DeepLearning.AI: Education Platform Expands Focus on Agentic AI and Developer Workflows

LinkAndrew Ng / DeepLearning.AIResource

DeepLearning.AI, founded by Andrew Ng, provides courses and specialisations across machine learning and AI. Recent short courses focus specifically on adaptive AI agents, local coding workflows, and automated code review.

Key points

  1. New course in collaboration with Oracle on building adaptive AI agents that retain memory across runs using agent traces and code knowledge graphs.
  2. Practical course with JetBrains exploring AI coding workflows, moving from Claude Code baselines to hybrid and local model setups.
  3. Hands-on training with Qodo on creating contextual AI code review agents.
  4. Core curriculum continues to feature foundational programmes like the Stanford Online Machine Learning Specialisation alongside crewAI and LangChain courses.

Why it matters

Software engineering is shifting from basic prompting toward building and managing autonomous agents within developer environments. These courses provide practical training on integrating agentic workflows into codebases, review pipelines, and local machines.

Analysis

The latest catalog updates highlight the industry shift towards AI engineering and agentic workflows. Rather than treating LLMs as standalone chat interfaces, the curriculum focuses on context retrieval, persistent memory across sessions, and evaluating cost and latency tradeoffs between cloud and local models.

Found in

Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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  • Mattersburg
    Johann Nepomuk Bergerstraße 7/2/14
    7210 Mattersburg, Austria
  • Vienna
    Ungargasse 64-66/3/404
    1030 Wien, Austria

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