's course management tools empower instructors with interfaces for distributing assignments and handouts to students via shared projects, automatically creating individual folders to prevent cross-access. Grading is facilitated through nbgrader integration, which supports automated and manual of Jupyter-based assignments, with scores and stored in GRADE.md files; features like peer grading randomly redistribute submissions for review, reducing instructor workload while maintaining accountability. Once graded, assignments can be returned to students with comments, ensuring a closed-loop entirely within the .

Technical Architecture

Cloud Infrastructure

CoCalc's core architecture relies on for container orchestration, which facilitates the scalable deployment of such as compute nodes and distributed storage systems. This setup allows for efficient management of containerized workloads, enabling horizontal by replicating pods for components like the services that handle user connections and . For instance, the hub-websocket and hub-proxy services can be configured with multiple replicas—typically around six for supporting up to 200 active users—to distribute load effectively across the cluster based on active user demand. The platform hosts its services on major cloud providers, including (GCP) via Google Kubernetes Engine (GKE), (AWS) through Elastic Kubernetes Service (EKS), and specialized providers like Hyperstack for GPU-intensive workloads. Users can provision powerful servers with configurable resources, such as up to over 400 CPU cores, more than 10,000 GB of RAM, and GPU options ranging from single T4 units to clusters of eight GPUs, supporting tasks and handling large datasets in fields like and scientific simulations. These resources are accessible via compute servers that integrate seamlessly with CoCalc projects, allowing dynamic scaling of CPU and RAM when idle to optimize costs. As of January 2025, support for NVIDIA Multi-Instance GPU (MIG) enables partitioning of GPUs for more efficient parallel workloads. Data management in CoCalc emphasizes reliability through features like frequent snapshots of project files, captured every couple of minutes to provide without consuming space, effectively offering unlimited snapshot storage. Automatic backups occur periodically to off-site encrypted storage, ensuring data durability, while functionality records edit histories for most types. with external storage is achieved via the CoCalc Cloud File System, built on JuiceFS and , which provides POSIX-compliant access to unlimited storage volumes that can be mounted across multiple compute servers and projects for seamless and persistence. Performance optimizations focus on load balancing and tailored for multi-user environments, with Kubernetes-native tools managing replication based on active user demand rather than total registrations. NGINX ingress controllers with multiple replicas distribute incoming traffic across nodes, while project quotas—such as 2 memory and 1 CPU per with overcommit ratios of 1:10 for memory and 1:20 for CPU—prevent and enable efficient scheduling. These configurations, refined through ongoing updates as of , support high concurrency in collaborative settings without compromising responsiveness.

Security and Deployment Options

CoCalc implements robust security measures to protect user data and ensure operational integrity. The platform is SOC 2 compliant, adhering to standards for data security, availability, processing integrity, confidentiality, and privacy. Additionally, CoCalc complies with the General Data Protection Regulation (GDPR), committing to notify the relevant Supervisory Authority within 72 hours of discovering a and informing affected users if there is a high risk to their rights. Data is encrypted both at rest in storage and backups, as well as in transit using and SSL/TLS protocols for all communications. Firewalls and access controls further safeguard against unauthorized access, though the platform notes that no system can guarantee absolute security. User authentication is supported through (SSO) options, including SAML and OAuth2, enabling seamless integration with existing identity providers. For collaborative environments, CoCalc provides granular access controls via project permissions, where owners can designate collaborators with specific read, write, or owner roles to manage file and resource access. Student projects can be restricted to prevent external , upgrades, or file downloads, enhancing focus and in educational settings. Activity is tracked through project logs, which record timelines of actions such as file opens, edits, and downloads, including timestamps and user details for auditing purposes. Deployment options offer flexibility for different organizational needs. The primary SaaS cloud version is hosted on CoCalc's infrastructure, providing immediate access without setup. For private hosting, CoCalc OnPrem enables on-premises installation on user-managed clusters using charts, allowing full control over data and resources in air-gapped or VPN-isolated environments. This self-hosted variant, which supports for component deployment, was developed to meet heightened privacy requirements and can integrate with internal services like . Hybrid setups combine the cloud with on-premises compute servers, where users connect personal hardware or virtual machines to a CoCalc project for enhanced performance while maintaining collaboration. Recent enhancements include the introduction of WireGuard-based encrypted VPN integration for compute servers in May 2024, enabling secure, direct communication between servers within the same project without relying on public routes. CoCalc's features, such as tunable integrations for custom GPU usage, support secure processing by allowing on-premises execution to keep sensitive computations isolated.

