Welcome To The Course (1:15)
What Are AI Agents & Workflows? (4:55)
An AI Agent You All Know (2:19)
About This Course - What To Expect (2:09)
Building AI Workflows & Applications
Module Introduction (2:21)
No Code vs With Code (2:07)
Building AI Apps & Using AI Programmatically (4:12)
Proprietary vs Open (Local) LLMs (5:51)
Using Open LLMs
Understanding Our Development Environment (2:29)
Creating a New Python Project (using "uv") (1:43)
OpenAI Setup & Pricing (5:41)
Getting Started With A First Example Workflow (2:44)
Preparing HTTP Requests For The OpenAI API (8:40)
Choosing & Using a Model (2:04)
Prompt Engineering (4:35)
Extracting & Using the LLM Response (4:50)
More on the OpenAI API & SDK
Code Deep Dives vs Provided Code Snippets
Use Those Docs (1:38)
Using The OpenAI Python SDK (5:49)
Leveraging Few-Shot Prompting (4:02)
Generating Prompts Dynamically With Energetic Content (2:12)
Building Multi-Step & Multi-Model Workflows (6:47)
Workflows vs Agentic Systems (1:34)
Using Locally Running Open Models via Ollama (8:08)
Enforcing & Using Structured Outputs (10:53)
More On JSON Schemas & Structured Outputs
Structured Outputs via SDK & Pydantic (3:56)
Using Prompt Engineering To Control Output
Onwards To Another Example (5:38)
Generating Images In a Workflow (6:27)
Controlling Workflow Execution with Control Flow Adjustments (2:45)
Control Flow In Action (8:42)
Adding a "Human In The Loop" (6:51)
Integrating External Services - Example: Slack (6:21)
Important: Potential Problems & Security Risks
Building AI Agents
Module Introduction (1:36)
How LLMs (Do Not) Use Tools (6:04)
Implementing Tool Use From Scratch (11:24)
Using OpenAI's Function Calling Feature (10:23)
Building a Multi-Tool Versatile Agent (11:16)
Using Advanced AI Models
Building Reusable Elements With Classes (7:53)
Getting Started with a Multi-Agent System (7:14)
Building &
📌 Creating a New Python Project (Alipur)
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📍 Alipur
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