Introduction to Data Science (Public Policy)

О курсе

Turn digital data into meaningful insights with practical data science skills for public policy and social research. This course is designed for learners interested in public policy, social sciences, data analysis, research, and related fields who want to use Python and digital data to better understand real-world social issues. Learn the foundations of Python programming using Jupyter Notebook, including variables, data types, expressions, strings, conditionals, functions, lists, loops, and user input. Build confidence in writing and applying Python code to work with different types of digital data. Develop practical data analysis skills using Pandas, including importing CSV files, working with DataFrames, slicing datasets, calculating summary statistics, and analyzing real-world data. Learn to communicate insights through visualizations such as histograms, scatter plots, and bar charts. Explore text analysis and natural language processing using Python and NLTK. Learn how to tokenize and preprocess text, remove stop words, calculate word frequencies, perform Part-of-Speech tagging, conduct concordance analysis, and explore sentiment analysis. Go further by learning how to access data through Web APIs, create GET requests, parse JSON responses, build DataFrames from web data, and ethically scrape websites using BeautifulSoup. Gain hands-on experience applying computational methods to digital data and interpreting results to uncover insights about the social world. Enroll now to build practical Python, data analysis, visualization, NLP, and web data skills.

Навыки, которые вы освоите

Учитесь у экспертов

Sushant Kumar

Преподаватель курса