Sold by: Galaxys CloudÂ
Deployed on AWS
AWS Free Tier
Fast.ai on AWS Marketplace: Complete Deep Learning Environment for Beginners. Pre-installed PyTorch 2.9.1 Fast.ai 2.8.5 on Ubuntu 22.04. Start training AI models in 5 minutes with our simplified setup. Perfect for students, developers, and researchers beginning their ML journey. Includes Jupyter Lab, example notebooks, and AWS optimization guides. Works on CPU instances for learning, ready for GPU acceleration when needed. Step-by-step tutorials for image classification, NLP, and tabular data projects. All dependencies pre-configured in isolated environment. Reduce setup time from days to minutes. Deploy, train, and experiment with deep learning immediately. AWS-specific guidance for cost optimization and performance tuning. Everything you need to go from zero to production-ready models.
Overview
Fast.ai Complete Deep Learning Environment - AWS Marketplace Edition
The perfect starting point for beginners entering deep learning. Specifically designed for students, career changers, and developers who want to learn AI without complex setup headaches.
Why Perfect for Beginners: Traditional deep learning requires days of configuration. Our solution eliminates barriers with zero configuration needed. Train your first model in under 5 minutes with no prior experience required.
Complete Package Includes: Pre-installed PyTorch 2.9.1 and Fast.ai 2.8.5 Jupyter Lab with interactive notebooks Essential libraries: NumPy, Pandas, Matplotlib, OpenCV AWS optimized for CPU and GPU instances Isolated virtual environment
Complete Documentation: Visit https://galaxys.cloud/fast-ai-complete-beginners-guide/Â Includes step-by-step tutorials Real-world project examples AWS cost optimization guide 30-day structured learning path Troubleshooting solutions
Ideal For: Students and self-learners avoiding setup struggles Career changers needing portfolio projects Developers exploring AI capabilities Educators requiring consistent classroom environments
Key Differentiators: 15-minute setup versus days of configuration Pre-configured and tested environment Beginner-focused guidance included AWS performance optimization Regular updates and maintenance
Ready Projects: Image classification for object recognition Sentiment analysis for text emotions Price prediction models Style transfer applications Recommendation systems
AWS Advantages: Start with t3.micro for learning Scale to g4dn.xlarge for serious training Use Spot Instances for cost savings Pay only for compute time used
Learning Timeline: Week 1: First model in 5 minutes Week 2: Complete first project Week 3: Advanced techniques Week 4: Production deployment
Technical Specifications: Ubuntu 22.04 LTS base image Python 3.10 plus Jupyter Lab and Notebook Git and AWS CLI included GPU ready for NVIDIA CUDA Security updates maintained
Educational Value: Progressive difficulty structure Real-world dataset examples Industry best practices Community learning access
Performance Features: AWS infrastructure optimized Auto-scaling ready Memory optimized configurations Cost monitoring guidance
Support Included: Complete online documentation Configuration troubleshooting AWS optimization tips Regular environment updates
Business Applications: Quick AI prototyping Team training efficiency Cost-effective experimentation Production transition ready
Educational Use: Standardized lab setup Reduced IT support needs Classroom scalability Industry-relevant curriculum
Simple Start Process:
- Launch from AWS Marketplace
- Connect via browser
- Activate environment
- Train first model
- Follow documentation
DIY vs Our Solution: Days of setup vs 15 minutes Configuration issues vs pre-configured No guidance vs complete tutorials Unoptimized vs AWS-tuned
For Beginners Who Think: AI seems too complicated Setup always fails What to do after installing Need practical projects
Transparent Pricing: No hidden fees AWS compute costs only Free tier eligible starts Budget-friendly scaling
Start Today: Begin your AI journey in minutes, not days. Everything included for deep learning success from first model to production deployment. Perfect for absolute beginners with growth for advanced projects.
Launch now from AWS Marketplace. Complete documentation and support provided. Your path to AI mastery starts here with our Fast.ai Complete Environment.
Highlights
- Beginner-Friendly AI Launchpad: Start training deep learning models in under 5 minutes with zero configuration. Our pre-installed Fast.ai environment eliminates complex setup, allowing complete beginners to focus on learning AI concepts rather than troubleshooting dependencies. Includes step-by-step tutorials and ready-to-run project templates.
- Complete Educational Ecosystem: More than just software a guided learning path with comprehensive documentation. Access 30 days of structured curriculum, real-world project examples, troubleshooting guides, and best practices for production deployment. Perfect for students, career changers, and educators building AI skills.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
t2.2xlarge Recommended | $1.60 |
t3.micro | $0.10 |
r8i.32xlarge | $6.40 |
m6id.4xlarge | $1.60 |
m5n.24xlarge | $6.40 |
h1.16xlarge | $3.20 |
m3.2xlarge | $1.60 |
r7i.xlarge | $0.10 |
r5ad.2xlarge | $1.60 |
m6i.large | $0.10 |
Vendor refund policy
For this offering, Galaxys Cloud does not offer refund, you may cancel at anytime.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
ver2025
Additional details
Usage instructions
Subscribe and Launch: Navigate to this product in AWS Marketplace. Click Continue to Subscribe, accept terms, then Continue to Configuration. Select region and instance type.
Configure Access: Set up security group to allow SSH (port 22) and HTTP (port 8888). Create or select existing key pair for authentication.
Connect via SSH: Use command: ssh -i your-key.pem ubuntu@ec2-ip-address.compute-1.amazonaws.comÂ
Start Environment: Execute: cd /home/ubuntu/fastai_project && source fastai_env/bin/activate && jupyter lab --ip=0.0.0.0 --port=8888 --no-browser
Access Interface: Open browser to http://ec2-ip-address:8888Â and enter token from terminal output.
Documentation: Complete user guide available at https://galaxys.cloud/fast-ai-complete-beginners-guide/Â
Technical Specifications:
Minimum: t3.small (2 vCPU, 2 GB RAM)
Recommended: g4dn.xlarge or larger for GPU acceleration
Storage: 20 GB EBS minimum
OS: Ubuntu 22.04 LTS
Resources
Vendor resources
Support
Vendor support
Remote support seller@galaxys.cloudÂ
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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