English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 67 Lessons (9h 25m) | 4.09 GB
Learn AI Agent Fundamentals from the Ground Up. Learn how to build resilient AI agents and develop Agentic AI skills in Python that will remain relevant despite the rapidly evolving AI landscape.
What you’ll learn
- Build Autonomous AI Agents – Learn how to create AI agents in Python that can operate independently, interact with APIs, and handle real-world tasks.
- Master Core and Advanced Agent Concepts – Understand agent loops, tool integration, multi-agent collaboration, and design principles.
- Optimize AI Agents for Real-World Use – Develop resilient, efficient, and maintainable agents while balancing token costs, speed, and predictability.
Skills you’ll gain
- Prompt Engineering
- Agentic AI Architecture
- Agentic AI
- AI Agent Architecture
- Python AI Agents
- AI Agents
- Generative AI
- AI Agents in Python
- AI Automation
- ChatGPT
- chain of thought prompting
- prompt patterns
- Large Language Models
AI agents are transforming the way we interact with technology, and in this specialization, you’ll learn how to build them from the ground up—without the need for complex or rigid frameworks that will be irrelevant next week. Whether you’re a beginner or an experienced developer, you’ll master the core concepts that power AI agents, giving you full control over their design and capabilities.
You’ll start with the fundamentals, understanding how agent loops work, then progress to equipping your agents with tools, integrating multi-agent systems, and implementing self-prompting for more autonomous behavior. Beyond coding, you’ll develop a deep understanding of AI architecture, learning to build resilient, modular, and maintainable agents optimized for token efficiency, speed, and predictable outcomes. By the end of this specialization, you’ll have the skills to create powerful AI agents and understand how to design them independent of any framework or programming language.
This specialization is for anyone with basic Python skills—no prior experience with AI or machine learning is required. Whether you’re just starting or already experienced, you’ll gain both foundational and advanced insights into AI agents. Beginners will get a strong start, while experts will walk away with a deeper understanding of how to innovate in this rapidly evolving space. By the end, you’ll have the skills to create powerful, future-proof AI agent skills.
Applied Learning Project
Throughout this specialization, you’ll build a variety of AI agents in Python that can operate autonomously, interact with APIs, and handle real-world challenges like error recovery and external data retrieval. These hands-on projects will give you the skills to create adaptable, functional agents capable of solving authentic problems in automation, data processing, and AI-driven decision-making.
Table of Contents
ai-agents-architecture-python
extending-ai-agents-with-self-prompting
untitled-lesson
1 prompts-as-computation
2 bridging-computer-tools-unstructured-data-with-prompting-the-ai-shim
3 the-persona-pattern-and-reasoning-personas-are-an-efficient-programming
4 the-persona-pattern
5 format-of-the-persona-pattern_instructions
6 simple-multi-agent-systems-with-personas
ai-agent-design-principles-safety
untitled-lesson
7 the-mate-design-principles-for-ai-agents
multi-agent-systems
untitled-lesson
8 introduction-to-multi-agent-systems
9 agent-interaction-memory
10 removing-noise-focusing-agent-attention
11 providing-agentic-ai-information-about-the-world
dependency-injection-for-tools
untitled-lesson
12 isolating-agents-from-accidental-complexity
approaches-to-improving-ai-agent-reasoning
untitled-lesson
13 improving-ai-agent-reasoning-with-in-context-learning
14 improving-ai-agent-reasoning-with-up-front-planning-chain-of-thought
15 improving-ai-agent-reasoning-with-in-loop-planning
16 the-great-agent-trade-off-ahead-of-time-vs-dynamic
ai-agents-python
agentic-ai-concepts
untitled-lesson
17 introduction
18 flipped-interaction-pattern
19 the-agent-loop
20 try-out-programmatic-prompting_instructions
