Humanities research often involves managing and analyzing large amounts of text or digital data. Learning fundamental programming skills is essential for efficient analysis and organization in the digital age. This course provides a gentle, practical introduction to data manipulation using Python, enabling you to automate repetitive tasks and gain deeper insights from your source materials without needing a computer science background. What you'll learn: Understand core programming concepts, including variables, loops, and conditional logic in Python. Practice structuring research data using fundamental data types and handling text strings effectively. Apply basic data cleaning and filtering techniques using the powerful Pandas library. Configure clean and isolated project environments using modern virtual environment tools. Develop small scripts to automate common research tasks, such as file processing and data extraction. The course begins with foundational Python syntax and gradually progresses to practical data structures and data manipulation tools. We guide you through applying these concepts to real-world data handling scenarios common in academic research. This course is specifically designed for beginners, including humanities students, researchers, and anyone needing to acquire practical digital literacy skills. No prior programming experience is required. Start building essential data analysis skills for your academic and professional future today.
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