This course is part of the Data Science Fundamentals Specialization

4.1
stars
104 ratings

Julie Pai

5,604 already enrolled

Offered By

Data Science Fundamentals SpecializationUniversity of California, Irvine

About this Course

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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.

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Coursera Labs

Includes hands on learning projects.

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Course 1 of 4 in the

Data Science Fundamentals Specialization

Intermediate Level

Approx. 7 hours to complete

English

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What you will 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 will gain

Environmental Data Analysis
Data Documentation
Geophysical Data
Data Mining

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 4 in the

Data Science Fundamentals Specialization

Intermediate Level

Approx. 7 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

3.73/5 (31 Ratings)

Julie Pai

Assistant Director of Technology Programs

Division of Continuing Education

12,542 Learners

8 Courses

Offered by

University of California, Irvine

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. UCI’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.

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Syllabus - What you will learn from this course

Week1

Week 1

2 hours to complete

Data Science: The Field and Profession

2 hours to complete

2 readings

Week2

Week 2

1 hour to complete

Data Science in Business

1 hour to complete

1 video (Total 3 min), 2 readings, 1 quiz

Week3

Week 3

2 hours to complete

Data Mining and an Overview of Data Analytics

2 hours to complete

2 readings

Week4

Week 4

3 hours to complete

Solving Problems with Data Science

3 hours to complete

1 video (Total 3 min), 2 readings, 1 quiz

Reviews

4.1

20 reviews

5 stars
53.33%
4 stars
21.90%
3 stars
13.33%
2 stars
5.71%
1 star
5.71%

TOP REVIEWS FROM INTRO TO ANALYTIC THINKING, DATA SCIENCE, AND DATA MINING

by MMMay 20, 2021

It is informative and gives me overview about data science and the future

by RSJan 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.

by CAFeb 11, 2021

The knowledge asked in the first quiz, hasn't been mentioned before in the reading.

by VSSep 22, 2022

I learnt about CRISP DM process, Data Science tools, Decision Trees in this course.

View all reviews

About the Data Science Fundamentals Specialization

This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques. The course also provides an overview of the most common techniques used in data science, including data analysis, statistical modeling, data engineering, manipulation of data at scale (big data), algorithms for data mining, data quality, remediation and consistency operations.

Frequently Asked Questions

When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
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.

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Intro to Analytic Thinking, Data Science, and Data Mining

About this Course

What you will learn

Skills you will gain