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Modern Automated AI Agents: Building Agentic AI to Perform Complex Tasks - Farid - 02-11-2025
![[Image: 424edd571e3a51a34222b6b99d107041.jpg]](https://i124.fastpic.org/big/2025/0209/41/424edd571e3a51a34222b6b99d107041.jpg)
Release year : January 2025
Manufacturer : Published by Pearson Via O'Reilly Learning
Author : Sinan Ozdemir
Duration : 5h 37m
Type of material given : Video lesson
Language : En + subtitles
Description:
Get started with automated AI agents
Overview
Modern Automated AI Agents introduces you to the concept of automated agents. It then helps you build a solid understanding of how to design, build, and optimize AI agents to tackle real-world challenges.
About the Instructor
Sinan Ozdemir is the founder and CTO of LoopGenius, where he uses state-of-the-art AI to help people create and run their businesses. Sinan is a former lecturer of Data Science at Johns Hopkins University and the author of multiple textbooks and videos on data science and machine learning. Additionally, he is the founder of the recently acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. He holds a master's degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco, California.
Learn How To
Build & use AI agents
Evaluate AI agent frameworks
Start to use CrewAI
Design multi-step workflows with LangGraph
Use large language models (LLMs)
Integrate existing and custom tools
Use thought, action, observation, and response components
Test and evaluate agents, their responses, backstories, definitions, and rules
Add planning and reflection to agents to bolster performance
Who Should Take This Course
Developers, data scientists, and engineers who are interested in building intelligent, autonomous AI agents capable of solving complex problems and adapting to dynamic environments
Course Requirements
Python 3 proficiency with some experience working in interactive Python environments including Notebooks (Jupyter/Google Colab/Kaggle Kernels)
Comfortable using the Pandas library and either Tensorflow or PyTorch
Understanding of ML/deep learning fundamentals including train/test splits, loss/cost functions, and gradient descent
Content
Introduction
Lesson 1 Introduction to AI Agents
Lesson 2 Under the Hood of AI Agents
Lesson 3 Building an AI Agent
Lesson 4 Testing and Evaluating Agents
Lesson 5 Expanding on ReAct with Planning and Reflection
Lesson 6 Advanced Applications and Future Directions
Summary
Example files : no
Format Video : mp4
Video : AVC, 1280 x 720, 16: 9, 30.000 FPS, 3,000 KB/S (0.017 Bit/Pixel)
Аудио: AAC, 44.1 KHz, 2 channels, 128 kb/s, CBR
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📌 Modern Automated AI Agents Building Agentic AI to Perform Complex Tasks (1.7 GB)
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