Master Agentic AI with LangGraph, Streamlit and OpenAI

Build Agentic AI applications with Python, LangGraph, LangChain and OpenAI

What you'll learn
- Understand agentic ai workflows and systems
- Implement agentic ai systems with LangGraph, OpenAI and Streamlit
- Automate complex business workflows with agentic ai
- Human in the loop interactions with mission critical work flows
- LangGraph Event Streams
- LLM tool calling workflow agents with Structured Output
- Agentic Design Patterns
- Implement fast, robust and reliable streaming AI applications

Requirements
- Interest in Generative AI and Agentic AI
- Any programming language knowledge(Python preferred)

Description
Agentic AI has become more disruptive than Generative AI these days.Organisations are rushing to transform their business models to implement agentic ai applications to unlock business value to stay ahead of the curve. As organisations transform their readily available workflows to leverage agentic AI  they will come across new business workflows that might exponentially add value to their revenue streams. So agentic ai has already impacted profoundly across sectors and verticles. As technology and solution providers we have to stay ahead of the curve on disruptive modern technologies such as in order to be relavant to our customers and guide them in the Gen Ai and Agentic AI adoption journey.LangGraph, LangChain,  Streamlit, OpenAI, Python is an ideal blend of technologies to implement most of the agentic ai business work flows robust, reliable and secure manner in highly agile product and development environments.Features such as data streaming, LLM tool calling, LLM structured output, short term context windows, long term stateful knowledge graphs, Time Travel etc are invaluable features to implement highly scalable, fast, robust, reliable and trustworthy agentic applications.Human in the loop is vital when agentic ai is infused into mission critical workflows to safeguard data layer.LangGraph interrupts, event systems and state preservation mechanism foundationally enable LangGraph to be equipped with reliable human in the loop implementations.Primary technologies used in this course are as below.

Agentic AI

Generative AI

LangGraph

LangChain

Streamlit

Python

OpenAI

VsCode

Who this course is for:
- Generative AI practitioners interested in Agentic AI
- Python developers interested in Agentic AI
- Business Consultants interested in transforming applicaions to use Agentic AI
- Anyone passionate on cutting edge technologies
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