Part of Build Complete Teams With AI Skills
Engineering Blueprint
Safety checkedBuild AI Products With Data to Deployment
5 expert skills for AI/ML/Data teams covering data science, pipelines, model deployment, prompt engineering, and computer vision with MLOps patterns.
What problem does this solve?
Enables data and AI teams to build production-grade AI systems from data infrastructure through model deployment and optimization. Teams struggle with data quality, ML model deployment, LLM integration, and real-time AI systems. This domain provides frameworks and tools for the complete AI/ML/Data lifecycle including MLOps, RAG systems, and AI agents.
How does it work?
Once set up, you upload AI/ML/Data skill files to Claude or Claude Code for AI frameworks and MLOps tools. 1. Choose your focus: data (pipelines, quality), analytics (experimentation, modeling), AI (LLMs, agents, vision). 2. Upload SKILL.md and reference guides for your specialization. 3. Run Python scripts for analysis: experiment design, pipeline orchestration, model deployment, prompt optimization. 4. Build AI systems using RAG architectures, agent patterns, and production ML infrastructure. Output: reliable data pipelines, optimized ML models, LLM applications with RAG, and computer vision systems.
Included Skills
No skills in this group
What's required to run this?
Requires Python 3.7+ plus machine learning libraries: PyTorch, TensorFlow, LangChain, LlamaIndex, scikit-learn. Data engineering requires Airflow, Spark, or Prefect. Supports cloud platforms: AWS (SageMaker, Lambda), GCP (Vertex AI), Azure (ML). Data storage: PostgreSQL, Snowflake, Databricks, BigQuery. Monitoring: MLflow, Weights & Biases, Evidently. All patterns use industry-standard tools and architectures.
Key Features
Data Science
Experiment design, feature engineering, statistical modeling, A/B testing, causal inference
Data Engineering
Data pipelines (Airflow/Spark), ETL/ELT workflows, data quality validation, dimensional modeling
ML Engineering
MLOps, model deployment, LLM integration, model monitoring, A/B testing in production
Prompt Engineering
LLM optimization, RAG system architecture, agentic AI design, chain-of-thought prompting
Computer Vision
Object detection, image segmentation, video processing, real-time inference optimization
About This Blueprint
- Industry
- Technology
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