Data Science is a multidisciplinary field blending data inference, algorithm development and technology, that stands at the forefront of transforming raw data into meaningful insights and innovations. At its core, data science involves extracting knowledge and insights from structured and unstructured data, using methods rooted in statistics, machine learning, and data analysis. This field is pivotal in today's information age, driving decision-making in industries ranging from healthcare to finance, and influencing societal advancements at an unprecedented scale. This course emphasizes the dual importance of quantitative analysis and qualitative interpretation to understand and leverage critical data. Beginning with Python programming fundamentals - a cornerstone in the data science toolkit - the curriculum advances through vital concepts such as data structures, manipulation, and exploratory data analysis (EDA). A special focus on Natural Language Processing (NLP) underscores the interdisciplinary nature of data science, integrating computational methods with linguistic insights. The course intertwines theoretical understanding with practical application, ensuring students not only learn the mechanics of data science, but also develop a critical, data-driven mindset. From engaging in hands-on projects to delving into real-world datasets, students will acquire the skills to convert data into compelling stories and actionable intelligence.