According to @DeepLearningAI, GenAI with Streamlit enables developers to start from intent and generate working app code in seconds, replacing hours of setup previously required for data or AI prototypes; source: https://twitter.com/DeepLearningAI/status/1963954016100004104. According to @DeepLearningAI, the post promotes the course Fast Prototyping of GenAI Apps with Streamlit aimed at helping learners prototype faster, test more ideas, and move from concept to app; source: https://www.deeplearning.ai/courses/fast-prototyping-of-genai-apps-with-streamlit and https://twitter.com/DeepLearningAI/status/1963954016100004104. According to @DeepLearningAI, the announcement explicitly tags Snowflake and thedataprof, highlighting relevance to data-centric development audiences; source: https://twitter.com/DeepLearningAI/status/1963954016100004104. According to @DeepLearningAI, no specific cryptocurrencies, tickers, or market metrics are cited in the announcement, so any trading impact would stem from faster in-house tool development rather than direct asset news; source: https://twitter.com/DeepLearningAI/status/1963954016100004104 and https://www.deeplearning.ai/courses/fast-prototyping-of-genai-apps-with-streamlit.

According to @DeepLearningAI, a new course titled Fast Prototyping of GenAI Apps with Streamlit, built in partnership with Snowflake, is now live to enable rapid prototyping of generative AI applications on Streamlit; source: @DeepLearningAI on X, Aug 12, 2025. The announcement stresses that months-long planning cycles no longer fit today’s fast-moving software landscape as new capabilities emerge weekly, underscoring a need for faster iteration; source: @DeepLearningAI on X, Aug 12, 2025. The post does not mention cryptocurrency, blockchain integrations, or token use, and no direct crypto market impact was disclosed; source: @DeepLearningAI on X, Aug 12, 2025.