IBM: The Data Science Method
Learn about the methodology, practices and requirements behind data science to better understand how to problem solve with data and ensure data is relevant and properly manipulated to address a variety of real-world projects and business scenarios.
About this course
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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.
At a Glance:
Institution: IBM
Subject: Data Analysis & Statistics
Level: Introductory
Prerequisites:
None
Language: English
Video Transcripts: اَلْعَرَبِيَّةُ, Deutsch, English, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
Associated programs:
Professional Certificate in Data Science Foundations
Professional Certificate in IBM Data Science
Associated skills:Big Data, Data Science, Problem Solving
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