Data Mining

NPTEL and Indian Institute of Technology, Kharagpur via YouTube

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COURSE OUTLINE: Data mining is the study of algorithms for finding patterns in large data sets. It is an integral part of modern industry, where data from its operations and customers are mined for gaining business insight. It is also important in modern scientific endeavors. Data mining is an interdisciplinary topic involving, databases, machine learning and algorithms. The course will cover the fundamentals of data mining. It will explain the basic algorithms like data preprocessing, association rules, classification, clustering, sequence mining and visualization. It will also explain implementations in open-source software. Finally, case studies on industrial problems will be demonstrated.

Syllabus

Lecture 1 Introduction, Knowledge Discovery Process.
Lecture 2 Data Preprocessing - I.
Lecture 3 Data Preprocessing - II.
Lecture 4 Association Rules.
Lecture 5 Apriori algorithm.
Lecture 6 : Rule generation.
Lecture 7 : Classification.
Lecture 8 : Decision Tree - I.
Lecture 9 : Decision Tree - II.
Lecture 10 : Decision Tree III.
Lecture 11 : Decision Tree IV.
Lecture 12 : Bayes Classifier I.
Lecture 13 : Bayes Classifier II.
Lecture 14 : Bayes Classifier III.
Lecture 15 : Bayes Classifier IV.
Lecture 16 : Bayes Classifier V.
Lecture 17 : K Nearest Neighbor I.
Lecture 18 : K Nearest Neighbor II.
Lecture 19 :.
Lecture 20.
Lecture 21.
Lecture 22 : Support Vector Machine I.
Lecture 23 : Support Vector Machine II.
Lecture 24 : Support Vector Machine III.
Lecture 25 : Support Vector Machine IV.
Lecture 26 : Support Vector Machine V.
Lecture 27: Kernel Machines.
Lecture 28: Artificial Neural Networks I.
Lecture 29:Artificial Neural Networks II.
Lecture 30: Artificial Neural Networks III.
Lecture 31: Artificial Neural Networks IV.
Lecture 32: Clustering I.
Lecture 33: Clustering II.
Lecture 34: Clustering III.
Lecture 35: Clustering IV.
Lecture 36: Clustering V.

Taught by

Data Mining - IITKGP

Reviews

4.4 rating, based on 42 Class Central reviews

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Shlok Banubakode @shlokbanubakode

I recently completed a course on Data Warehouse and Mining, and it was an incredibly insightful experience. The course provided a solid foundation in understanding the architecture and functioning of data warehouses, along with hands-on practice on…

I recently completed a course on Data Warehouse and Mining, and it was an incredibly insightful experience. The course provided a solid foundation in understanding the architecture and functioning of data warehouses, along with hands-on practice on data mining techniques.

The lectures were well-structured, covering key concepts like ETL processes, OLAP operations, dimensional modeling, and various data mining algorithms, including clustering, classification, and association rule mining. The real-world case studies and projects helped in applying theoretical knowledge to practical scenarios, which made the learning even more valuable.

One of the highlights of the course was the focus on tools like SQL, Tableau, and WEKA, which were used to visualize and mine data effectively. I also appreciated how the instructors emphasized the role of data preprocessing and cleaning, ensuring we had a deep understanding of how to handle large datasets in real business contexts.

Overall, this course has significantly enhanced my skills in building and managing data warehouses while leveraging data mining techniques for better decision-making. I would highly recommend it to anyone looking to break into the field of data analytics or business intelligence.
Yashaswini Pai

I recently completed this data mining course, and it was nothing short of transformative. The curriculum was well-structured, starting from foundational concepts and gradually progressing to advanced techniques like clustering, classification, and a…

I recently completed this data mining course, and it was nothing short of transformative. The curriculum was well-structured, starting from foundational concepts and gradually progressing to advanced techniques like clustering, classification, and association rule mining. What stood out most was the balance between theory and hands-on practice—every module included real-world datasets and guided projects that made abstract concepts immediately applicable.
The instructor’s explanations were clear, concise, and enriched with practical examples. Complex algorithms such as decision trees, k-means, and neural networks were broken down into digestible steps, making them accessible even to beginners.
By the end, I felt confident not only in understanding the mechanics of data mining but also in applying them to solve business problems and uncover actionable insights. This course is a must for anyone serious about data-driven decision-making—it equips you with both the knowledge and the confidence to excel.
Harsha Kattamanchi

I recently completed the Data Mining course found via Class Central, and it provided a solid foundation in extracting patterns from large datasets. The curriculum effectively balanced theoretical concepts—like clustering, association rules, and decision trees—with hands-on practical exercises. I particularly appreciated the focus on real-world applications, which made the complex mathematical models much easier to grasp. The instructor explained intricate algorithms with great clarity, ensuring that even beginners could follow along. However, I would have liked to see more advanced case studies toward the end. Overall, this course is an excellent resource for anyone looking to enter the field of data science.
Muhammad Bobby Nur Darmawan

The Data Mining course was extremely insightful and well-structured. It provided a strong understanding of key concepts like data preprocessing, classification, clustering, association rules, and predictive modeling. The hands-on exercises and real-world case studies made it easier to connect theory with practical applications. The instructor explained complex topics in a simple and engaging way, making the learning process enjoyable. This course enhanced my analytical and problem-solving skills, especially in handling large datasets. Overall, it was a valuable experience that strengthened my knowledge of data analytics and machine learning foundations. Highly recommended for anyone interested in data science
Dilleswara Raju Challa

