AI: Advanced Level

Are you curious about Artificial Intelligence (AI) and how it shapes the world? This course will introduce you to AI’s history, how it makes predictions, understands language and images, and learns using neural networks inspired by the human brain. You’ll also gain hands-on experience by building and testing a machine learning model. By the end, you’ll explore career opportunities in AI and discover how to take your first steps toward an AI-related profession.

• AI Data Processing & Prediction: The ability to explain how AI systems ingest and process data to generate predictions, encompassing concepts like feature engineering and model training.
• Natural Language Processing (NLP) Fundamentals: Practical understanding of how AI interprets and generates human language, enabling learners to identify applications like sentiment analysis or chatbots.
• Computer Vision Basics: The foundational knowledge of how AI "sees" and analyzes images, including concepts like object recognition and image classification.
• Machine Learning Model Development: The hands-on skill of conceptualizing, building, and evaluating a basic machine learning model.
• AI Career Pathway Identification: The capacity to recognize diverse career opportunities within the AI field and understand the skills required for various roles.

• Describe the history of AI development.
• Define structured, unstructured, and semi-structured data.
• Explain machine learning and how AI makes predictions from data.
• Understand how AI processes and generates human language.
• Explain how AI analyzes and creates images.
• Describe three methods AI uses to analyze data.
• Understand how neural networks help AI make predictions.
• Build and test an AI machine learning model using IBM Watson Studio.
• Identify ways AI systems can be designed to minimize bias.
• Recognize AI career opportunities, required skills, and resources for further learning.

• Comprehensive video lessons explaining fundamental AI concepts, including its historical development, data processing methodologies, and the mechanisms behind predictive modeling.
• Practical exercises demonstrating how AI understands human language (Natural Language Processing), analyzes images (Computer Vision), and leverages the power of neural networks.
• Step-by-step tutorials on building and testing a machine learning model, alongside guidance on identifying and navigating various AI career pathways.
• Certificate of completion upon successful course completion.