Introduction to Conversational and Generative AI

Program Overview

This comprehensive program provides an in-depth exploration of Conversational and Generative AI, covering key concepts such as speech-to-text, NLP, sentiment analysis, and chatbot development. Through interactive lectures, hands-on workshops, and a final project, participants gain practical skills and knowledge to pursue careers in this rapidly growing field. The program emphasizes ethical considerations and societal impact, ensuring responsible use of Conversational AI.

Program Outline

Outline:

• Module 1: History of Conversational AI
• Learn about the history and evolution of Conversational AI and its key milestones.
• Explore the applications and advancements of Conversational AI across various industries.
• Module 2: Speech-to-text
• Discover the fundamentals of speech recognition and explore the technology behind converting speech into text.
• Examine the challenges and advancements in speech recognition, including different accents and slang.
• Module 3: Natural Language Processing (NLP)
• Delve into the principles of NLP and explore its key techniques for understanding and manipulating human language.
• Learn about different NLP tasks such as tokenization, parsing, and sentiment analysis.
• Module 4: Sentiment Analysis
• Understand the concept of sentiment analysis and the techniques used to extract emotions and opinions from text and speech.
• Discover applications of sentiment analysis in various fields, including marketing, customer service, and social media analysis.
• Module 5: Natural Language Features
• Explore various linguistic features and how they can be extracted and used to represent text and speech.
• Learn about feature engineering techniques and their importance in NLP applications.
• Module 6: Intent Recognition
• Understand the process of identifying the underlying intention behind a user's utterance in natural language.
• Explore different intent recognition techniques and their applications in building chatbots and other conversational AI systems.
• Module 7: Natural Language Generation (NLG)
• Learn about the principles of NLG and techniques for generating human-like text and speech in response to user input.
• Explore applications of NLG in various areas, including chatbots, virtual assistants, and content creation.
• Module 8: Chatbots
• Discover the different types of chatbots and their functionalities, including rule-based, retrieval-based, and generative chatbots.
• Learn about chatbot development techniques and best practices for building effective conversational interfaces.
• Module 9: Large Language Models (LLMs)
• Explore the concept of LLMs and their capabilities, including generating text, translating languages, and writing different kinds of creative content.
• Discuss the ethical implications and societal impact of LLMs.
• Module 10: Conversational AI ethics
• Examine the ethical considerations related to the development and deployment of Conversational AI, including bias, privacy, and transparency.
• Explore ways to ensure responsible and ethical use of Conversational AI in various applications.

Assessment:

• Continuous assessment throughout the course through assignments, quizzes, and participation in class discussions.
• Final project involving the development of a simple Conversational AI application.

Teaching:

• Interactive lectures that combine theoretical concepts with practical examples and case studies.
• Hands-on workshops and labs where students can apply their learning to real-world tasks.
• Individual and group feedback from experienced instructors who are experts in Conversational AI.

Careers:

• Graduates of this course will be well-equipped for careers in the rapidly growing field of Conversational AI.
• Potential career paths include:
• Conversational AI developer
• Chatbot developer
• NLG engineer
• Conversational AI researcher
• NLP engineer
• Data scientist
• Machine learning engineer

Other:

• This course is ideal for anyone interested in learning about Conversational AI, including business professionals, technology enthusiasts, and students.
• No prior experience with Conversational AI is required, but a basic understanding of Python programming is necessary.