Welcome to Introduction to Analytic Thinking, Data Science, and Data Mining. In this course, we will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. We will review the types of business problems data science can solve and discuss the application of the CRISP-DM process to data mining efforts. A brief overview of Descriptive, Predictive, and Prescriptive Analytics will be provided, and we will conclude the course with an exploratory activity to learn more about the tools and resources you might find in a data science toolkit.
Intro to Analytic Thinking, Data Science, and Data Mining
Intro to Analytic Thinking, Data Science, and Data Mining
This course is part of Data Science Fundamentals Specialization
Instructor: Julie Pai
9,727 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.2
(144 reviews)
Intermediate level
Some related experience required
7 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
The knowledge and skills needed to work in the data science profession
How data science is used to solve business problems
The benefits of using the cross-industry standard process for data mining (CRISP-DM)
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
2 assignments
Taught in English
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This course is part of the Data Science Fundamentals Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Welcome to Module 1, Data Science: The Field and Profession. In this module, we will review data science as a field and explore the concepts of small and big data. We will also survey the skills of successful data scientists and discuss the types of business problems data scientists might be asked to solve in the near future.
What's included
2 readings1 discussion prompt
Welcome to Module 2, Data Science in Business. In this module, we will take a closer look at the applications of data science in a business environment and discuss ethical considerations to keep in mind when working with data.
What's included
1 video2 readings1 assignment
Welcome to Module 3, Data Mining and an Overview of Data Analytics. In this module we will begin with an explanation of CRISP-DM, a cross-industry standard process for data mining. We will also provide an introduction to descriptive, predictive and prescriptive analytics.
What's included
2 readings1 discussion prompt
Welcome to Module 4, Solving Problems with Data Science. In this last module of the course we will explore some real-world applications of data science solutions and take a closer look at the types of tools and programs you might expect to see in a data science toolkit.
What's included
1 video2 readings1 assignment1 discussion prompt
Instructor
Instructor ratings
3.9 (42 ratings)5 Courses15,817 learners
Offered by
Recommended if you're interested in Data Analysis
Fractal Analytics
University of Colorado Boulder
Johns Hopkins University
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4.2
144 reviews
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Showing 3 of 144
RS
5
Reviewed on Jan 2, 2021
I consider this course a must for one's journey into Data Science. The videos are short and to the point to serve the purpose of the course.
CM
5
Reviewed on May 20, 2021
It is informative and gives me overview about data science and the future
RV
4
Reviewed on Sep 22, 2022
I learnt about CRISP DM process, Data Science tools, Decision Trees in this course.
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Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
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