It been very understandable and made easy to learn data mining .But if any assignments are provided it help the trainers to understand more deeply
Adarsh Nambiar @adarshnambiar

Great introductory course with good content and clear explanations, perfect for beginners in data mining.
Elvia Lissy Shaji

Good teaching style I gained a lot of experience and was to catch up easily. The curriculum was well-structured and covered key concepts such as data preprocessing, data cleaning, classification, clustering, association rule mining, and basic predictive analysis. Complex topics were explained in a simple and systematic manner, making the course suitable even for learners with limited prior exposure to data analytics. Practical examples and case-based explanations helped in understanding how data mining techniques are applied in real-world business and technological scenarios.
Ayush Gujar

The Data Mining course was extremely insightful and well-structured. It provided a strong understanding of key concepts like data preprocessing, classification, clustering, association rules, and predictive modeling. The hands-on exercises and real-world case studies made it easier to connect theory with practical applications. The instructor explained complex topics in a simple and engaging way, making the learning process enjoyable. This course enhanced my analytical and problem-solving skills, especially in handling large datasets. Overall, it was a valuable experience that strengthened my knowledge of data analytics and machine learning foundations. Highly recommended for anyone interested in data science.
Aditya Kumawat

This Data Mining course provides a strong foundation in essential techniques like classification, clustering, and association rule mining. It expertly balances theoretical concepts with practical application, using real-world datasets and popular tools (e.g., Python libraries). The instructor clearly explains complex algorithms and their trade-offs. While the pace can be challenging for absolute beginners, the content is highly relevant and immediately applicable to industry roles. Completing this course significantly boosts one's ability to extract meaningful insights and patterns from large datasets. Highly recommended for aspiring data scientists and analysts.
Aryan Varma

The NPTEL Data Mining course available on YouTube is an excellent resource for students and professionals interested in gaining a strong foundation in data mining concepts. Delivered by experienced IIT professors, the course covers key topics such a…

The NPTEL Data Mining course available on YouTube is an excellent resource for students and professionals interested in gaining a strong foundation in data mining concepts. Delivered by experienced IIT professors, the course covers key topics such as association rule mining, clustering, classification, decision trees, and data preprocessing in a clear and structured manner. The explanations are in-depth yet beginner-friendly, making complex concepts easy to understand. Visual aids, real-world examples, and algorithm demonstrations further enhance learning. Regular quizzes and assignments reinforce understanding and practical application. One of the best aspects is that it’s freely accessible on YouTube, making high-quality education available to all. Whether you're preparing for academic exams or aiming to apply data mining in real-world scenarios, this course provides great value. Overall, it’s a highly recommended course for anyone looking to build a career in data science, machine learning, or related fields.
Siddhant Kadu
1

All the topics are covered and explained excellently.This data mining course offers a great introduction to uncovering patterns and insights from large sets of data. It usually covers essential topics like classification, clustering, association rule mining, and anomaly detection. The course is generally engaging, with practical exercises and projects to help solidify learning. Whether you're a beginner or looking to sharpen your data skills, it's a valuable course for anyone interested in fields like data science, analytics, or machine learning.
Tejendra Kumar

Good course Very useful understanding of algorithms and clustering concepts very useful for the exam point of view and other competitive exams
Kamraan Mulani

The course is well-structured and provides a clear understanding of key data mining concepts. The instructor explains complex topics in a simple and engaging way. The examples and demonstrations make learning easier and more practical. Highly recommended for beginners and intermediate learners.
Rohit Gupta

Great free NPTEL YouTube course—clear lectures, solid theory & real-world examples. A strong intro to data mining
Durvesh

Great intro to data mining with practical examples, easy to follow and very informative. This NPTEL Data Mining course provides a strong foundation with clear explanations, practical examples, and real-world applications. Highly recommended!
Ritesh Pawar

Ideal for computer science, IT, and data science students or professionals who want to understand how to discover patterns in structured/unstructured data. Beginners with limited programming or statistics background may need extra preparation.
Francisco Ornil Dos Santos Júnior

A didática do professor foi excelente, conseguiu tornar o conteúdo complexo fácil de entender. Além disso, o professor demonstrou grande conhecimento prático e teórico, o que foi muito útil para mim.
Megha Yewale

I recently completed an online course on data mining, and it was an enriching experience. The course covered a wide range of topics, including classification, clustering, association rules, and predictive analytics, with a strong focus on practical…

I recently completed an online course on data mining, and it was an enriching experience. The course covered a wide range of topics, including classification, clustering, association rules, and predictive analytics, with a strong focus on practical applications. The instructors did a great job of explaining complex concepts in a clear and engaging manner, supplemented by hands-on exercises that reinforced learning. The use of real-world datasets made the assignments interesting and relevant.

However, some sections felt a bit rushed, and I would have appreciated more in-depth coverage of advanced algorithms. Also, the forums could be more active to facilitate peer learning. Overall, it's a solid course for beginners and intermediate learners looking to build a strong foundation in data mining.
Thamina Siddiky

It is helpful but very ordinary and boring types. Some dynamic key points should be added to make the lessons more understandable and catchy.
Shashwat Agarwal

Experience is very nice my skills will definitely grow through this course and the explanation of each lecture is too good