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Data Mining and Knowledge Discovery

4.9 Filled star Filled star Filled star Filled star Half star
Based on 7 ratings
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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.

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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

Syllabus

Association
Clustering
Classification
Data Warehouse
Read more

Traffic lights

Read about what's good
what should give you pause
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

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Reviews summary

Data mining: strong theory, limited practice

According to students, this course offers a strong theoretical foundation in data mining and knowledge discovery. Many praise the clear and well-structured lectures and the instructor's ability to explain complex topics like classification, clustering, and data warehousing. It's often recommended for those seeking a solid conceptual understanding. However, a significant number of students highlight a limited focus on practical application and the use of potentially outdated tools, suggesting a need for more hands-on projects and coding exercises. Some also note that the course occasionally assumes prior knowledge in related fields, and coverage of certain topics, like data streams, could be more in-depth.
Lectures are well-explained and logically organized.
"The lectures were clear and well-structured, covering classification and clustering effectively."
"An excellent introduction... the instructor explains complex topics very well."
"The structure of the modules was logical, and I particularly enjoyed the section on frequent pattern mining."
"The lectures were engaging and the quizzes helped reinforce learning."
Provides robust conceptual understanding of data mining.
"This course provided a solid theoretical foundation in data mining concepts."
"It's more academic than purely practical, which suited my learning style. I would recommend it if you want a strong theoretical base."
"I gained a solid understanding of data warehousing techniques and beyond."
"Absolutely loved this course! It's a comprehensive guide to data mining and knowledge discovery."
"This fantastic course helped me build a conceptual understanding of data mining."
Some modules felt rushed; may assume prior stats/programming.
"Some parts, particularly on data streams and web databases, felt rushed or less developed."
"The course provides a broad overview, but it felt like it assumes too much prior knowledge in statistics and programming for a general audience."
"I had to supplement with external resources quite a bit."
"The content quality varied across modules."
Course is theory-heavy, lacks sufficient hands-on experience.
"However, I felt the hands-on examples were a bit limited and the tools used felt slightly outdated for current industry standards."
"More practical projects would really enhance the learning experience."
"I was disappointed with the lack of real-world application. The course is heavy on theory and mathematical formulas but light on how to actually implement these methods."
"The course needs more coding exercises and contemporary tools."

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
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'
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
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

Career center

Learners who complete Data Mining and Knowledge Discovery will develop knowledge and skills that may be useful to these careers:
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.
See salaries and explore the career path for Data Analyst
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.
See salaries and explore the career path for Data Scientist
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.
See salaries and explore the career path for Data Mining Consultant
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.
See salaries and explore the career path for Machine Learning Engineer
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.
See salaries and explore the career path for Data Warehouse Architect
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.
See salaries and explore the career path for Business Analyst
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.
See salaries and explore the career path for Market Researcher
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.
See salaries and explore the career path for Actuary
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.
See salaries and explore the career path for Risk Manager
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.
See salaries and explore the career path for Forensic Accountant
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.
See salaries and explore the career path for Financial Analyst
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.
See salaries and explore the career path for Auditor
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.
See salaries and explore the career path for Database Administrator
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.
See salaries and explore the career path for Web Developer
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.
See salaries and explore the career path for Software Engineer

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.
Data Mining
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.
Data Mining: Concepts and Techniques (The Morgan...
Kindle Edition
$$$
Data Mining: Concepts and Techniques (The Morgan...
Hardcover
$$$
Data Mining: Concepts and Techniques, Second...
Hardcover
$$
Data Mining: Know It All
Hardcover
$$$
Cover image
The Elements of Statistical Learning
Save
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.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Machine Learning
Save
Provides a broad introduction to machine learning, covering both the theoretical foundations and the practical applications of machine learning algorithms. It valuable resource for both students and practitioners who want to learn about machine learning.
Machine Learning (McGraw-Hill International...
Paperback
$$$
Machine Learning: An Artificial Intelligence...
Hardcover
$$$
Recent Advances in Robot Learning: Machine Learning...
Paperback
$$$$
Machine Learning: A Guide to Current Research (The...
Mass Market Paperback
$$$$
Machine Learning: An Artificial Intelligence...
Kindle Edition
$$$
Cover image
Data Mining and Machine Learning
Save
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.
Data Mining and Machine Learning: Fundamental...
Hardcover
$$$
Data Mining and Machine Learning: Fundamental...
Kindle Edition
$$$
Cover image
Data Mining Methods for Knowledge Discovery
Save
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.
Data Mining Methods for Knowledge Discovery
Paperback
Check
Data Mining Methods for Knowledge Discovery
Kindle Edition
Check
Cover image
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.
Data Mining: Practical Machine Learning Tools and...
Paperback
$$$
DATA MINING, 4TH EDITION
Paperback
$$
Data Mining: Practical Machine Learning Tools and...
Kindle Edition
$$
Cover image
Data Mining Techniques
Save
Provides a practical introduction to data mining, covering both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Data Mining Techniques: For Marketing, Sales, and...
Paperback
$$
Data Mining Techniques: For Marketing, Sales, and...
Paperback
$$
Data Mining Techniques: For Marketing, Sales, and...
Paperback
$$
Data Mining Techniques: For Marketing, Sales, and...
Audio CD
$$
Data Mining Techniques: For Marketing, Sales, and...
Kindle Edition
$$
Cover image
Data Mining with R
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.
Data Mining with R: Learning with Case Studies,...
Hardcover
$$$
Data Mining with R: Learning with Case Studies...
Hardcover
$$
Data Mining with R: Learning with Case Studies,...
Kindle Edition
$$
Cover image
Machine Learning for Business Analytics
Save
Provides a practical introduction to data mining for business intelligence. It covers both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Machine Learning for Business Analytics: Concepts,...
Hardcover
$$$$
Machine Learning for Business Analytics: Concepts,...
Kindle Edition
$$$$
Cover image
Data Analytics & Visualization All-in-One For...
Save
Provides a practical introduction to data mining for beginners. It covers both the theoretical foundations and the practical applications of data mining algorithms. It valuable resource for both students and practitioners who want to learn about data mining.
Data Analytics & Visualization All-in-One For...
Paperback
$$
Data Analytics & Visualization All-in-One For...
Kindle Edition
$$

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Course image
Rating
4.9 Filled star Filled star Filled star Filled star Half star
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
Language
English
Transcript
English
This course belongs to a collection called Big Data Technology. It's comprised of five courses:
  1. Big Data Technology Capstone Project
  2. Big Data Computing with Spark
  3. Foundations of Data Analytics
  4. Data Mining and Knowledge Discovery (viewing)
  5. Mathematical Methods for Data Analysis
Traffic lights
Read about what's good
what should give you pause
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
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