21 try-out-the-customer-service-agent_instructions
22 adding-structure-to-ai-agent-outputs
23 learning-more-staying-connected_instructions
ai-agents-tools-actions-language
untitled-lesson
24 gail-goals-actions-information-language
25 giving-agents-tools
26 tool-descriptions-and-naming
27 tool-results-and-agent-feedback
28 try-out-an-agent-that-calls-python-functions_instructions
29 try-out-llm-function-calling_instructions
30 try-out-an-agent-loop-with-function-calling_instructions
31 exercise-extend-the-function-calling-agent_instructions
game-a-conceptual-framework-for-ai-agents
untitled-lesson
32 overview-of-the-game-framework
33 simulating-agents-in-chatgpt
34 try-out-the-agent-framework_instructions
agent-tool-mangement
untitled-lesson
35 try-out-the-readme-agent-with-the-decorator_instructions
rethinking-how-software-is-built-in-the-age-of-ai-agents
untitled-lesson
36 build-the-impossible-with-ai-agents
37 rethinking-how-we-teach-innovation
38 hallucination-is-a-new-form-of-computing
39 new-ways-to-access-and-extract-information
prompt-engineering
course-introduction
course-overview
40 motivating-example-building-a-meal-plan-with-a-fusion-of-food-from-ethiopia-and
41 overview-of-the-course
42 motivating-example-act-as-a-speech-pathologist
43 setting-up-an-account-and-using-chatgpt_instructions
large-language-model-basics
44 what-are-large-language-models
45 randomness-in-output
introduction-to-prompts
what-are-prompts
46 what-is-a-prompt
47 intuition-behind-prompts
48 everyone-can-program-with-prompts
intro-to-prompt-patterns
49 prompt-patterns
50 the-persona-pattern
51 reading-a-prompt-pattern_instructions
52 format-of-the-persona-pattern_instructions
53 learn-more-about-prompt-patterns_instructions
54 staying-connected-learning-more_instructions
prompts-conversations-new-information
55 introducing-new-information-to-the-large-language-model
56 prompt-size-limitations
57 prompts-are-a-tool-for-repeated-use
58 root-prompts
59 what-to-take-after-or-with-this-course_instructions
prompt-patterns-i
introduction-to-prompt-patterns
60 question-refinement-pattern
61 format-of-the-question-refinement-pattern_instructions
62 cognitive-verifier-pattern
63 format-of-the-cognitive-verifier-pattern_instructions
64 audience-persona-pattern
65 format-of-the-audience-persona-pattern_instructions
66 flipped-interaction-pattern
67 format-of-the-flipped-interaction-pattern_instructions
few-shot-examples
effective-prompts
68 few-shot-examples
69 few-shot-examples-for-actions
70 few-shot-examples-with-intermediate-steps
71 writing-effective-few-shot-examples
72 chain-of-thought-prompting
73 learn-more-about-chain-of-thought-prompting_instructions
74 react-prompting
75 learn-more-about-react_instructions
76 using-large-language-models-to-grade-each-other
prompt-patterns-ii
prompt-patterns-catalog
77 game-play-pattern
78 format-of-the-game-play-pattern_instructions
79 template-pattern
80 format-of-the-template-pattern_instructions
81 meta-language-creation-pattern
82 format-of-the-meta-language-creation-pattern_instructions
83 recipe-pattern
84 format-of-the-recipe-pattern_instructions
85 alternative-approaches-pattern
86 format-of-the-alternative-approaches-pattern_instructions
prompt-patterns-iii
prompt-patterns-catalog
87 ask-for-input-pattern
88 format-of-the-ask-for-input-pattern_instructions
89 combining-patterns
90 outline-expansion-pattern
91 format-of-the-outline-expansion-pattern_instructions
92 menu-actions-pattern
93 format-of-the-menu-actions-pattern_instructions
94 fact-check-list-pattern
95 format-of-the-fact-check-list-pattern_instructions
96 tail-generation-pattern
97 tail-generation-pattern_instructions
98 semantic-filter-pattern
99 format-of-the-semantic-filter-pattern_instructions
100 course-conclusion-thank-you
101 continue-learning-about-prompt-engineering_instructions
102 continue-learning-about-prompt-engineering_jules
Resources
prompt-engineering-showcase
103 resources
chatgpt
104 resources
reading-materials-on-prompt-engineering
105 jules
106 resources
prompts-used-for-creating-the-emails
107 resources
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