Your Top AI Questions Answered: AI Literacy for Everyone
44mGeneral2025-08-01
Authors
Marily Nika
AI Product Lead at Google, Executive Fellow at Harvard Business School
Course details
Explore the dynamic landscape of artificial intelligence and gain a strong understanding of both traditional and generative AI. Join instructor and generative AI expert Dr. Marily Nika as she offers an overview of the history of AI—from its conceptual inception to its current state. Discover the differences between traditional AI and generative AI, before diving into constructing effective prompts to enhance the usefulness of AI responses in various contexts. Learn about key technologies including transformer architecture, large language models (LLMs), and real-world applications like chatbots, translators, and agents. Along the way, Marily covers the importance of data quality, expert human contribution, and the back-end technology, such as GPUs, all of which are essential for training AI systems. This course is an ideal fit for tech enthusiasts, data scientists, professionals in tech-driven fields, and anyone looking to leverage AI for personal or professional growth.
Learning objectives
Compare traditional AI systems with generative AI models and describe their unique capabilities and applications.
Explain what a GPU is and how it leads to overall cost for running AI models.
Outline the key components of an effective generative AI prompt.
Identify the ethical considerations in AI development and explain strategies for practicing responsible AI.
Summarize the impact of data quality on AI outcomes.
Learning objectives
Compare traditional AI systems with generative AI models and describe their unique capabilities and applications.
Explain what a GPU is and how it leads to overall cost for running AI models.
Outline the key components of an effective generative AI prompt.
Identify the ethical considerations in AI development and explain strategies for practicing responsible AI.
Summarize the impact of data quality on AI outcomes.
Skills covered
AI Literacy for EveryoneAI Foundations and LiteracyArtificial Intelligence (AI)One-Off
Concepts
Introduction
- Answers to your most common AI questions
Understanding AI and GenAI's Unique Capabilities
- A quick history of AI
- What's the difference between traditional AI and generative AI
- Why does AI cost so much to create
Generative AI Technical Concepts
- What's an LLM
- What does it mean to train an AI model
- What is a GPU
- What is an AI agent and how can it help you
Working with Generative AI Tools
- What makes an effective prompt
- What is Chain of Thought prompting
Data and Quality Considerations
- Why does quality matter in AI
- How can we ensure data integrity in AI
- How does data quality impact AI outcomes
Ethics and Compliance
- What are the ethical considerations in AI
- How can we practice responsible AI
- What are the regulations and compliance requirements for AI
- Could we have coverage of the environmental impact of AI when we shouldn't use it to avoid overuse wasting computing power