Overview

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A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Build practical AI-powered applications using the Claude API and modern LLM engineering techniques. You will learn how to integrate Claude models into Python applications, manage multi-turn conversations, implement memory systems, stream responses, and create structured outputs for production-ready intelligent applications. The journey begins with an in-depth exploration of the Claude model family and the Anthropic API ecosystem. You will set up API access, make your first Python requests, and progressively implement advanced conversational AI features such as chatbot memory, system prompts, streaming responses, and structured response handling. This course is designed for Python developers, AI enthusiasts, software engineers, and technical professionals who want to build intelligent applications using modern LLM APIs. Learners should have basic Python programming knowledge and familiarity with APIs. The course is best suited for intermediate learners looking to expand into AI application development and generative AI engineering. By the end of the course, you will be able to integrate the Claude API into Python applications, build memory-enabled AI chatbots, implement advanced tool-calling systems, create structured AI workflows, and develop complete RAG-powered intelligent applications using embeddings, vector databases, and contextual retrieval pipelines.

Syllabus

Introduction

In this module, we will introduce the course structure and provide an overview of the Claude API and its capabilities for building intelligent applications. You will understand the overall learning journey and the foundational concepts required to work with conversational AI systems. This section establishes the groundwork needed to confidently progress into hands-on API implementation and advanced AI workflows.

Claude API and Model Family Deep Dive

In this module, we will explore the Claude model family and learn how to access and interact with the Claude API using Python. You will build practical applications featuring conversational memory, system prompts, streaming responses, and structured outputs for intelligent AI interactions. By the end of this section, you will have hands-on experience creating dynamic chatbot systems powered by advanced Claude API capabilities.

Tools Usage with Claude API

In this module, we will focus on extending Claude API functionality through tool-calling and intelligent workflow integration. You will create custom tools, define schemas, and implement advanced chatbot systems capable of interacting with multiple tools simultaneously. This section also introduces web search tool-calling to enhance applications with real-time information retrieval and intelligent automation.

RAG - Retrieval-Augmented Generation - with the Claude API

In this module, we will build Retrieval-Augmented Generation workflows using the Claude API, embeddings, LangChain, and vector databases. You will learn how to process documents, generate embeddings, manage text chunking strategies, and retrieve relevant contextual information efficiently. By the end of this section, you will develop a complete RAG pipeline capable of generating accurate and context-aware intelligent responses.