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This article focuses on xAI's Grok 4.6 model and its dedicated coding agent, Grok Build, demonstrating their integration for automating end-to-end data science workflows. The piece highlights the model's agentic capabilities in handling complex multi-step tasks like data generation, cleaning, and API deployment within a terminal-based environment.

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Build an End-to-End Data Science Project with Grok Build and Grok 4.6

KDnuggetsAugust 24, 20267 min read

Use Grok Build to create a production-ready data science workflow with EDA, scikit-learn, model training, FastAPI, API testing, and cloud deployment.

Grok 4.6 is xAI's latest frontier model, built specifically for coding, agentic tasks, and knowledge work. It focuses heavily on long-running agents that can work across a codebase, research problems, test their work, and keep going through complex multi-step tasks. According to xAI's evaluations, Grok 4.6 reaches frontier-level performance and matches GPT-5.6 Sol on the Artificial Analysis Intelligence Index. What makes it even more interesting for developers is Grok Build, xAI's own terminal coding agent and TUI. Instead of relying on a third-party coding interface, xAI built a full-screen, interactive terminal experience specifically for working with its models, and Grok 4.6 now powers Grok Build directly. In this guide, we will use Grok Build and just four prompts to create an end-to-end data science project that predicts how long a customer may…

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