We may earn an affiliate commission when you visit our partners.
Raymond Chi-Wing WONG
Data mining has recently emerged as a major field of research and applications. Aimed at extracting useful and interesting knowledge from large data repositories such as databases and the Web, data mining integrates techniques from the fields of database, statistics and AI.
Register for this course and see more details by visiting:
OpenCourser.com/course/bttshi/data
Three deals to help you save
We found three deals and offers that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Use code at checkout.
Valid until December 4
Save on Select Programs
Stay ahead in a competitive job market and save with these programs.
Take
30%
off
EDXCYBER24
Valid for a limited time only
Future-proof your career
Access O'Reilly books, live events, courses, and more. Save with an annual subscription.
Take
15%
off
What's inside
Learning objectives
- Apply the clustering techniques to find clusters within the data
- Use the classification techniques to conduct classification and predication
- Use the knowledge of frequest pattern mining to discover patterns from the data
- Learn data warehouse techniques for data analysis
- Apply the clustering techniques to find clusters within the data
- Use the classification techniques to conduct classification and predication
- Use the knowledge of frequest pattern mining to discover patterns from the data
- Learn data warehouse techniques for data analysis
Syllabus
Association
Clustering
Classification
Data Warehouse
Read more
Syllabus
Association
Clustering
Classification
Data Warehouse
Read more
Data Mining over Data Streams
Web Database
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Raymond Chi-Wing WONG, who is recognized for their work in Data Mining
Strengthens an existing foundation for intermediate learners in Data Mining
Covers unique perspectives are ideas that may add color to other topics and subjects in Data Mining
Explores Data Mining, which is highly relevant in an academic setting
Explores Data Mining, which is standard in industry
Develops clustering techniques, classification techniques, knowledge of frequent pattern mining, and Data Warehouse, which are core skills for Data Mining
Save this course
Save Data Mining and Knowledge Discovery to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data Mining and Knowledge Discovery with these
activities:
Connect with Data Mining Experts
Show steps
Seek guidance and support from professionals in the field.
Show steps
-
Attend industry events and meetups to connect with data mining professionals.
-
Reach out to professors or researchers at universities or research institutions.
-
Join online communities and forums for data mining enthusiasts.
Review 'Data Mining - Concepts and Techniques'
Show steps
Review the foundational concepts of data mining by exploring a comprehensive textbook.
View
Data Mining: Concepts and Techniques
on Amazon
Show steps
-
Read the introduction and first three chapters of the textbook.
-
Take notes on the key concepts and techniques described.
-
Summarize the main ideas in each chapter in your own words.
Solve Data Mining Practice Problems
Show steps
Sharpen your data mining skills by solving practice problems.
Show steps
-
Find a set of practice problems online or in a textbook.
-
Solve the problems using the techniques you have learned in the course.
-
Check your answers against the provided solutions.
Show all three activities
Connect with Data Mining Experts
Show steps
Seek guidance and support from professionals in the field.
Show steps
Show steps
Show steps
- Attend industry events and meetups to connect with data mining professionals.
- Reach out to professors or researchers at universities or research institutions.
- Join online communities and forums for data mining enthusiasts.
Review 'Data Mining - Concepts and Techniques'
Show steps
Review the foundational concepts of data mining by exploring a comprehensive textbook.
View
Data Mining: Concepts and Techniques
on Amazon
Show steps
Show steps
Show steps
- Read the introduction and first three chapters of the textbook.
- Take notes on the key concepts and techniques described.
- Summarize the main ideas in each chapter in your own words.
Solve Data Mining Practice Problems
Show steps
Sharpen your data mining skills by solving practice problems.
Show steps
Show steps
Show steps
- Find a set of practice problems online or in a textbook.
- Solve the problems using the techniques you have learned in the course.
- Check your answers against the provided solutions.
