Big Data and Artificial Intelligence Fundamentals

Organizations today are flooded with information, but the real value lies in knowing how to process and interpret that data to solve complex problems. This course provides a foundational understanding of the relationship between Big Data, Data Science, and Artificial Intelligence, preparing you to navigate the modern data landscape. You will gain a clear perspective on how data-driven decisions are made and the tools required to turn raw information into actionable insights. Through written explanations and code examples, you will explore the lifecycle of a data project and the ethical considerations of modern AI. What you'll learn: - Understand the core principles of Big Data and why it is a critical asset for modern organizations - Identify the roles of Data Science, Machine Learning, and Artificial Intelligence within a project ecosystem - Learn to distinguish between high-quality data and common data pitfalls that lead to incorrect conclusions - Explore the typical lifecycle of a data science project from initial problem definition to deployment - Practice using modern Python libraries and tools for data manipulation and analysis - Apply basic prompt engineering concepts and understand how large language models fit into current workflows The course begins with essential terminology and the historical context of data growth before moving into the practical application of Python for data processing. You will explore the daily workflows of data professionals and the evolving role of AI in various industries. This course is designed for absolute beginners who want to understand the data landscape. No prior experience in programming or data analysis is required. Start building your foundation in the world of data and AI today.