- COURSE
AI+ Everyone
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The AI+ Everyone course introduces Artificial Intelligence to a broad audience. It covers the basics of AI, including its history, myths vs. reality, and significance in everyday life. The course explores key AI technologies like machine learning and deep learning, with practical examples and an interactive workshop. Participants will examine AI applications through case studies such as smart speakers, self-driving cars, and healthcare innovations. It also delves into the AI project workflow, including problem definition, model training, and deployment. Ethical considerations, including bias, privacy, and responsible AI development, are discussed, along with the role of generative AI in creativity.
All students receive:
- One-Year Subscription (with all updates)
- High-Quality E-Book
- Al Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Exam Study Guide
- Proctored Exam with one Free Retake
Upcoming Class Dates and Times
All Sunset Learning courses are guaranteed to run
Course Outline and Details
Prerequisites
- Understand the basics of digital technologies and how they affect life
- Awareness of ethical principles and societal impact of technology
- Curiosity and openness to learning about new concepts and technologies
Target Audience
- Business Managers
Course Objectives
- Foundational understanding
- Practical Application
- Case study analysis
- Ethical Awareness
- Preparation for the future
Course Outline
Introduction To Artificial Intelligence (AI)
- What is Artificial Intelligence?
- A Brief History of AI
- Demystifying AI: Myths vs. Reality
- The Significance of AI in Everyday Life
AI Technologies
- Machine Learning: Basics and Beyond
- Deep Learning and Neural Networks
- AI Technologies in Action: Simplified Examples
- Interactive Workshop: Exploring AI
AI in Action: Applications and Case Studies
- Introduction to AI Applications
- Case Study 1: Smart Speakers
- Case Study 2: Self-Driving Cars
- Case Study 3: Healthcare Applications
The Workflow of AI Projects
- Introduction to AI Project Workflow
- Problem Definition and Data Preparation
- Model Selection, Training, and Validation
- Deployment and Integration
- Evaluation and Iteration
- Ethics And Social Implications Of AI
Introduction to AI Ethics and Social Implications
- Bias and Fairness in AI
- Privacy and Security in the Age of AI
- Responsible AI Development
- AI and Society: Looking Ahead