Applications

In Education

CoCalc has been widely adopted in educational settings for delivering interactive courses in and programming, enabling instructors to facilitate through shared Jupyter Notebooks and Sage Worksheets. In environments, students can engage directly with computational tools without local installations, allowing seamless interaction during lectures and hands-on activities, such as exploring mathematical concepts or coding exercises in and . The platform's course management system supports educators in creating and distributing assignments, with built-in capabilities for auto-grading code submissions using tools like nbgrader, which automates evaluation of Jupyter-based exercises. This is particularly valuable in subjects like and , where real-time feedback on student work—via synchronized editing and side-chat features—helps instructors provide immediate guidance and fosters iterative learning. CoCalc's integration into university curricula is evident in courses leveraging for advanced , such as introductory mathematical software classes at institutions like the (e.g., Math 157 in 2023), and Python programming modules at . The Institute for Computational and Experimental Research in Mathematics (ICERM) has utilized CoCalc as a software-as-a-service offering for students in U.S. universities and colleges as of 2025. As of 2025, free trial projects remain available to educators, enabling initial classroom use without cost barriers. A key benefit of CoCalc in education is its no-install access, which eliminates hardware and software setup requirements, thereby reducing participation barriers for students in under-resourced schools or regions with limited computing infrastructure. This accessibility promotes equity in STEM education by allowing focus on conceptual understanding and problem-solving rather than technical hurdles.

In Research and Development

CoCalc facilitates research workflows in mathematics, physics, and data analysis by integrating tools such as Jupyter Notebooks for reproducible experiments and SageMath for symbolic computation. In mathematics, researchers utilize SageMath's capabilities for tasks like solving differential equations and visualizing 3D graphics within collaborative worksheets. For physics simulations, such as calculating hydrogen energy levels via the Bohr equation or Monte Carlo studies of ferro-magnetism using the Ising model, CoCalc's environment supports precise numerical modeling and data visualization. Data analysis workflows benefit from Python, R, and Julia integrations, enabling statistical methods for processing climate datasets or quantum computing algorithms. In , CoCalc supports collaborative coding among teams through real-time synchronization of files and integration with systems like . Developers can access full Git functionality via the Linux Terminal, allowing seamless connections to repositories on , , or for and code versioning. Additionally, GPU access via dedicated compute servers enables training models with frameworks such as and , offering options from T4 to multiple H100 GPUs for accelerated computations. Adoption in academic research includes neural network simulations and quantum algorithm implementations, as demonstrated in public projects leveraging CoCalc's GPU resources since 2023. In industry, CoCalc aids prototyping through scalable compute environments, with case studies highlighting its use for in tasks, such as training generative models on GPU-backed servers. By 2025, enhancements like Kubernetes-based deployments support scalability for large research teams, accommodating hundreds of collaborators on complex projects. Key advantages include sharing of computational results via built-in access controls and TimeTravel for revision history, ensuring data integrity without external tools; however, a 2024 security vulnerability (CVE-2024-36109), a cross-site scripting issue due to insufficient sanitization of user-supplied input in the markdown parser allowing execution of arbitrary JavaScript code in published files, was addressed through CoCalc's security reporting process. This integration streamlines workflows by combining version control with real-time collaboration, reducing overhead in distributed development.

