--- title: "Cloud Platform" description: "Start Your QuantConnect Journey. Learn to use the QuantConnect Platform and explore our features." canonical: https://www.quantconnect.com/docs/v2/cloud-platform markdown: https://www.quantconnect.com/docs/v2/cloud-platform.md language: python source: https://github.com/QuantConnect/Documentation/tree/master/01%20Cloud%20Platform modified: 2026-11-01 index: https://www.quantconnect.com/llms.txt --- # Cloud Platform [Documentation](https://www.quantconnect.com/docs/v2.md) > Cloud Platform > Code examples are shown in Python. Append `?lang=csharp` to this URL for the C# version of this page. ![Cloud platform icon](https://cdn.quantconnect.com/i/tu/cloud-platform-icon.svg) ### Quant Research in the Cloud ### Quickly deploy quantitative strategies on the QuantConnect Cloud Platform ### Start Your QuantConnect Journey Join the leading cloud platform for quant research and trading. Easily scale your team on our cloud, and focus on what matters, alpha. [Get Started](https://www.quantconnect.com/docs/v2/cloud-platform/getting-started.md) [Download PDF](https://cdn.quantconnect.com/docs/i/Quantconnect-Cloud-Platform-Python.pdf) ![Cloud Platform](https://cdn.quantconnect.com/i/tu/header-img-cloud.webp) #### IN THIS SECTION [Getting Started](https://www.quantconnect.com/docs/v2/cloud-platform/getting-started.md) [Organizations](https://www.quantconnect.com/docs/v2/cloud-platform/organizations.md) [Supported Brokerages](https://www.quantconnect.com/docs/v2/cloud-platform/live-trading/brokerages.md) [API Reference](https://www.quantconnect.com/docs/v2/cloud-platform/api-reference.md) --- - [Organizations](https://www.quantconnect.com/docs/v2/cloud-platform/organizations.md): Learn how to manage your Organizations - [Learning Center](https://www.quantconnect.com/docs/v2/cloud-platform/learning-center.md): A coding environment to learn quantitative trading using LEAN - [Projects](https://www.quantconnect.com/docs/v2/cloud-platform/projects.md): Manage and deploy your algorithms - [Research](https://www.quantconnect.com/docs/v2/cloud-platform/research.md): Test your hypothesis on historical data in interactive Jupyter notebooks - [Backtesting](https://www.quantconnect.com/docs/v2/cloud-platform/backtesting.md): Simulate a trading algorithm on historical data - [Datasets](https://www.quantconnect.com/docs/v2/cloud-platform/datasets.md): The Dataset Market is a portal where we aggregate datasets for you to use in your algorithms - [Live Trading](https://www.quantconnect.com/docs/v2/cloud-platform/live-trading.md): Deploy your algorithms in live mode with real-time data - [Optimization](https://www.quantconnect.com/docs/v2/cloud-platform/optimization.md): Find the optimal algorithm parameters to maximize or minimize an objective function - [Research Pipeline](https://www.quantconnect.com/docs/v2/cloud-platform/research-pipeline.md): Track projects from idea to live trading on a kanban board - [Object Store](https://www.quantconnect.com/docs/v2/cloud-platform/object-store.md): File system that you can use in your algorithms to save, read, and delete data - [Community](https://www.quantconnect.com/docs/v2/cloud-platform/community.md): Connect with a vibrant community of quants - [API Reference](https://www.quantconnect.com/docs/v2/cloud-platform/api-reference.md): QuantConnect API endpoints ## Pages in This Section - [Welcome](https://www.quantconnect.com/docs/v2/cloud-platform/welcome.md): QuantConnect is an open-source, community-driven algorithmic trading platform. Our trading engine is powered by LEAN, which supports C# and Python languages. - [Getting Started](https://www.quantconnect.com/docs/v2/cloud-platform/getting-started.md): A demonstration of how to create, backtest, and paper trade a new algorithm. - [Security and IP](https://www.quantconnect.com/docs/v2/cloud-platform/security-and-ip.md): You own your code. Your IP is private by default unless you explicitly share it with the community in the forums or with another team member via collaboration. - [Organizations](https://www.quantconnect.com/docs/v2/cloud-platform/organizations.md): An organization is a collection of members that share hardware resources, share access to datasets, and collaborate together to develop projects. - [Learning Center](https://www.quantconnect.com/docs/v2/cloud-platform/learning-center.md): The Learning Center is a coding environment to learn quantitative trading using LEAN. It contains courses from educators from the QC team and the community. - [Projects](https://www.quantconnect.com/docs/v2/cloud-platform/projects.md): Projects contain files to run backtests, launch research notebooks, perform parameter optimizations, and deploy live trading strategies. - [Research](https://www.quantconnect.com/docs/v2/cloud-platform/research.md): The Research Environment is a Jupyter notebook-based environment where you can access our data through the QuantBook class instead of in a backtest. - [Backtesting](https://www.quantconnect.com/docs/v2/cloud-platform/backtesting.md): Backtesting is the process of simulating a trading algorithm on historical data. By running a backtest, you can measure how the algorithm would have performed. - [Datasets](https://www.quantconnect.com/docs/v2/cloud-platform/datasets.md): Datasets are a stream of data points you use in your algorithms to make trading decisions and fill orders. Our Dataset Market contains curated datasets available for use in your strategy. - [Live Trading](https://www.quantconnect.com/docs/v2/cloud-platform/live-trading.md): A live algorithm trades in real-time with real market data. QuantConnect enables you to run your algorithms in live mode with real-time market data. - [Optimization](https://www.quantconnect.com/docs/v2/cloud-platform/optimization.md): Parameter optimization is the process of finding the optimal algorithm parameters to maximize or minimize an objective function. Just be wary of overfitting. - [Research Pipeline](https://www.quantconnect.com/docs/v2/cloud-platform/research-pipeline.md): The Research Pipeline is a kanban board for moving projects through research, backtesting, paper trading, and live trading. - [Object Store](https://www.quantconnect.com/docs/v2/cloud-platform/object-store.md): The Object Store is an organization-specific key-value storage location to save and retrieve data in QuantConnect's cache. It's similar to a hash table. - [Community](https://www.quantconnect.com/docs/v2/cloud-platform/community.md): Our platform supports several channels of communication so our members can discuss with the core team, other community members, and third-party contractors. - [API Reference](https://www.quantconnect.com/docs/v2/cloud-platform/api-reference.md): The QuantConnect REST API lets you communicate with our cloud servers through URL endpoints. To use our Python or C# wrapper, see QuantConnect API.