Bem-vindo ao curso de LangChain em Python. Aprenda esta tecnologia revolucionária que permite que você desenvolva aplicações completas usando IA Generativa com Grandes Modelos de Linguagem. Este curso foi cuidadosamente desenvolvido para fornecer a você um entendimento profundo e prático das mais recentes tecnologias de processamento de linguagem natural e integração de modelos de linguagem de grande escala. O que você aprenderá:
Read more
Bem-vindo ao curso de LangChain em Python. Aprenda esta tecnologia revolucionária que permite que você desenvolva aplicações completas usando IA Generativa com Grandes Modelos de Linguagem. Este curso foi cuidadosamente desenvolvido para fornecer a você um entendimento profundo e prático das mais recentes tecnologias de processamento de linguagem natural e integração de modelos de linguagem de grande escala. O que você aprenderá:
Bem-vindo ao curso de LangChain em Python. Aprenda esta tecnologia revolucionária que permite que você desenvolva aplicações completas usando IA Generativa com Grandes Modelos de Linguagem. Este curso foi cuidadosamente desenvolvido para fornecer a você um entendimento profundo e prático das mais recentes tecnologias de processamento de linguagem natural e integração de modelos de linguagem de grande escala. O que você aprenderá:
1. Introdução: Apresentação do curso e configuração do ambiente.
2.Uso de LLMs: Exemplos práticos de uso de modelos de linguagem (LLMs) com OpenAI, incluindo completion e chat.
3. LangChain: Conceitos fundamentais e avançados: caching, templates, chains, sequential chains, router chains, tools, agents, e react agents.
4. Embeddings: Criação e utilização de embeddings para representar texto em espaços vetoriais.
5. Aplicação de LLM Web com Streamlit: Desenvolvimento de aplicações web interativas utilizando Streamlit e LLMs.
6. Vectorstores e Pinecone: Armazenamento e recuperação de vetores com Pinecone.
7. RAG (Retrieval-Augmented Generation): Implementação de busca semântica em documentos jurídicos.
8. Usando Outros Modelos: Exemplos práticos com modelos alternativos, como o Gemini do Google.
Você ainda vai ter:
Suporte Completo: Estamos aqui para ajudar você em cada etapa do seu aprendizado.
Acesso Vitalício: Revise e estude no seu próprio ritmo, a qualquer momento.
Certificado de Conclusão: Comprove seu conhecimento e avance em sua carreira.
Material Complementar: Recursos adicionais para aprofundar seu entendimento.
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What's inside
Learning objectives
- Explore chains, sequential chains e router chains no langchain.
- Domine o uso de langchain, incluindo caching e templates.
- Utilize tools, agents e react agents para tarefas avançadas.
- Crie e utilize embeddings para representar textos em espaços vetoriais.
- Desenvolva aplicações web interativas com streamlit e llms.
- Aprenda a armazenar e recuperar vetores usando pinecone.
- Implemente buscas semânticas em documentos jurídicos com rag.
- Veja exemplos práticos com o modelo gemini do google.
- Aplique técnicas avançadas de nlp com langchain.
- Melhore suas habilidades em ia com exemplos práticos e projetos
- Explore chains, sequential chains e router chains no langchain.
- Domine o uso de langchain, incluindo caching e templates.
- Utilize tools, agents e react agents para tarefas avançadas.
- Crie e utilize embeddings para representar textos em espaços vetoriais.
- Desenvolva aplicações web interativas com streamlit e llms.
- Aprenda a armazenar e recuperar vetores usando pinecone.
- Implemente buscas semânticas em documentos jurídicos com rag.
- Veja exemplos práticos com o modelo gemini do google.
- Aplique técnicas avançadas de nlp com langchain.
- Melhore suas habilidades em ia com exemplos práticos e projetos
Syllabus
Modelos da OpenAI
Apresentação
Introdução
O que é LangChain e para que Serve
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Syllabus
Good to know
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Activities
Review NLP Concepts
Show steps
Solidify your understanding of NLP concepts to enhance your learning in this course.
Browse courses on
NLP
Show steps
-
Review materials from previous NLP courses or tutorials.
-
Focus on core NLP concepts such as tokenization, stemming, and part-of-speech tagging.
-
Practice applying these concepts using NLP libraries.
Execute LLMs
Show steps
Practice using LLMs to understand their capabilities and limitations.
Browse courses on
LLMs
Show steps
-
Choose an LLM (e.g., OpenAI's GPT-3 or GPT-J).
