DeepLearning.AI: Start or Advance Your Career in AI
发布时间:2026-09-08 | 浏览:2
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Build a foundation of machine learning and AI skills, and understand how to apply them in the real world.
AI Python for Beginners
Learn Python programming with AI assistance. Gain skills writing, testing, and debugging code efficiently, and create real-world AI applications.
ChatGPT Prompt Engineering for Developers
Learn the fundamentals of prompt engineering for ChatGPT. Learn effective prompting, and how to use LLMs for summarizing, inferring, transforming, and expanding.
Generative AI for Everyoneㅤ
Learn how to use generative AI's capabilities & limitations. Get an overview of real-world examples, and impact on business & society for effective strategies.
Machine Learning Specialization
Learn foundational AI concepts through an intuitive visual approach, then learn the code needed to implement the algorithms and math for ML.
Multi AI Agent Systems with crewAI
Automate business workflows with multi-AI agent systems. Exceed the performance of prompting a single LLM by designing and prompting a team of AI agents through natural language.
LangChain for LLM Application Development
Use the powerful and extensible LangChain framework, using prompts, parsing, memory, chains, question answering, and agents.
AI for Everyone
Learn about AI technologies and how to use them. Examine AI's societal impact, and learn to navigate this technological shift.
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Building Adaptive AI Agents
Building Adaptive AI Agents
AI agents often repeat the same mistakes because they carry nothing forward between sessions. This course teaches three ways to fix that. Learners build a pipeline that turns agent traces into reusable, human-approved skills, build a code knowledge graph that improves retrieval in large codebases, and learn when to adapt the model itself. The result is agents that improve with every run.
AI Coding Workflows: From Cloud to Local
AI Coding Workflows: From Cloud to Local
Learn to take control of your AI coding workflow. Starting from a Claude Code baseline, you'll structure work for smaller models, switch coding agents, connect to different models and providers, and progress from cloud to hybrid and fully local workflows. Along the way, you'll evaluate tradeoffs in cost, speed, and usage metrics.
AI can write more code than any team can review by hand. In this hands-on course with Qodo, you'll learn how to make AI code review effective, from running reviews early to giving the reviewer the right context. Then you'll build your own review agent and see why context is what makes a review reliable.
What matters in AI right now
Inside Key Changes in Data Policies, Ox Alpha Revealed, Taking Custom Models Beyond Fine-Tuning
The Batch News & Insights: A key AI engineering skill is using coding agents.
GLM-5.3’s Exploits, AI Models and Hardware Speed Up, DeepSeek’s New Agent Harness
The Batch News & Insights: How have software engineering fundamentals changed with agentic coding?
Anthropic’s Watermarks, Grok 4.6 Surges, Qwen’s Open Weights, Better Corrections for Speech Recognition
The Batch News & Insights: I previously wrote about our AI Engineering Skills Map, with the highest level skills being (i) Building and deploying...
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