Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
Offered By


About this Course
Learner Career Outcomes
30%
32%
10%
Learner Career Outcomes
30%
32%
10%
Offered by

IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Syllabus - What you will learn from this course
From Problem to Approach and From Requirements to Collection
In this module, you will learn about why we are interested in data science, what a methodology is, and why data scientists need a methodology. You will also learn about the data science methodology and its flowchart. You will learn about the first two stages of the data science methodology, namely Business Understanding and Analytic Approach. Finally, through a lab session, you will also obtain how to complete the Business Understanding and the Analytic Approach stages and the Data Requirements and Data Collection stages pertaining to any data science problem.
From Understanding to Preparation and From Modeling to Evaluation
In this module, you will learn what it means to understand data, and prepare or clean data. You will also learn about the purpose of data modeling and some characteristics of the modeling process. Finally, through a lab session, you will learn how to complete the Data Understanding and the Data Preparation stages, as well as the Modeling and the Model Evaluation stages pertaining to any data science problem.
From Deployment to Feedback
In this module, you will learn about what happens when a model is deployed and why model feedback is important. Also, by completing a peer-reviewed assignment, you will demonstrate your understanding of the data science methodology by applying it to a problem that you define.
Reviews
TOP REVIEWS FROM DATA SCIENCE METHODOLOGY
This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)
Very informative step-by-step guide of how to create a data science project. Course presents concepts in an engaging way and the quizzes and assignments helped in understanding the overall material.
This is my favourite in the series, the 10 questions to be answered were mind opening. The repetition after every video makes easier for important points to stick to the brain. Very good indeed...
It just totally rebuilds my mind in thinking about how I should approach solving problems. I feel that I'm learning strong framework for an evidence-based logical approach. Just like a consultant.
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