References

  1. [1]
    CoCalc
    With CoCalc, you can easily collaborate with colleagues, students, and friends to edit computational documents. We support Jupyter Notebooks, LaTeX files, ...Sign InOnline Linux TerminalSign UpOnline LaTeX EditorTrial Projects
  2. [2]
    Team - William Stein - CoCalc
    Chief Executive Officer and Founder of SageMath, Inc. William is both the CEO and a lead software developer for both the front and back end of CoCalc.
  3. [3]
    Where does CoCalc come from?
    Sep 10, 2018 · Sagemath Inc., the company behind CoCalc, is an independent Seattle based tech startup founded by William Stein in Feb 2015.
  4. [4]
    CoCalc: Collaborative Calculation in the Cloud - GitHub
    CoCalc is web-based software that enables collaboration in research, teaching, and scientific publishing.
  5. [5]
    Compute Servers — CoCalc Manual documentation
    We provide the best real-time collaborative environment for Jupyter, LaTeX, and SageMath! Introduction · Core Applications · Signature Features · AI Assistant ...Missing: editor | Show results with:editor
  6. [6]
    AI Assistant — CoCalc Manual documentation
    AI Assistant with the help of Large Language Models (LLMs) can transform how you use CoCalc for learning, writing programs, and writing scientific documents.
  7. [7]
    Using nbgrader — CoCalc Manual documentation
    nbgrader is a tool that facilitates creating and grading assignments in the Jupyter notebook. It allows instructors to easily create notebook-based assignments.
  8. [8]
    What is SageMathCloud: let's clear some things up
    Aug 27, 2014 · The goal of the SageMath software project, which I founded in 2005, is to create a viable free open source alternative to Magma, Mathematica, ...
  9. [9]
    SageMathCloud is Now CoCalc
    May 20, 2017 · As of May 20, 2017, SageMathCloud is being renamed to CoCalc, for Collaborative Calculation in the Cloud.Missing: rebranding announcement
  10. [10]
    Software Updates 2018 — CoCalc Manual documentation
    (new) support for automatically processing PythonTeX code in LaTeX documents. (new) additional Library entries for RMarkdown and LaTeX/PythonTeX examples.
  11. [11]
    On-Premises Offerings - CoCalc
    We offer flexible licensing options, including volume discounts for large organizations, academic discounts for educational institutions, multi-year ...Missing: 2020 | Show results with:2020
  12. [12]
    AI Assistant | Features - CoCalc
    CoCalc integrates large language models including OpenAI's ChatGPT, Google's Gemini, Anthropic's Claude, and Mistral as virtual assistants.
  13. [13]
    CoCalc News
    This week, NVIDIA highlighted CoCalc as a key platform for teaching with its CUDA-Q academic materials.
  14. [14]
    SageMath - Open-Source Mathematical Software System
    SageMath is a free open-source mathematics software system licensed under the GPL. It builds on top of many existing open-source packages.Sage Cell Server · Why Sage? · Download · Tutorial
  15. [15]
    Tutorial - SageMath Documentation
    Sage is free, open-source math software that supports research and teaching in algebra, geometry, number theory, cryptography, numerical computation, and ...Introduction · Getting Help · Basic Algebra and Calculus · Linear Algebra
  16. [16]
    Use SageMath Online - CoCalc
    CoCalc's integrated course management system fully supports using nbgrader together with SageMath Jupyter Notebooks. We provide custom Python templates for all ...
  17. [17]
    Online Jupyter Notebooks - CoCalc
    CoCalc supports many kernels right out of the box: several Python environments, SageMath, R Statistical SoftwareOctave, Julia and many more. No software setup: ...
  18. [18]
    TimeTravel — CoCalc Manual documentation
    CoCalc's TimeTravel allows you to easily access all revisions of a file. You can use it to see what changes have been made by your collaborators or to recover ...Missing: enhancements | Show results with:enhancements
  19. [19]
    LaTeX Editor — CoCalc Manual documentation
    CoCalc supports embedding relevant code directly within a LaTeX document using PythonTeX, SageTeX, or Knitr respectively. Such code is automatically processed ...
  20. [20]
    Collaborative Calculations - CoCalc
    CoCalc support many programming languages. This includes Python, R, Julia, LaTeX, and C++. Check out the links below to get an overview over what is available.Missing: 2018 | Show results with:2018