Show all three activities
Career center
Learners who complete Data Mining and Knowledge Discovery will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use data mining and knowledge discovery to build predictive models and identify patterns in data. This course provides a solid foundation for a career as a Data Scientist by teaching you the fundamental concepts of data mining, such as clustering, classification, and frequent pattern mining. You'll gain hands-on experience applying these techniques to real-world datasets, preparing you to extract valuable insights and drive informed decision-making.
Data Analyst
Data Analyst
Data Analysts apply their knowledge of data mining and knowledge discovery to extract meaningful insights from large datasets. This course can help prepare you for a rewarding career as a Data Analyst by providing you with a comprehensive foundation in data mining techniques, including clustering, classification, and frequent pattern mining. With these skills, you can contribute to data-driven decision-making and help organizations derive value from their data.
Data Mining Consultant
Data Mining Consultant
Data Mining Consultants help organizations implement data mining solutions. This course provides a comprehensive foundation in data mining and knowledge discovery, preparing you for a successful career as a Data Mining Consultant. You'll learn about clustering, classification, and frequent pattern mining techniques, as well as how to apply these techniques to real-world business problems.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve complex problems. This course provides a strong foundation in data mining and knowledge discovery, which are essential skills for Machine Learning Engineers. You'll learn about clustering, classification, and frequent pattern mining techniques, which can be used to train and evaluate machine learning models. This course will prepare you for a successful career as a Machine Learning Engineer by providing you with the skills to build and deploy effective machine learning solutions.
Business Analyst
Business Analyst
Business Analysts use data mining and knowledge discovery to identify business problems and opportunities. This course can help you develop the skills necessary to become a successful Business Analyst by providing you with a foundation in data mining techniques, including clustering, classification, and frequent pattern mining. You'll learn how to use these techniques to analyze data and extract insights that can be used to improve business processes and make informed decisions.
Actuary
Actuary
Actuaries use data mining and knowledge discovery to assess risk and uncertainty. This course provides a foundation in data mining techniques, such as clustering, classification, and frequent pattern mining, which are essential for Actuaries. You'll learn how to use these techniques to analyze data and extract insights that can be used to develop and price insurance products.
Risk Manager
Risk Manager
Risk Managers use data mining and knowledge discovery to identify and manage risks. This course provides a foundation in data mining techniques, such as clustering, classification, and frequent pattern mining, which are essential for Risk Managers. You'll learn how to use these techniques to analyze data and extract insights that can be used to develop and implement risk management strategies.
Market Researcher
Market Researcher
Market Researchers use data mining and knowledge discovery to understand consumer behavior and market trends. This course provides a strong foundation in data mining techniques, such as clustering, classification, and frequent pattern mining, which are essential for Market Researchers. You'll learn how to use these techniques to analyze market data and extract insights that can be used to develop effective marketing strategies.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and build data warehouses, which are large databases that store data from multiple sources. This course provides a foundation in data mining and knowledge discovery, which can be applied to data warehouse design and management tasks. You'll learn about clustering, classification, and frequent pattern mining techniques, which can be used to identify data patterns and trends, optimize data warehouse performance, and improve data quality.
Auditor
Auditor
Auditors use data mining and knowledge discovery to detect fraud and ensure compliance. This course provides a foundation in data mining techniques, such as clustering, classification, and frequent pattern mining, which are essential for Auditors. You'll learn how to use these techniques to analyze data and extract insights that can be used to identify suspicious transactions and ensure compliance with regulations.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases, ensuring that they are available, reliable, and secure. This course provides a solid foundation in data mining and knowledge discovery, which can be applied to database management tasks. You'll learn about clustering, classification, and frequent pattern mining techniques, which can be used to identify data patterns and trends, optimize database performance, and improve data security.
Financial Analyst
Financial Analyst
Financial Analysts use data mining and knowledge discovery to analyze financial data and make investment recommendations. This course provides a solid foundation in data mining techniques, such as clustering, classification, and frequent pattern mining, which are essential for Financial Analysts. You'll learn how to use these techniques to analyze financial data and extract insights that can be used to make informed investment decisions.
