Build Data Analytics Multi Agent System with Google ADK & LLMs

akshay nair · Advanced ·🧠 Large Language Models ·1y ago

About this lesson

Learn to build a powerful Data Analytics Multi-Agent System from scratch using Google's Agent Development Kit (ADK)! This comprehensive tutorial guides you step-by-step through designing and coding a collaborative AI system that leverages Google Gemini and OpenAI LLMs to transform raw data into actionable insights. Perfect for intermediate data scientists and developers looking to explore the cutting edge of AI and distributed systems. In this video, you'll master: Designing multi-agent architectures tailored for data analytics tasks. Implementing diverse agent types (Data Collectors, Preprocessors, LLM Analysts, Visualizers) in Python using Google ADK. Integrating Google Gemini (via Vertex AI) and OpenAI (e.g., GPT-4o via LiteLLM) for advanced data analysis. Orchestrating inter-agent communication and managing data flow using ADK's state management. Generating meaningful data visualizations with Matplotlib and Seaborn based on agent outputs. 🔗 GitHub Repository (Complete Code): https://github.com/Ak-9647/data_analytics_mas 🛠️ Tools & Technologies Used: Python, Google Agent Development Kit (ADK), Google Cloud Vertex AI (for Gemini), OpenAI API (e.g., GPT-4o), LiteLLM, Pandas, Matplotlib, Seaborn. ✨ Key Concepts Covered: Multi-Agent Systems (MAS), Agent-Based Modeling, Google ADK, Large Language Models (LLMs), Google Gemini, OpenAI GPT, Data Pipelines, Data Collection, Data Preprocessing, AI-Powered Analysis, Data Visualization, Python for Data Science, Distributed AI Systems, Vertex AI, LiteLLM. 👍 Like this video if you found it helpful and learned something new! 🔔 Subscribe to the channel and hit the notification bell for more tutorials on AI, Multi-Agent Systems, and Data Science. 💬 Have questions or want to share what you're building? Comment below – we love hearing from you! #DataAnalytics #MultiAgentSystem #GoogleADK #Python #AI #ArtificialIntelligence #GoogleGemini #OpenAI #GPT #LLM #VertexAI #DistributedSystems #DataScience #CodingTutorial #Te

Original Description

Learn to build a powerful Data Analytics Multi-Agent System from scratch using Google's Agent Development Kit (ADK)! This comprehensive tutorial guides you step-by-step through designing and coding a collaborative AI system that leverages Google Gemini and OpenAI LLMs to transform raw data into actionable insights. Perfect for intermediate data scientists and developers looking to explore the cutting edge of AI and distributed systems. In this video, you'll master: Designing multi-agent architectures tailored for data analytics tasks. Implementing diverse agent types (Data Collectors, Preprocessors, LLM Analysts, Visualizers) in Python using Google ADK. Integrating Google Gemini (via Vertex AI) and OpenAI (e.g., GPT-4o via LiteLLM) for advanced data analysis. Orchestrating inter-agent communication and managing data flow using ADK's state management. Generating meaningful data visualizations with Matplotlib and Seaborn based on agent outputs. 🔗 GitHub Repository (Complete Code): https://github.com/Ak-9647/data_analytics_mas 🛠️ Tools & Technologies Used: Python, Google Agent Development Kit (ADK), Google Cloud Vertex AI (for Gemini), OpenAI API (e.g., GPT-4o), LiteLLM, Pandas, Matplotlib, Seaborn. ✨ Key Concepts Covered: Multi-Agent Systems (MAS), Agent-Based Modeling, Google ADK, Large Language Models (LLMs), Google Gemini, OpenAI GPT, Data Pipelines, Data Collection, Data Preprocessing, AI-Powered Analysis, Data Visualization, Python for Data Science, Distributed AI Systems, Vertex AI, LiteLLM. 👍 Like this video if you found it helpful and learned something new! 🔔 Subscribe to the channel and hit the notification bell for more tutorials on AI, Multi-Agent Systems, and Data Science. 💬 Have questions or want to share what you're building? Comment below – we love hearing from you! #DataAnalytics #MultiAgentSystem #GoogleADK #Python #AI #ArtificialIntelligence #GoogleGemini #OpenAI #GPT #LLM #VertexAI #DistributedSystems #DataScience #CodingTutorial #Te
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