According to @AndrewYNg, DeepLearningAI engineers used AI coding to implement a basic clone of Cloudflare capabilities during a Cloudflare outage, restoring their site before many major websites; source: @AndrewYNg on X, Nov 19, 2025. For traders, this outage report highlights single-vendor infrastructure risk that can influence sentiment toward Cloudflare (NET) and AI tooling providers when availability is disrupted; source: @AndrewYNg on X, Nov 19, 2025. Crypto market impact: interruptions at core web providers can restrict access to exchange and DeFi web interfaces, so monitoring status updates and maintaining alternative access paths is prudent during such events; source: @AndrewYNg on X, Nov 19, 2025.

According to Andrew Ng, he announced a new course titled Agentic AI on X and stated that building AI agents is one of the most in-demand skills in the job market, posted on October 7, 2025, source: https://twitter.com/AndrewYNg/status/1975614372799283423. He added that the course is available now at the provided link and teaches implementation of four key agentic design patterns, including Reflection, source: https://twitter.com/AndrewYNg/status/1975614372799283423 source: https://t.co/Ryb1M38I1v.

According to DeepLearningAI, the organization is seeking a Product Marketing Manager to lead campaigns targeting AI builders and learners, with a focus on launching courses designed to foster real-world AI application skills. This hiring initiative signals DeepLearningAI's commitment to expanding its educational offerings and market influence in the artificial intelligence sector. For crypto traders, increased AI education could lead to greater innovation and adoption of AI-driven trading tools, potentially impacting the volatility and liquidity of AI-related tokens and projects. Source: DeepLearningAI

According to DeepLearningAI, recent research identifies that multi-agent systems often fail due to poor specifications, inter-agent misalignment, and weak task verification. These failures can have significant consequences for AI-driven trading algorithms in the cryptocurrency market, as flawed agent coordination may lead to suboptimal trade execution and risk management. Improvements in prompt design and agent restructuring have been shown to reduce these failures, offering potential enhancements for algorithmic trading systems that leverage multi-agent AI in crypto markets (source: DeepLearningAI).

According to DeepLearningAI, the new Data Analytics Professional Certificate has been launched, thanks to the feedback from volunteer testers who helped refine the first two courses. This program could potentially enhance data-driven decision-making skills crucial for crypto trading strategies.

According to @DeepLearningAI, a sample lesson from the Mathematics for Machine Learning and Data Science Specialization, led by @SerranoAcademy, delves into Newton’s method. This technique is crucial for finding polynomial roots, offering insights into the mathematical foundations essential for machine learning algorithms.