Course Description

Natural Language Processing & Conversational AI is transforming how businesses interact with customers, automate workflows, and extract insights from text data. This comprehensive technical course equips software engineers and technical professionals with production-ready skills to build, deploy, and maintain sophisticated conversational AI systems. Starting with NLP fundamentals and progressing to advanced LLM integration, you'll master the complete stack of technologies powering modern chatbots, voice assistants, and intelligent automation systems. Through hands-on projects using industry-standard tools like OpenAI GPT-4, Anthropic Claude, LangChain, Rasa, spaCy, and NLTK, you'll learn to architect scalable conversational systems that handle real-world complexity. The curriculum emphasizes practical implementation over theory, covering critical production concerns like context management, error handling, performance optimization, and monitoring. You'll build multiple complete projects including rule-based chatbots, retrieval-augmented generation (RAG) systems, multi-turn conversational agents, voice-enabled assistants, and enterprise-grade workflow automation. Each module includes Python implementations with TypeScript alternatives, real-world case studies from leading tech companies, debugging strategies, and common pitfall avoidance. By course completion, you'll possess the expertise to architect conversational AI solutions, integrate cutting-edge LLMs into production applications, optimize for cost and latency, implement robust error handling and fallback strategies, and deploy scalable systems that deliver exceptional user experiences. Whether you're building customer service automation, internal productivity tools, or innovative AI-powered products, this course provides the comprehensive technical foundation and practical experience needed to succeed in the rapidly growing field of conversational AI engineering.