Forensic Accountant
Forensic Accountant
Forensic Accountants use data mining and knowledge discovery to investigate financial crimes. This course provides a foundation in data mining techniques, such as clustering, classification, and frequent pattern mining, which are essential for Forensic Accountants. You'll learn how to use these techniques to analyze financial data and extract insights that can be used to detect and investigate financial crimes.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course may be useful for Software Engineers who want to develop data mining or knowledge discovery applications. You'll learn about clustering, classification, and frequent pattern mining techniques, which can be used to build software applications that can extract insights from data.
Web Developer
Web Developer
Web Developers design and develop websites and web applications. This course may be useful for Web Developers who want to develop data mining or knowledge discovery applications for the web. You'll learn about clustering, classification, and frequent pattern mining techniques, which can be used to build web applications that can extract insights from data.
For more career information including salaries, visit:
OpenCourser.com/course/bttshi/data
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Mining and Knowledge Discovery.
Save
Comprehensive introduction to data mining, covering all the major concepts and techniques. It valuable reference for both beginners and experienced data miners. It can be used as a textbook in data mining courses.
Classic in the field of machine learning. It provides a comprehensive overview of the fundamental principles of statistical learning, including supervised and unsupervised learning algorithms. It valuable reference for both beginners and experienced machine learning practitioners.
Save
Provides a broad introduction to machine learning, covering both the theoretical foundations and the practical applications of machine learning algorithms. It valuable resource for both students and practitioners who want to learn about machine learning.
Comprehensive introduction to data mining and analysis, covering both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Provides a comprehensive overview of data mining and knowledge discovery, covering both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Save
Provides a practical introduction to data mining, covering both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Provides a practical introduction to data mining, covering both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Save
Provides a practical introduction to data mining using the R programming language. It covers both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Provides a practical introduction to data mining for business intelligence. It covers both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Provides a practical introduction to data mining for beginners. It covers both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/bttshi/data
Share
Similar courses
Here are nine courses similar to
Data Mining and Knowledge Discovery.
Evaluating a Data Mining Model
OpenCourser.com/course/wn697s/evaluating
Evaluating a Data Mining Model
Data Mining and the Analytics Workflow
OpenCourser.com/course/ofz017/data
Data Mining and the Analytics Workflow
More Data Mining with R
OpenCourser.com/course/v413lh/more
More Data Mining with R
More Data Mining with Weka
OpenCourser.com/course/uuvk8p/more
More Data Mining with Weka
Process Mining: Data science in Action
OpenCourser.com/course/gsv0zz/process
Process Mining: Data science in Action
Introduction to Process Mining with ProM
OpenCourser.com/course/ch4jr3/introduction
Introduction to Process Mining with ProM
Process Mining in Healthcare
OpenCourser.com/course/7w8czg/process
Process Mining in Healthcare
Data Mining Project
OpenCourser.com/course/dmgt9u/data
Data Mining Project
Data Science: A New Way of Thinking | 数据科学导论
OpenCourser.com/course/sc5odv/data
Data Science: A New Way of Thinking | 数据科学导论
Effort
6 to 10 hours per week for 8 weeks
Level
Intermediate
Via
edX
Institution
The Hong Kong University of Science and Technology
Instructor
Raymond Chi-Wing WONG
Session
April 2, 2024
- July 29, 2024
Language
English
Transcript
English
This course belongs to a
collection
called
Big Data Technology. It's comprised of five courses:
- Big Data Technology Capstone Project
- Big Data Computing with Spark
- Foundations of Data Analytics
- Data Mining and Knowledge Discovery (viewing)
- Mathematical Methods for Data Analysis
Good to know
Taught by Raymond Chi-Wing WONG, who is recognized for their work in Data Mining
Strengthens an existing foundation for intermediate learners in Data Mining
Covers unique perspectives are ideas that may add color to other topics and subjects in Data Mining
Explores Data Mining, which is highly relevant in an academic setting
Explores Data Mining, which is standard in industry
Develops clustering techniques, classification techniques, knowledge of frequent pattern mining, and Data Warehouse, which are core skills for Data Mining
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser