Nutrition and Dietetics

In today's age of advanced technology, we are fortunate enough to have easy access to an abundance of data through the internet and social media platforms. This data serves as a highly valuable resource for professionals in a multitude of fields, including business, science, and social science. To that end, this comprehensive course is designed to equip students with the skills necessary to effectively analyze complex data using Python programming. Throughout the course, students will learn to utilize powerful tools such as Numpy, Pandas for data analysis and Seaborn, Matplotlib for data visualization, all within the user-friendly Jupyter Notebook. In addition, the course will provide students with invaluable insights on how to collect, clean, prepare, and analyze time-series data. Furthermore, students will gain a deep understanding of how to apply linear regression models to predict unknown and future values, thereby enhancing their ability to make informed decisions based on data-driven insights.

Throughout this course, individuals will develop a comprehensive understanding of utilizing Python to analyze a diverse range of data. This will include gaining proficiency in data preparation for analysis, executing basic statistical analysis, creating impactful data visualizations, and forecasting future trends derived from data.