
Learn to create interactive web apps for data science using Streamlit. Explore basic concepts, add widgets, interact with data, and deploy to the cloud. Build apps for visualization, model training, and analytics.

Develop a Streamlit data app to visualize advertising ROI using Snowpark Python. Learn data ingestion, transformation, ML modeling, and interactive visualization techniques.

Explore innovative Python tools and data storytelling techniques to create engaging, impactful presentations. Learn to combine interactivity and memorability for more effective communication.

Desarrolla un chatbot multimodal con Vertex AI, Gemini Pro y Streamlit, y despliégalo en Google App Engine para aplicaciones de aprendizaje automático.

Learn to build an AI-powered web scraper using Python, Selenium, BeautifulSoup, and LangChain. Extract specific information from websites with AI-driven parsing and overcome common scraping challenges.

Build a local RAG system for PDFs using LLMs, LangChain & Streamlit. Extract text, create vector stores, implement advanced retrieval, and integrate local/remote LLMs for efficient document processing.

Explore innovative Python tools and data storytelling techniques to create engaging, interactive presentations that captivate audiences and enhance information retention.

Deep dive into advanced Streamlit features for building robust, performant web apps in Python. Learn caching, session state management, and app testing through a multi-page GitHub activity dashboard with chatbot integration.

Learn to build a voice-controlled AI assistant using Python, Streamlit, LangChain, and Ollama in under 100 lines of code. Create your own local version of Alexa through hands-on coding.

Dive into building an end-to-end RAG application using Langchain, multiple LLMs, and vector stores to enable interactive conversations with unstructured data through a Streamlit interface.

Dive into containerization with Docker and Docker Compose while building a RAG application that processes unstructured data using LangChain, multiple LLMs, and vector stores through Streamlit.

Master building a conversational PDF bot using Streamlit, LlamaIndex, and Nvidia NIM to create interactive document-based chat applications with advanced RAG capabilities.