Intro to Analytic Thinking, Data Science, and Data Mining
Master data science fundamentals, explore the CRISP-DM process, and learn ethical considerations in data mining. Perfect for aspiring data scientists.
Master data science fundamentals, explore the CRISP-DM process, and learn ethical considerations in data mining. Perfect for aspiring data scientists.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Fundamentals Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Understand the role and skills required in data science profession
Apply CRISP-DM methodology to solve business problems
Evaluate ethical considerations in data science
Identify appropriate analytics approaches for different scenarios
Explore data science tools and resources
Skills you'll gain
This course includes:
0.1 Hours PreRecorded video
2 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course introduces fundamental concepts of data science and data mining. Students learn about the field of data science, its applications in business, and ethical considerations. The curriculum covers the CRISP-DM methodology, types of analytics (Descriptive, Predictive, and Prescriptive), and practical applications through real-world case studies. The course emphasizes both theoretical understanding and practical implementation of data science concepts.
Data Science: The Field and Profession
Module 1 · 2 Hours to complete
Data Science in Business
Module 2 · 1 Hours to complete
Data Mining and an Overview of Data Analytics
Module 3 · 1 Hours to complete
Solving Problems with Data Science
Module 4 · 2 Hours to complete
Fee Structure
Instructor
Assistant Director of Technology Programs at UC Irvine
Julie Pai is an accomplished professional with over 10 years of experience in technology education programs. Her journey began in biology and clinical research, which sparked her interest in statistical analysis and data analysis. As the Assistant Director of Technology Programs at the University of California, Irvine, Julie collaborates with industry professionals to create, launch, and manage a variety of technology courses, including Data Science, Data Analytics, Cloud Computing, and Machine Learning. She is proficient in several programming languages and tools such as Tableau, SQL, MySQL, Python, Spark, Hive, and Scala. Julie's dedication to education is reflected in her efforts to develop engaging curricula that equip students with the skills needed to thrive in the technology sector. Through her work, she plays a vital role in bridging the gap between academia and industry, fostering a new generation of data-driven professionals.
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