ISBN: 9798184567396 - building ai agents in 21 days: a hands-on course in agentic systems with python and llms (6 risultati)

Taschenbuch. Condizione: Neu. Neuware.

Paperback. Condizione: new. Paperback. Building AI Agents in 21 DaysA Hands-On Course in Agentic Systems with Python and LLMsby M. Saqib ================================================================Go from a single line that calls a language model to a deployed, autonomous agent that plans, uses tools, checks its own work, andrecovers from failure - in three focused weeks.================================================================ Most "AI agent" books hand you a framework and a magic import. Youend up with a demo you can't debug and only a hazy idea of what theagent actually does. This book is the opposite. You build the agentyourself, from the loop up, in plain Python - so when somethingbreaks, you know exactly why. You call Claude through the official Anthropic Python SDK and writeevery part by hand: the control loop, the tools, memory, retrieval, planning, guardrails, and the deployment around it. Frameworks likeLangGraph and CrewAI are explained so you can read them - but younever hide behind one. By Day 21 an agent is no longer magic. It issomething you can build, measure, and ship. WHAT YOU GET- 21 day-chapters (3 weeks x 7 days) of careful, worked teaching -no filler, no hand-waving.- 150+ runnable Python listings with real output.- 246 figures and diagrams - loop diagrams, sequence diagrams, andmeasured plots.- A clean, print-friendly layout, and a per-day workshop (quiz andexercises) so each idea lands in your hands. THE 21 DAYSWeek 1 - Foundations Day 1. What Is an Agent? The Loop That Thinks Day 2. Tool Calling - Giving the Model Hands Day 3. The Agent Loop Day 4. ReAct - Reasoning Before Acting Day 5. Memory & the Context Window Day 6. Structured Output You Can Trust Day 7. Errors, Timeouts, and a Resilient LoopWeek 2 - Capability Day 8. Designing Tools the Model Can Use Day 9. Retrieval as a Tool (RAG) Day 10. Planning vs. Reacting Day 11. Multi-Step Tasks & Working State Day 12. Self-Correction & Reflection Day 13. Cost and Latency Budgeting Day 14. Tracing and ObservabilityWeek 3 - Robustness and Scale Day 15. Evaluating Agents Day 16. Guardrails and Safety Day 17. Human in the Loop Day 18. Multi-Agent Orchestration Day 19. Long-Running & Background Agents Day 20. Deploying an Agent Day 21. Capstone - A Complete Agent, End to End WHO IT'S FORYou know ordinary Python - functions, dictionaries, exceptions. Youdo NOT need any machine-learning background, and you will not train amodel; you call one and build the system around it. You need anAnthropic API key; each call costs a fraction of a cent, and thewhole book runs for about the price of a coffee. BY DAY 21 YOU CAN- build the agent loop that calls a model, runs its tools, and feedsthe results back until the task is done;- design tools, schemas, and structured output the model uses well;- ground an agent's answers in your own documents with retrieval;- make an agent plan, reflect, and correct itself;- measure and cut what every run costs in tokens and time;- evaluate an agent like code, guard it against bad input and promptinjection, and deploy it as a real service. The agent stops being a black box. Go build one that works. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: New. Print on Demand.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. Building AI Agents in 21 DaysA Hands-On Course in Agentic Systems with Python and LLMsby M. Saqib ================================================================Go from a single line that calls a language model to a deployed, autonomous agent that plans, uses tools, checks its own work, andrecovers from failure - in three focused weeks.================================================================ Most "AI agent" books hand you a framework and a magic import. Youend up with a demo you can't debug and only a hazy idea of what theagent actually does. This book is the opposite. You build the agentyourself, from the loop up, in plain Python - so when somethingbreaks, you know exactly why. You call Claude through the official Anthropic Python SDK and writeevery part by hand: the control loop, the tools, memory, retrieval, planning, guardrails, and the deployment around it. Frameworks likeLangGraph and CrewAI are explained so you can read them - but younever hide behind one. By Day 21 an agent is no longer magic. It issomething you can build, measure, and ship. WHAT YOU GET- 21 day-chapters (3 weeks x 7 days) of careful, worked teaching -no filler, no hand-waving.- 150+ runnable Python listings with real output.- 246 figures and diagrams - loop diagrams, sequence diagrams, andmeasured plots.- A clean, print-friendly layout, and a per-day workshop (quiz andexercises) so each idea lands in your hands. THE 21 DAYSWeek 1 - Foundations Day 1. What Is an Agent? The Loop That Thinks Day 2. Tool Calling - Giving the Model Hands Day 3. The Agent Loop Day 4. ReAct - Reasoning Before Acting Day 5. Memory & the Context Window Day 6. Structured Output You Can Trust Day 7. Errors, Timeouts, and a Resilient LoopWeek 2 - Capability Day 8. Designing Tools the Model Can Use Day 9. Retrieval as a Tool (RAG) Day 10. Planning vs. Reacting Day 11. Multi-Step Tasks & Working State Day 12. Self-Correction & Reflection Day 13. Cost and Latency Budgeting Day 14. Tracing and ObservabilityWeek 3 - Robustness and Scale Day 15. Evaluating Agents Day 16. Guardrails and Safety Day 17. Human in the Loop Day 18. Multi-Agent Orchestration Day 19. Long-Running & Background Agents Day 20. Deploying an Agent Day 21. Capstone - A Complete Agent, End to End WHO IT'S FORYou know ordinary Python - functions, dictionaries, exceptions. Youdo NOT need any machine-learning background, and you will not train amodel; you call one and build the system around it. You need anAnthropic API key; each call costs a fraction of a cent, and thewhole book runs for about the price of a coffee. BY DAY 21 YOU CAN- build the agent loop that calls a model, runs its tools, and feedsthe results back until the task is done;- design tools, schemas, and structured output the model uses well;- ground an agent's answers in your own documents with retrieval;- make an agent plan, reflect, and correct itself;- measure and cut what every run costs in tokens and time;- evaluate an agent like code, guard it against bad input and promptinjection, and deploy it as a real service. The agent stops being a black box. Go build one that works. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…