Simplify Environment Setup.
Begin Building Faster.
Pre-configured environments with curated packages mean clean dependencies and faster development.
Why Waste Time on Setup?
Launch in Minutes
Launch environments in minutes, not hours. Spend more time building, less time configuring.
Built for Your Project
Specialized environments tailored to your specific use case, from web development to financial modeling.
Battle Tested
We test every package combination so you don’t have to worry about conflicts.
14 Specialized Environments Ready to Launch
Core Development Environments
Python Starter
Just Python and pandas.
A clean foundation for Python development with minimal dependencies.
This environment is the perfect starting point for creating your own environment with only the packages you need, making it ideal for beginners transitioning from Excel or other tools to Python-based workflows.
Available to all users.
Anaconda Metapackage
NumPy, pandas, scikit-learn, Panel and much more.
This comprehensive environment is recommended for most practitioners. Whether it’s linear algebra or rocket science, this environment has all the packages you are likely to need for most data science projects.
Available to all users.
AI & Machine Learning Environments
AI/ML
TensorFlow, PyTorch, Transformers, and more
This machine learning toolkit provides frameworks optimized for model development and performance. It enables access to popular ML libraries for building, training, and deploying various types of models.
Available to all users.
PyTorch
PyTorch, torchvision, torchaudio, and more
This PyTorch-focused environment provides tools for neural network development, model experimentation, and advanced deep learning projects.
Available to business users.
Natural Language Processing
NLTK, spaCy, transformers, and more
This deep learning environment includes the complete PyTorch ecosystem. It enables advanced text analysis, language processing workflows, and automated content generation using state-of-the-art natural language tools.
Available to business users.
Industry-Specific Environments
Finance
This financial analysis environment includes packages for a variety of finance-centric projects, including financial modeling, portfolio analysis, and market research.
Available to all users.
Banking
XGBoost, LightGBM, imbalanced-learn, and more
This advanced analytics environment provides machine learning tools specifically designed for banking professionals working on credit risk modeling, fraud detection, and regulatory compliance projects.
Available to business users.
Insurance
PyMC, ArviZ, patsy, plotly, and more
This actuarial science environment features probabilistic analysis tools tailored for insurance professionals conducting catastrophe modeling, claims analytics, and sophisticated risk assessment projects.
Available to business users.
Life Sciences
BioPython, NetworkX, SciPy, and more
This genomics and molecular analysis environment supports life sciences professionals with specialized bioinformatics tools for pharmaceutical research, biological data analysis, and network modeling projects.
Available to business users.
Manufacturing
FastAPI, Prophet, Celery, and more
This environment enables manufacturing professionals to implement predictive maintenance and quality control with comprehensive monitoring, forecasting, and automated workflow management capabilities.
Available to business users.
Technology Integration Environments
Snowflake
Snowpark, Snowflake ML, Streamlit, and more
The Snowflake environment provides optimized analytics workflows and connectivity to Snowflake databases. It enables large-scale data processing, scalable model building, and interactive dashboard creation.
Available to business users.
ETL
PySpark, Dask, MLflow, and more
This distributed data processing environment includes modern pipeline orchestration frameworks for large-scale operations. It provides comprehensive tools for handling massive data volumes, tracking pipeline performance, and building enterprise-scale workflows.
Available to business users.
Web Development
FastAPI, Django, SQLAlchemy, and more
This full-stack Python development environment provides comprehensive database integration and API frameworks. It enables high-performance application building, secure API development, and data-driven web solutions.
Available to business users.
DevOps
Boto3, Kubernetes, Docker SDK, and more
This infrastructure automation environment enables cloud-native deployment pipelines with comprehensive orchestration tools. It provides complete automation capabilities, container management, and CI/CD workflow building.
Available to business users.
Trusted by Millions of Developers
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Users Worldwide
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Quick Start Environments
Frequently Asked Questions
What are quick start environments?
Quick start environments are pre-configured Python environments with carefully curated packages for specific use cases and industries. Instead of spending hours researching and installing compatible packages, you get curated environments that work together seamlessly from day one.
How do I access quick start environments?
Install Anaconda Navigator and Anaconda Toolbox, log in to the Anaconda AI Platform, open JupyterLab or Notebooks, and select “Create New Environment” from the Anaconda Toolbox. Launch any environment with a single click.
Do I have to use quick start environments in JupyterLab or Notebooks?
No, you can use quick start environments in JupyterLab, Notebooks, or any IDE that supports conda environments, like VS Code or PyCharm.
Can I customize environments after installation?
Absolutely! Quick start environments are designed as starting points for your projects. You can add, remove, or update packages just like any conda environment using Navigator, CLI commands, or magic commands directly in Jupyter notebooks.
Which environments are available for free?
Free users have access to Python starter, Anaconda metapackage, AI/ML starter, and finance environments. Business users get access to all 14 environments, including specialized industry and technology-integrated environments.
