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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.
This Course Includes
edx
4.3 (8 reviews )
7 weeks at 3-7 hours per week
english
Online - Self Paced
course
IBM
About IBM: The Data Science Method
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.
What You Will Learn?
- Explain why a methodology for approaching data science problems is needed.
- List the major steps involved in tackling a data science problem.
- Determine appropriate data sources for your data science analysis methodology.
- Describe the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.
- Demonstrate your understanding of the data science methodology by applying it to a problem that you define.