Building AI-powered Chatbots and Virtual Assistants Designing, training, & scaling chatbots and VAs powered by LLM, NLP, and other advanced techniques

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Overview

In today’s digital landscape, chatbots and virtual assistants have transformed from novelties into essential business tools. Chatbots—automated programs designed to simulate conversation—handle routine inquiries and transactions, while virtual assistants offer more sophisticated, personalized support through natural language processing and machine learning capabilities.

As consumers increasingly expect 24/7 service and immediate responses, organizations across industries are recognizing that building customized chatbots and virtual assistant solutions isn’t merely advantageous—it’s becoming critical for competitive survival. These AI-powered assistants reduce operational costs, improve customer satisfaction through consistent service delivery, and free human employees to focus on complex, high-value tasks.

For forward-thinking organizations, developing proprietary conversational AI isn’t just about keeping pace—it’s about creating intelligent digital touchpoints that understand customer needs, reflect brand values, and deliver seamless experiences that drive loyalty in an increasingly automated world.

Cognixia’s Building AI-powered Chatbots and Virtual Assistants corporate training is designed for organizations looking to empower their teams to develop, train, and scale chatbots and virtual assistants that are powered by cutting-edge technology including natural language processing, large language models, and other advanced techniques.

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What you'll learn

  • Types and key components of chatbots
  • Fundamentals of natural language processing
  • Designing and training chatbots
  • Building chatbots with Python
  • Enhancing chatbots with LLMs and other advanced techniques
  • Creating voice-enabled virtual assistants
  • Deploying and scaling chatbots in real-world scenarios

Prerequisites

  • Basic understanding of Python programming
  • Familiarity with APIs and web services
  • Knowledge of Natural Language Processing (NLP) concepts
  • Experience with cloud platforms (AWS, Azure, GCP) is beneficial, not mandatory

Curriculum

  • Evolution of chatbots: Rule-based vs. AI-powered chatbots
  • Key components of chatbots: NLP, intent recognition, and dialogue management
  • Overview of AI models for chatbots: LLMs and transformer models
  • Understanding tokenization, Named Entity Recognition (NER), and sentiment analysis
  • Pre-trained NLP models (BERT, GPT, T5) for chatbots
  • Fine-tuning language models for domain-specific chatbots
  • Using Hugging Face transformers for NLP tasks
  • Choosing the right framework – Rasa, Dialogflow, LangChain, OpenAI API)
  • Intent classification and entity extraction
  • Creating conversational flows and response generation
  • Handling multi-turn conversations and context retention
  • Building a basic AI chatbot with Python
  • Integrating Large Language Models (LLMs) like GPT, Claude, and Gemini for smarter responses
  • Prompt engineering for LLM-based chatbots
  • Memory and personalization in Conversational AI
  • Retrieval-Augmented Generation (RAG) for Knowledge-Driven Chatbots
  • Implementing a Knowledge-Enhanced Chatbot
  • Introduction to speech recognition and Text-to-Speech (TTS)
  • Building a voice assistant using OpenAI whisper and Google Speech API
  • Integrating vision models (image and video-based chatbots)
  • Creating a voice-enabled virtual assistant
  • Deploying on cloud platforms (AWS Lex, Azure Bot Service, Google Dialogflow)
  • API integration with websites, mobile apps, and messaging platforms (WhatsApp, Telegram, Slack)
  • Performance optimization, monitoring, and security best practices
  • Deploying a chatbot in a real-world scenario

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FAQs

AI-powered chatbots are intelligent digital assistants that use artificial intelligence to understand and respond to human language naturally. They can handle customer inquiries, provide information, and perform tasks automatically without human intervention. Unlike basic rule-based chatbots, AI chatbots learn from interactions to continuously improve their responses and can understand context, nuance, and varying ways people phrase questions.
Virtual assistants are sophisticated AI systems that can perform a wide range of tasks through natural conversation, often acting as personal or administrative helpers. Unlike AI-powered chatbots, which typically focus on specific domains and predetermined interactions, virtual assistants offer broader functionality—they can manage calendars, set reminders, control smart devices, place orders, and learn user preferences over time. Virtual assistants generally provide more personalized experiences with contextual awareness across multiple conversations and platforms, whereas chatbots excel at efficiently handling specific, well-defined customer service scenarios within a single interaction.
The Building AI-powered Chatbots and Virtual Assistants course is designed for developers and AI professionals keen to build chatbots and virtual assistants for their organizations.
For this course, participants need to have a basic understanding of Python programming, familiarity with APIs and web services, and knowledge of Natural Language Programming concepts. Participants would also benefit from having experience with cloud platforms like Microsoft Azure, Amazon AWS, and Google Cloud Platform, however, this is not mandatory.