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Mastering the Basics of Conversational AI
Embark on a journey into the world of artificial intelligence with our introductory course, “Understanding AI.” Designed for beginners and intermediate learners, this course provides a comprehensive overview of the fundamental concepts of AI, focusing on Conversational AI technologies like LLMs, NLU, and RAG. Whether you’re a developer, a product manager, or simply an AI enthusiast, this course will equip you with the knowledge needed to understand and discuss AI technologies confidently.
What You Will Learn:
Core AI Concepts: Understand what AI is, its key components, and how it’s evolved over time.
LLMs in Conversational AI: Learn about Large Language Models and their role in enhancing conversational agents.
NLU and NLP: Dive into Natural Language Understanding and Processing—key technologies behind AI’s ability to interpret human language.
Knowledge Bases and RAG: Explore how AI systems utilize knowledge bases and Retrieval-Augmented Generation to improve response accuracy.
AI Ethics and Bias: Gain insight into the ethical considerations and potential biases involved in AI development.
Course Content:
Is it for me?
Aspiring AI Professionals: Ideal for those starting their journey into AI and looking for a structured learning path.
Developers and Product Managers: Perfect for tech professionals who wish to understand AI applications in software development and product design.
AI Enthusiasts: Suitable for anyone curious about how AI technologies work and their impact on various industries.
Join us in “Understanding AI” to build a solid foundation in Artificial Intelligence, preparing you to engage with and contribute to discussions on one of today’s most dynamic and impactful fields of technology.
Getting Started
Below you can select any lesson and jump right in.
Lesson 1: Introduction to AI and Conversational Agents
Basics of Conversational Agents: Understand the core functions of chatbots and virtual assistants and their applications in various industries.
Foundational Technologies: Dive into the critical technologies that power conversational agents, including the workings of NLP, NLU, and the transformative role of LLMs.
Integration of LLMs: Explore how conversational agents use Retrieval-Augmented Generation (RAG) for pulling contextually relevant information during interactions.
Advanced Techniques: Learn about the strategic implementation of prompt design, engineering, and the fine-tuning of LLMs to refine interactions and enhance user experience.
Lesson 2: Deep Dive into LLMs
The Core Functions of LLMs: How these models generate text and interpret language.
Advanced Implementation Strategies: Including prompt engineering and the use of RAG for dynamic information retrieval.
Practical Applications: How these technologies are applied in real-world scenarios to create more intelligent and responsive AI agents.
Lesson 3: Overcoming LLM Challenges & Limitations
The Nature of Hallucinations and Inaccuracies: Learn why LLMs, despite their sophistication, can generate misleading or incorrect responses, and how this ties back to their design and training data.
Bias Unpacked: Dive into the mechanics of bias within AI systems. We’ll discuss what creates bias, how it affects the outputs of LLMs, and the broader implications for technology and society.
Practical Solutions and Strategies: Explore actionable techniques such as prompt tuning, knowledge base optimization, and fine-tuning strategies designed to refine the performance of LLMs and ensure they are not only effective but also equitable and ethical in their operations.
Lesson 4: AI Ethics
Ethical Impacts of AI
Impact on Businesses, Jobs, Culture, and our Democratic Institutions
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