-
Experiment with different prompts and observe the responses.
-
Analyze the responses to identify patterns and biases.
Explore LangChain Documentation
Show steps
Gain a thorough understanding of LangChain's capabilities and usage.
Browse courses on
LangChain
Show steps
-
Review the official LangChain documentation.
-
Follow tutorials on specific topics, such as creating chains or using tools.
-
Experiment with the code examples provided in the tutorials.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in LangChain Community Discussions
Show steps
Engage with other LangChain users to exchange ideas and learn from their experiences.
Browse courses on
LangChain
Show steps
-
Join the LangChain community forum or Discord server.
-
Participate in discussions on topics related to LangChain.
-
Ask questions and share your knowledge with others.
Attend a LangChain Workshop
Show steps
Immerse yourself in LangChain by attending a hands-on workshop led by experts.
Browse courses on
LangChain
Show steps
-
Find a reputable LangChain workshop in your area or online.
-
Register for the workshop and prepare any necessary materials.
-
Actively participate in the workshop, ask questions, and network with other attendees.
Explore Advanced LangChain Features
Show steps
Expand your knowledge of LangChain's capabilities by learning about advanced features.
Browse courses on
LangChain
Show steps
-
Review documentation or tutorials on topics such as caching or agents.
-
Experiment with these features in your own LangChain applications.
-
Explore examples and best practices for using advanced features effectively.
Write a LangChain Tutorial
Show steps
Share your knowledge by creating a tutorial that guides others in using LangChain.
Browse courses on
LangChain
Show steps
-
Choose a specific topic within LangChain to focus on.
-
Develop a step-by-step guide with clear explanations and code examples.
-
Publish your tutorial on a platform like Medium or GitHub.
Develop a LangChain Application
Show steps
Apply your knowledge by building a practical application using LangChain.
Browse courses on
LangChain
Show steps
-
Identify a problem or use case that LangChain can solve.
-
Design and implement a solution using LangChain.
-
Test and iterate on your application to improve its functionality.
Review NLP Concepts
Show steps
Solidify your understanding of NLP concepts to enhance your learning in this course.
Browse courses on
NLP
Show steps
- Review materials from previous NLP courses or tutorials.
- Focus on core NLP concepts such as tokenization, stemming, and part-of-speech tagging.
- Practice applying these concepts using NLP libraries.
Execute LLMs
Show steps
Practice using LLMs to understand their capabilities and limitations.
Browse courses on
LLMs
Show steps
- Choose an LLM (e.g., OpenAI's GPT-3 or GPT-J).
- Experiment with different prompts and observe the responses.
- Analyze the responses to identify patterns and biases.
Explore LangChain Documentation
Show steps
Gain a thorough understanding of LangChain's capabilities and usage.
Browse courses on
LangChain
Show steps
- Review the official LangChain documentation.
- Follow tutorials on specific topics, such as creating chains or using tools.
- Experiment with the code examples provided in the tutorials.
Participate in LangChain Community Discussions
Show steps
Engage with other LangChain users to exchange ideas and learn from their experiences.
Browse courses on
LangChain
Show steps
- Join the LangChain community forum or Discord server.
- Participate in discussions on topics related to LangChain.
- Ask questions and share your knowledge with others.
Attend a LangChain Workshop
Show steps
Immerse yourself in LangChain by attending a hands-on workshop led by experts.
Browse courses on
LangChain
Show steps
- Find a reputable LangChain workshop in your area or online.
- Register for the workshop and prepare any necessary materials.
- Actively participate in the workshop, ask questions, and network with other attendees.
Explore Advanced LangChain Features
Show steps
Expand your knowledge of LangChain's capabilities by learning about advanced features.
Browse courses on
LangChain
Show steps
- Review documentation or tutorials on topics such as caching or agents.
- Experiment with these features in your own LangChain applications.
- Explore examples and best practices for using advanced features effectively.
Write a LangChain Tutorial
Show steps
Share your knowledge by creating a tutorial that guides others in using LangChain.
Browse courses on
LangChain
Show steps
- Choose a specific topic within LangChain to focus on.
- Develop a step-by-step guide with clear explanations and code examples.
- Publish your tutorial on a platform like Medium or GitHub.
Develop a LangChain Application
Show steps
Apply your knowledge by building a practical application using LangChain.
Browse courses on
LangChain
Show steps
- Identify a problem or use case that LangChain can solve.
- Design and implement a solution using LangChain.
- Test and iterate on your application to improve its functionality.
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