The Data Science Method

About this Course

Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge! Despite and influx in computing power and access to data over the last couple of decades, our ability to use data within the decision-making process is either lost or not maximized all too often. We do not have a strong grasp of the questions asked and how to apply the data correctly to resolve the issues at hand. The purpose of this course is to share the methods, models and practices that can be applied within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address business and real-world challenges. You will learn how to identify a problem, collect and analyze data, build a model, and understand the feedback after model deployment. Advancing your ability to manage, decipher and analyze new and big data is vital to working in data science. By the end of this course, you will have a better understanding of the various stages and requirements of the data science method and be able to apply it to your own work.

Created by: IBM

Level: Introductory


Related Online Courses

Los contenidos de este curso se han pensado para permitir que los usuarios de Tableau mejoren a un nivel intermedio las propias capacidades en el empleo de la herramienta. En los precedentes... more
Bayesian Statistics is a captivating field and is used most prominently in data sciences. In this course we will learn about the foundation of Bayesian concepts, how it differs from Classical... more
Every modern organization is a digital organization or will rapidly become digital. Artificial intelligence, Google/Amazon/Facebook/Uber, and big data have dramatically raised customer expectations... more
Structured Query Language (SQL) is a standardized programming language used to manage relational databases and perform various operations on their data. This is the first course of a two-part... more
Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL