Data Science Essentials: Analysis, Statistics, and ML

About this course

This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the specialization. Gain a solid foundation in data science, covering statistics, data analysis, SQL, and machine learning. This specialization combines theory and practical skills, preparing you to analyze data, build models, and visualize insights confidently. The journey begins with an in-depth look into statistics and mathematics such as probability, regression, and hypothesis testing. You'll then master SQL to extract, transform, and manipulate data for real-world analytics. As you progress, you'll dive into Python's powerful libraries—NumPy, Pandas, and Matplotlib—laying the groundwork for data preprocessing, analysis, and visualization. Further, you’ll create interactive dashboards with Plotly Dash, then dive into machine learning to build and evaluate predictive models. This specialization is ideal for aspiring data scientists, analysts, and developers aiming to transition into data-centric roles. A basic understanding of Python and high-school-level math will be helpful. The specialization is at an intermediate level. By the end of the specialization, you will be able to perform statistical analysis, write SQL queries for data extraction, build interactive dashboards, and implement foundational machine learning models in Python.