Advanced Conversational AI - 5 days

• Fundamental understanding of conversational AI and NLP models
• Experience with programming languages such as Python
• Basic knowledge of API integration and cloud services

Audience

• AI project managers
• Conversational AI developers
• Senior software engineers

Conversational AI refers to technologies that enable computers to simulate and engage in human-like conversations. These systems use advanced natural language processing (NLP), machine learning, and AI algorithms to understand, process, and respond to user inputs in a conversational manner.

This instructor-led, live training (online or onsite) is aimed at advanced-level Conversational AI developers who wish to gain practical experience with advanced skills necessary for developing, managing, and optimizing sophisticated conversational AI projects.

By the end of this training, participants will be able to:

• Master advanced design and development principles for conversational AI.
• Implement robust conversational flows with adaptive learning.
• Integrate AI models with various enterprise-level systems.
• Ensure effective project management and lifecycle strategies for AI-driven projects.
• Evaluate and refine conversation models based on user feedback and data analysis.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

• Conversational AI systems overview
• Evolution and components of modern conversational systems

Designing Advanced Conversational Flows

• Creating dynamic, context-aware dialogues
• Handling complex user intents and entities
• Building and testing adaptive conversation scenarios

Advanced NLP Techniques

• Pre-training and fine-tuning large language models
• Implementing named entity recognition (NER) and sentiment analysis

Multilingual and Cross-Language Processing

• Strategies for supporting multiple languages in one project
• Integrating and testing NER and sentiment analysis in a conversational bot

Backend Integration and Data Handling

• Connecting bots to enterprise-level data sources and APIs
• Using databases and cloud services for data storage and retrieval

Security and Compliance Considerations

• Ensuring data privacy, encryption, and secure user interactions
• Developing API connections and implementing data security protocols

Designing User-Centric Interfaces

• Enhancing user experience with voice and visual interactions

Adaptive Learning for Conversational AI

• Implementing user feedback loops and learning mechanisms to improve interactions
• Building adaptive learning features and evaluating their performance

Managing Conversational AI Projects

• Agile project management techniques specific to AI projects
• Defining KPIs and success metrics for conversational projects

Testing and Optimization Strategies

• Continuous testing frameworks for conversational AI
• Monitoring, analytics, and refining models post-deployment
• Conducting performance tests and optimization routines

Summary and Next Steps