Knowledge Discovery Process Models: From Traditional to Agile Modeling

Knowledge discovery is the process of discovering useful knowledge from a collection of data. In this course, we will learn about various algorithms that are used to derive knowledge and perform classification and prediction.

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Knowledge Discovery Process Models: From Traditional to Agile Modeling
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Includes
  • 47 hands-on practice exercises
  • 6 Assessment exercises
  • 201 knowledge based questions
  • Lifetime access
About the Course
Knowledge Discovery Process Models: From Traditional to Agile Modeling

Knowledge discovery is the process of discovering useful knowledge from a collection of data. In this course, we will learn about various algorithms that are used to derive knowledge and perform classification and prediction.

Course Objectives

Upon successful completion of the course, the learner will be able to

  • Master the various concepts in Knowledge Discovery Models.

  • Learn how Knowledge Discovery Models plays an important role in AI and ML algorithms.

Course Content
Time Series Analysis

In this topic, you will learn about how to perform trend analysis using a statistical technique called Time Series Analysis.

  • 3 Hrs 15 Mins
  • 32 Problems
Sequence Discovery

In this topic, you will learn about finding statistically relevant patterns between data examples using Sequence Discovery.

  • 3 Hrs 15 Mins
  • 33 Problems
Summarization

In this topic, you will learn about deriving information from the data using various summarization techniques.

  • 2 Hrs 15 Mins
  • 31 Problems
Association Rules

In this topic, you will learn about analyzing data for patterns, or co-occurrence, in a database using Association Rule.

  • 3 Hrs
  • 28 Problems
Classification

In this topic, you will learn about various classification algorithms and their implementations.

  • 3 Hrs
  • 56 Problems
Clustering

In this topic, you will learn about various clustering algorithms that group set of objects in such a way that objects in the same group are more similar to each other.

  • 3 Hrs 15 Mins
  • 34 Problems
Regression,Prediction

In this topic, you will learn about forming regression line for the given data and Predicting the outcome for a given input using the previously formed regression relation

  • 4 Hrs
  • 40 Problems
You will Learn through our Scientifically Designed & Proven 5 Step Practice Oriented Learning Process
iLearn
In this session, you will find video lectures and other resources to learn the concepts.
iDesign
In this session, you will start designing and creating your own programs.
iExplore
In this session, you will find interesting set of activities which will make you explore more on the specific topic.
iAssess
In this session, you will have activities to self assess your knowledge and skills on the specific topic.
iAnalyse
In this session, you will find varieties of exercises to improve your code analysis, testing and debugging skills.
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Harihara Budra P, XII std

Harihara Budra P, XII std
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