  21. [21]
    Software Environment — CoCalc Manual documentation
    Main supported software environments · Python – Python is a general purpose programming language. · R Statistical Software – the R-project provides a statistical ...
  22. [22]
    Linux Terminal — CoCalc Manual documentation
    The CoCalc Linux Terminal lets you run programs online in a Linux environment. The ongoing terminal session is synchronized with your collaborators.
  23. [23]
    The CoCalc Computing Environment - SIAM
    Nov 1, 2017 · The CoCalc platform supports dozens of programming languages—such as Python, Sage, R, Julia, C, C++, Haskell, Scala, and Fortran—and ...<|separator|>
  24. [24]
    Enhance your Projects with Compute Servers - CoCalc
    GPU's: select one or more powerful GPUs for your selected machine, including H100's for about $2/hour. CPU: you can not only select the number of CPU cores, ...
  25. [25]
    Features - CoCalc
    CoCalc extensively integrates with AI language models, including OpenAI's ChatGPT, Google's Gemini,Anthropic's Claude, and Mistral.Missing: 2023 2024
  26. [26]
    Collaborate. Share! Publish!!! — CoCalc Manual documentation
    In CoCalc, you can collaborate on projects, share files/folders via links, and publish them on the CoCalc share server for discoverability.
  27. [27]
    Collaborative Editing in CoCalc: OT, CRDT, or something else?
    Oct 11, 2018 · CoCalc has 2, when people's clocks are synced, because all patches you've applied have timestamp less than now (=time when making the patch).Ot = Operational Transforms · What About Cocalc's Approach... · More DetailsMissing: synchronous | Show results with:synchronous
  28. [28]
    https://doc.cocalc.com/chat.html
  29. [29]
    Computational Whiteboard - CoCalc
    CoCalc's whiteboard is a full-featured online collaborative tool with Jupyter code cells, LaTeX, markdown, sticky notes, sketching, chat, and time travel.
  30. [30]
    Assignments and Handouts — CoCalc Manual documentation
    The grades and comments are stored in GRADE.md files inside each student folder. Return an Assignment . Once an assignment has been graded, Return buttons ...
  31. [31]
    Peer Grading — CoCalc Manual documentation
    Use peer grading to randomly and anonymously redistribute collected assignments to your students, so that they can grade it for you.Missing: management tools
  32. [32]
    Teach scientific software online using Jupyter Notebooks - CoCalc
    Manage all files. The course management interface gives you full control over distributing, collecting, grading and returning everyone's assignments. Diagram ...
  33. [33]
    Scaling - CoCalc OnPrem v3.7.7
    This page describes how to scale CoCalc in a Kubernetes cluster. There are basically two aspects to think about.Missing: infrastructure | Show results with:infrastructure
  34. [34]
    CoCalc OnPrem
    It is possible to run a completely standalone instance of CoCalc on a Kubernetes cluster. The underlying services and their architecture are identical to those ...Missing: 2020 | Show results with:2020
  35. [35]
    Google GCP/GKE - CoCalc OnPrem v3.7.7
    This guide is specific for an GKE Cluster. If you want to use another cloud provider for your Kubernetes cluster, you have to adapt the instructions. 2022-05: ...
  36. [36]
    Amazon AWS/EKS - CoCalc OnPrem v3.7.7
    This guide helps you setting up CoCalc OnPrem on AWS. It will use it's EKS Kubernetes service to run CoCalc OnPrem.
  37. [37]
    New GPU Cloud Integration with Hyperstack! – News - CoCalc
    Apr 24, 2024 · If you are using GPU's on CoCalc, there's an entirely new cloud option that you should see which is Hyperstack.Missing: providers | Show results with:providers
  38. [38]
    Backups — CoCalc Manual documentation
    All files in every project are snapshotted every couple of minutes. You can browse your snapshots by clicking the “Backups” link at the upper right of the ...Missing: management | Show results with:management
  39. [39]
    Cloud File System — CoCalc Manual documentation
    A CoCalc Cloud File System is “the third way” to store and access your data on Compute Servers, in addition to the home directory of your project and Fast Local ...Missing: management snapshots external
  40. [40]
    Trust - CoCalc
    CoCalc by SageMath, Inc. is SOC 2 compliant, meaning we meet rigorous standards for data security and operational integrity.
