Python & LLM – AI Chatbot Architecture (AIPLLM)

Programming, Python

Would you like to take your company’s automation to the next level and build intelligent AI assistants that truly understand your data?

This intensive, hands-on course will guide you through the complete development process for modern chatbots, from architecture to production deployment.

THIS TRAINING COURSE WILL HELP YOU:

  • Design a modern AI chatbot architecture, from the user interface and LLM to logging and cost tracking
  • Work effectively with the LangChain framework in Python, including chains, parsers, memory, and templates
  • Integrate leading LLM models, including OpenAI GPT-5.4, Anthropic Claude Sonnet, and Google Gemini 3, and implement fallback strategies
  • Apply advanced prompt engineering and security guardrails to prevent hallucinations
  • Implement a RAG (Retrieval-Augmented Generation) architecture for company documents, including PDFs, SQL, and databases, using vector databases and embeddings
  • Create AI agents with Function Calling and connections to external systems, including CRM systems, search engines, and APIs
  • Measure quality and perform evaluations using tracing, regression tests, latency monitoring, and financial tracking
  • Deploy a finished chatbot to production, including API key security, rate limiting, and session management

WHO SHOULD ATTEND?

  • Python developers and backend engineers – developers who want to add advanced conversational logic, RAG architecture, and agent behavior to their applications using LangChain
  • Software architects and IT leaders – professionals responsible for designing the overall architecture of AI solutions, selecting suitable LLM models, managing costs and latency, and ensuring security
  • Data Scientists and AI/ML specialists – anyone who wants to connect language models effectively with internal databases, knowledge bases such as PDFs and SQL, and company APIs
  • Innovation and product engineers – technically oriented professionals tasked with designing and implementing autonomous assistants, internal copilots, and automated agents

COURSE LOCATION AND AVAILABLE DATES



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Course content:

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  • Artificial Intelligence – Chatbot Development and Solution Architecture
    1. what a modern AI chatbot is
    2. chatbot types: FAQ, internal assistant, customer support, copilots
    3. basic architecture: UI, backend, LLM, memory, tools, databases, logging
  • Working with LangChain in Python
    1. installation and project structure
    2. basic LangChain building blocks
    3. prompts, chains, output parsers
    4. working with conversations and message history
  • Connecting to LLM APIs
    1. selecting a provider and model
    2. connecting via an API key
    3. working with model parameters, limits, latency, and costs
    4. fallback strategies between models
  • Model Overview
    1. OpenAI: GPT-5.4
    2. Anthropic: Claude Sonnet
    3. Google: Gemini 3
  • Prompt Engineering in LangChain
    1. system instructions and roles
    2. prompt templates
    3. controlling the response format
    4. guardrails and hallucination reduction
  • Chatbot with Memory and Conversational Logic
    1. short-term and long-term memory
    2. summarising conversation history
    3. context window and its limitations
    4. chatbot state and session management
  • RAG in Practice
    1. when to use RAG and when not to
    2. document ingestion
    3. chunking, metadata, retrieval
    4. embeddings and vector stores
    5. citing sources in responses
  • Tools, Function Calling, and Agentic Behaviour
    1. tools for search, calculations, databases, and CRM
    2. calling functions from LangChain
    3. when to use a chain and when to use an agent
    4. safe use of tools
  • Integration with Data and External Systems
    1. PDFs, web, databases, APIs
    2. connecting to SQL / NoSQL
    3. working with an internal knowledge base
    4. connecting to company systems
  • Quality, Testing, and Evaluation
    1. prompt test sets
    2. measuring accuracy, relevance, and costs
    3. regression testing of responses
    4. observability and tracing
  • Deployment and Operations
    1. development and production environments
    2. key and configuration management
    3. rate limiting, retries, timeouts
    4. scaling and cost monitoring
  • Final Project
    1. design and implementation of a fully functional chatbot
    2. RAG over your own content
    3. connecting to external tools
    4. deployment to a production environment
Schedule:
2 days (9:00-17:00)
Price per person:
496.00 € ( 600.16 € incl. 21% VAT)

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