Enroll Course: https://www.coursera.org/learn/introduccion-ciencia-de-datos-aplicada
Are you curious about the world of data science but unsure where to start? Coursera’s ‘Introducción a la ciencia de datos aplicada’ (Introduction to Applied Data Science) is an excellent launching pad for anyone looking to understand the fundamentals of this rapidly growing field. This course, designed as a first immersion, promises to equip students with a solid understanding of what data science entails, the role of a data scientist, the essential tools they use, and the methodologies crucial for tackling data-driven projects.
The course is thoughtfully structured into four weekly modules, each building upon the previous one.
**Module 1: La ciencia de datos y los científicos de datos** kicks off with a comprehensive introduction. You’ll delve into the definition of data science, explore its applications across various disciplines, and learn about two key methodologies: ASUM-DM for project development and Design Thinking for identifying analytical opportunities. The module culminates with a practical case study, allowing you to immediately apply what you’ve learned.
**Module 2: Análisis exploratorio de datos** shifts the focus to practical data analysis. Here, you’ll get hands-on with essential tools, likely Jupyter Notebook as indicated by the syllabus, to uncover business insights. The module covers univariate statistics, including measures of central tendency, location, and variability, along with graphical representations to validate business hypotheses. Another case study, this time focused on the retail sector, provides practical experience, followed by applying these concepts to the Airbnb case study.
**Module 3: Modelos analíticos basados en estadística bivariada** takes your analytical skills a step further by exploring the relationships between variables. After understanding individual variables in Module 2, you’ll now tackle bivariate statistics. This includes studying correlation for quantitative variables and contingency tables with chi-square tests for categorical variables. Like the previous module, this section reinforces learning through a retail sector case study using Jupyter Notebook, and then applies these advanced concepts to the Airbnb case study.
**Module 4: Comparaciones entre grupos y validación de modelos estadísticos** concludes the course by emphasizing the importance of hypothesis testing and statistical significance. Through two selected case studies, you’ll gain a practical understanding of why validating hypotheses correctly is critical in data science projects. This module solidifies your grasp of statistical modeling and its validation.
Overall, ‘Introducción a la ciencia de datos aplicada’ is a well-rounded and accessible course for beginners. It strikes a good balance between theoretical concepts and practical application, utilizing relevant tools and case studies to make the learning process engaging and effective. If you’re looking to take your first steps into the exciting realm of data science, this course comes highly recommended.
Enroll Course: https://www.coursera.org/learn/introduccion-ciencia-de-datos-aplicada