Loading

€11.99 €9.99

Special offer - Alison T-shirts available on discount until 31st July!

Pre-Order Now!
Free Online Courses, Classes and Tutorials

Data Analytics - Mining and Analysis of Big Data

Join 4,678 other students
Data Analytics - Mining and Analysis of Big Data
  • Free Course

  • NPTEL

  • 2-3 Hours

  • Assessment

  • Certification

  • 50 Pts

  • Description
  • Outcome
  • Certification
  • In this free data analysis course Data Analytics - Mining and Analysis of Big Data you will be introduced to the concept of big data and to a number of techniques that are used to analyse and interpret big data.

    The course begins by introducing you to big data and lists the four V’s of big data. You will learn about associative rule mining, and about when association can be applied and the patterns that arise in mining.

    Next, you will learn about clustering analysis. You will examine the difference between clustering and classification and the different types of clustering. You will also learn about K-means clustering and K-meloids.

    Finally, you will learn about online and active learning. You will learn about experimentation and the difference between an online and offline context of creating data. You will be introduced to the n-arm bandit problem and how to find solutions for the multi-arm bandit problem.

    This free online course will be of great interest to professionals involved in data science and data analysis and any learner who wants to learn more about analysing big data using mining and clustering techniques.

  • Having completed this course you will be able to:
    - Define association rule mining.
    - Explain mining frequent patterns and rules.
    - List when association rules can be applied.
    - Define the apriori algorithm.
    - List the four V’s of big data.
    - Explain why social media data can be hard to disambiguate .
    - Distinguish between clustering and classification.
    - Explain why clustering is used.
    - List the different types of clustering.
    - Define K-Means clustering.
    - Explain k-meloids.
    - Distinguish between online and offline context of creating data.
    - Define what stochastic multi-choice problems are.
    - Explain the n-arm bandit problem.
    - Describe some solutions for the multi-arm bandit problem.

  • All Alison courses are free to study. To successfully complete a course you must score 80% or higher in each course assessments. Upon successful completion of a course, you can choose to make your achievement formal by purchasing an official Alison Diploma, Certificate or PDF.

    Having an official Alison document is a great way to celebrate and share your success. It is:

    • Ideal to include with CVs, job applications and portfolios
    • A way to show your ability to learn and achieve high results

Modules List( 5 )
Notification

You have received a new notification

Click here to view them all