Follow along as I build an AI Agent in python with LangGraph to perform data science and discuss if my job is safe from automation.
Using Cursor & Streamlit for rapid prototyping.
🎥 Channel: @WW_AI_Adventures
GitHub repo:
👉 https://github.com/whitew1994WW/AgenticDataAnalysis
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Chapters
0:00 🕒 Intro
01:23 Finding a Dataset
03:45 Seeing how well ChatGPT performs
06:59 Plotly Intro
07:35 Build Part 1: Creating a Streamlit Data Upload
10:34 Build Part 2: Adding Chat to the Frontend
12:59 Build Part 3: Initial Reach Agent
19:10 Build Part 4: Passing Input Data to our Agent
22:00 Build Part 5: Executing Code in out Agent
27:10 Build Part 6: Persisting Variables between execution
36:48 Build Part 7: Plotting Inline
39:56 Final Demo!
45:00 Is my job safe as a data scientist?
47:33 Outro
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Stay Connected with Me!
📧 Email: [email protected] (Consultancy coming soon!)
💬 Discord: https://discord.gg/k3pqPcQzQG
🔗 LinkedIn: www.linkedin.com/in/william-white-data-scientist
👨💻 GitHub: https://github.com/whitew1994WW
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About
In this video, I'll be creating an AI agent with python and langgraph to perform some tasks a data scientist normally would. Machine Learning, Data Visualisation and stake holder management. Ill be using streamlit for the frontend & Ill also be using cursor througout so watch how fast you can build a great agent. There will be some advanced techniques for LangGraph relating to state management.
📌 Tags:
#AI #LangGraph #AgenticAI #OpenAI #GPT4 #Python #APIs #AIResearch #langchain #cursorai #streamlit