What Is Email Marketing?
November 5, 2024
Article · 10 min read
This course is part of Data Science Fundamentals Specialization
Instructor: Julie Pai
9,979 already enrolled
Included with
(147 reviews)
(147 reviews)
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)
Add to your LinkedIn profile
2 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
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.
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.
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.
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.
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.
1 video2 readings1 assignment1 discussion prompt
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Since 1965, the University of California, Irvine has combined the strengths of a major research university with the bounty of an incomparable Southern California location. UC Irvine’s unyielding commitment to rigorous academics, cutting-edge research, and leadership and character development makes the campus a driving force for innovation and discovery that serves our local, national and global communities in many ways.
Coursera Instructor Network
Course
University at Buffalo
Course
Fundação Instituto de Administração
Course
Johns Hopkins University
Specialization
147 reviews
57.82%
19.72%
12.24%
5.44%
4.76%
Showing 3 of 147
Reviewed on May 20, 2021
It is informative and gives me overview about data science and the future
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.
Reviewed on Sep 22, 2022
I learnt about CRISP DM process, Data Science tools, Decision Trees in this course.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
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:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.