Machine Learning & AI Introduction (RXM402) Course Overview

Course Prerequisites

Target Audience for Machine Learning & AI Introduction (RXM402)

Machine Learning & AI Introduction (RXM402) offers foundational knowledge on AI and machine learning, catering to individuals eager to enhance their skills and career prospects in tech-driven industries.

• Data Analysts
• Software Developers
• IT Professionals
• Business Analysts
• Managers in Tech Companies
• Students in Computer Science/IT
• Technology Enthusiasts
• Researchers and Academics
• Project Managers
• Data Scientists (Aspiring)
• Marketing Professionals (looking to leverage data)
• Product Managers

Learning Objectives - What you will Learn in this Machine Learning & AI Introduction (RXM402)?

Introduction:
The Machine Learning & AI Introduction (RXM402) course equips students with foundational knowledge in AI and machine learning concepts, enabling them to understand their applications and implications in various fields.

Learning Objectives and Outcomes:

• Understand the fundamental concepts of machine learning and artificial intelligence.
• Explore different types of learning: supervised, unsupervised, and reinforcement learning.
• Gain insights into key algorithms and their applications.
• Analyze datasets and identify patterns using machine learning techniques.
• Discuss ethical considerations and biases in AI models.
• Implement basic machine learning models using popular frameworks.
• Evaluate the performance of machine learning models.
• Learn about real-world applications of AI across various industries.
• Develop problem-solving skills through practical exercises and projects.
• Familiarize with tools and resources for ongoing learning in AI and machine learning.