  41. [41]
    CoCalc - Privacy Policy
    Oct 3, 2025 · This Privacy Policy explains our online and offline information practices, the kinds of information we may collect, how we intend to use and share that ...
  42. [42]
    Overview - CoCalc OnPrem v3.7.7
    CoCalc OnPrem makes it possible to self-host CoCalc on your own cluster. This solves a couple of problems, enhances what your users can do with the cluster, and ...Missing: premises 2020
  43. [43]
    Project Settings — CoCalc Manual documentation
    To download datasets into your project. To connect to your project with SSH. To get extra storage space (both RAM and disk space).
  44. [44]
    Restrict Student Projects — CoCalc Manual documentation
    Restricting student projects can reduce confusion and prevent issues with running and grading assignments. It may also keep students more focused.
  45. [45]
    Project Log — CoCalc Manual documentation
    The project log provides a timeline of past actions, including file openings, collaborator actions, and file actions like download, delete, and move.Missing: enhancements | Show results with:enhancements
  46. [46]
    Setup - CoCalc OnPrem v3.7.7
    GKE. This setup runs on Google Kubernetes Engine in Google's GCP cloud: Google GCP/GKE ; EKS. It also runs on Amazon's Elastic Kubernetes Service in their AWS ...
  47. [47]
    Compute Server VPN – News - CoCalc
    The new Wireguard encrypted VPN between all compute servers in a project is now live and fully working in all the testing I've done.Missing: integration | Show results with:integration
  48. [48]
    Why CoCalc? — CoCalc Manual documentation
    On Premises Option​​ CoCalc Cloud can be deployed on your own resources or on cloud providers such as GCP, AWS, or Aliyun. CoCalc's AI integration can be easily ...Missing: 2020 | Show results with:2020
  49. [49]
    Mathematics and Programming in the Cloud with CoCalc - Eductive
    Jun 13, 2017 · This was precisely one of the key motivations for William Stein: He noticed that there were a number of existing open-source math packages ...
  50. [50]
    Math 157 - Intro to Mathematical Software (Winter 2023)
    The lectures use a "learn by doing" model in which students interact with CoCalc during the lecture; students are expected to attend class with a laptop or ...Missing: education | Show results with:education
  51. [51]
    Teaching Python with CoCalc | Matthew Towers' homepage
    Jul 7, 2022 · This post is about how I adapted MATH0011 in those years, which was based on the use of an online collaborative environment called CoCalc.Missing: education | Show results with:education
  52. [52]
    Trial Projects — CoCalc Manual documentation
    Trial projects are completely free and they already offer features not available in free tiers of our competitors, for example, Linux Terminal. Full access ...Missing: educators | Show results with:educators
  53. [53]
    CoCalc -- Page 2 of public files
    Complete advanced calculus applications including series, sequences, and differential equations using Julia's computational ecosystem.
  54. [54]
    Project: Publications - CoCalc
    Sep 7, 2025 · Calculate hydrogen energy levels using the Bohr equation (E = -13.6 eV/n²), visualize electron transitions, and generate electron configurations ...
  55. [55]
    Climate Data Analysis with Python in CoCalc.ipynb
    Learning Objectives · Master climate data analysis using fundamental statistical methods · Apply linear regression techniques to quantify global warming trends.
  56. [56]
    Quantum Computing Fundamentals with Python in CoCalc.ipynb
    Implement practical quantum algorithms. Compare quantum vs classical computing advantages. Explore real-world quantum applications.
  57. [57]
    Git Version Control — CoCalc Manual documentation
    CoCalc gives you full control over Git via a Linux Terminal in the command-line. Once you have enabled internet access for your project, you can to connect to ...
  58. [58]
    CoCalc has GPU's and powerful VM's – News
    Nov 19, 2023 · CoCalc now features robust compute servers, enabling users to connect a remote computer to CoCalc and utilize it for terminals and Jupyter notebooks.
  59. [59]
    sagemathinc/cocalc-howto: How to do things on https ... - GitHub
    Turbocharge Your Research: A Quick Guide to High-Performance Computing on CoCalc · Using SageMath with a CPU or GPU Server · JAX · Running On-Prem Compute ...