Overview
Implement LLMs via API (free and paid) or locally, exploring various models like Llama, Deepseek, ChatGPT, Gemini, and more, Develop a marketing assistant to generate and adapt content for different audiences, platforms, and goals at scale, Build a RAG-powered chatbot that answers questions using company documents to deliver consistent answers, speed up support, and reduce costs, Create a resume analyzer to automatically screen and classify the most suitable candidates, extract structured information, and provide relevant insights, Implement an AI agent that generates personalized exercises with explanations and automatically exports them to editable files, Build a financial AI agent to interpret reports, generate summaries, and answer questions with full transparency, Develop a virtual travel guide using a multi-agent system to create personalized itineraries based on a traveler's profile, Implement an agent that connects to a SQL database to analyze product reviews, generate useful summaries, and answer questions in natural language, Build a medical agent to analyze images, generate detailed reports, and retrieve up-to-date scientific references to support its findings, Create professional and intuitive user interfaces for your Artificial Intelligence applications using Streamlit
Professionals from any field looking to practically apply LLMs to solve real-world problems, Entrepreneurs and business leaders who want to leverage generative AI to innovate, automate processes, and gain a competitive edge, Consultants, freelancers, and independent professionals who want to deliver custom, AI-powered solutions to their clients, AI and innovation enthusiasts interested in exploring the practical applications of LLMs and agents across various industries, Developers looking to expand their skill set in generative AI and learn from real-world case studies to build a strong portfolio
Programming logic, Basic Python programming
Discover how Generative Artificial Intelligence is transforming businesses by driving innovation and efficiency across multiple industries! This hands-on course offers an immersive dive into the world of LLMs (Large Language Models) and AI Agents, equipping you to create intelligent, automated solutions for real-world business challenges.
With the rapid advancement of NLP (Natural Language Processing) and language models, companies and professionals are adopting these technologies to boost productivity and make decisions with greater precision. With this in mind, this course was designed to provide you with a practical, direct, and applicable learning experience. You will learn to implement solutions in Python, with a focus on applying LLMs to business contexts, but with skills that are versatile enough to be adapted to any real-world challenge.
Throughout the course, you will master the key tools and frameworks in the generative AI ecosystem, including LangChain, LangGraph, LlamaIndex, CrewAI, Agno, and other open-source solutions. Learn to implement LLMs via Python APIs (both free and paid) or locally, exploring models such as Llama, DeepSeek, ChatGPT, Gemini, and more — always with an emphasis on real-world, scalable applications.
You will act as a professional tasked with addressing diverse business needs. Through 8 practical case studies, you will be challenged to develop useful, customized applications applying generative AI in:
Marketing: Create an AI marketing assistant to scale content creation. Effortlessly adapt text for diverse audiences, platforms, and goals.
Customer Service & Support: Develop intelligent chatbots with RAG. Use real documents (e.g., manuals, PDFs) to provide accurate answers to customer questions.
Human Resources: Automatically screen resumes and classify candidates. Extract structured information and gain relevant insights.
Education: Generate personalized exercises based on a student's level and preferences, and automatically export them to editable files. Obtain detailed explanations and a 24/7 tutor with access to tools.
Finance: Interpret financial reports and generate automated summaries with ease. Query the agent and receive transparent, data-driven answers.
Tourism: Develop virtual guides to create personalized itineraries with a multi-agent system. Gain control over each agent's role in crafting the final itinerary.
Retail/E-commerce: Analyze product reviews and extract relevant summaries. Connect to a SQL database to analyze and answer questions asked in natural language.
Medicine: Automate medical image analysis and generate detailed reports. Include reference search to support final conclusions.
Throughout the course, you will explore multiple techniques and concepts, including prompt engineering, RAG (Retrieval-Augmented Generation), vector database search (local and cloud), document parsing and preprocessing, structured data export (e.g., JSON), reasoning models, AI agents integrated with tools, multi-agent systems, and multimodal LLMs for image analysis, among others.
Additionally, for each case study, you will develop a professional and intuitive user interface using the Streamlit library, ensuring usability and practical applicability of the solutions.
To make access and experimentation easier, the course focuses on Google Colab, a free and accessible environment for all students, without requiring local infrastructure or advanced hardware. You will also learn to implement and run solutions locally, expanding your development and deployment options.
Get ready to turn ideas into modern solutions with generative AI!
Jones Granatyr
Olá! Meu nome é Jones Granatyr e já trabalho em torno de 10 anos com Inteligência Artificial (IA), inclusive fiz o meu mestrado e doutorado nessa área. Atualmente sou professor, pesquisador e fundador do portal IA Expert, um site com conteúdo específico sobre Inteligência Artificial. Desde que iniciei na Udemy criei vários cursos sobre diversos assuntos de IA, como por exemplo: Deep Learning, Machine Learning, Data Science, Redes Neurais Artificiais, Algoritmos Genéticos, Detecção e Reconhecimento Facial, Algoritmos de Busca, Mineração de Textos, Buscas em Textos, Mineração de Regras de Associação, Sistemas Especialistas e Sistemas de Recomendação. Os cursos são abordados em diversas linguagens de programação (Python, R e Java) e com várias ferramentas/tecnologias (tensorflow, keras, pandas, sklearn, opencv, dlib, weka, nltk, por exemplo). Meu principal objetivo é desmistificar a área de IA e ajudar profissionais de TI a entenderem como essa tecnologia pode ser utilizada na prática e que possam visualizar novas oportunidades de negócios.