Course Description

Mastering Big Data

Global Edulink



Data Analytics – What’s the big idea?

“Big data” is a term for data sets that are so large or complex that traditional data processing application software is unable to adequately deal with them. Challenges include capture, storage, analysis, data curation, search, sharing, transfer, visualisation, querying, updating, and information privacy. The term big data often refers simply to the use of predictive analytics, user behaviour analytics, or certain other advanced data analytics methods that extract value from data, and rarely to a particular size of data set.

Multinational corporations such as LinkedIn or Pinterest are having to use complex data analytics to manage the sheer volume of big data that they possess. This has become a lucrative business for technical specialists who can effectively manage this data on their behalf, working either on a contract or permanent basis.

Course Curriculum

  1. Get the big ideas behind big data and analytics
  2. An approach for mastering the data deluge
  3. Studying patterns and causes
  4. How to manage complexity of algorithms? & data management cycle
  5. How to get graphic and seeing the data?
  6. How to prepare data for success?
  7. New statistics transforming sports
  8. Identifying political polls – how weighted averaging wins?
  9. When life is (almost) linear – regression
  10. How to train computers to think like humans?
  11. Identifying anomalies and breaking trends
  12. Simulation beyond data and equations
  13. Overfitting – too good to be truly useful
  14. The math of march madness – bracketology
  15. Understanding quantifying quality on the world wide web
  16. Text and sentiment analysis – watching words and data compression and recommendation systems
  17. Learning about decision trees – jump start an analysis
  18. Many ways to create groups – clustering and social networks
  19. Understanding challenges of privacy and security
  20. How to set the analytical foundations for the future?

Who is it for?

Analysts, IT, and other technical professionals.

Certification:

Successful candidates will be awarded a certificate in Mastering Big Data.

Benefits you will gain:

By enrolling in this course, you’ll get:

  • High-quality e-learning study materials and mock exams.
  • Tutorials/materials from the industry leading experts.
  • Includes step-by-step tutorial videos and an effective, professional support service.
  • 24/7 Access to the Learning Portal.
  • The benefit of applying for NUS extra Discount Card.
  • Recognised Accredited Qualification.
  • Access Course Content on Mobile, Tablet or Desktop.
  • A study in a user-friendly, advanced online learning platform.
  • Excellent customer service and administrative support.

Course Code 1095
College Name Global Edulink
Course Category Business, Data Analytics
Course Type Online Learning
Course Qualification CPD
Course Location Ireland
Course Fee 67.00
Course Duration 12 GUIDED LEARNING HOURS
Course Times All delivered through a system that you will have access to 24 hours a day, 7 days a week for 365 days (12 months).
Title of Awarding Certificate in Mastering Big Data.
Entry Requirements No entry requirements though it may be useful to have a general technical background. This course is available to all students, of all academic backgrounds. However, basic knowledge of Microsoft Office would be an advantage. Learners should be ages 16 or over to undertake the qualification. Basic understanding of English language, literacy, numeracy and ICT are required to attend this course.
Career Path Senior Business Analyst, Data Governance , Experimentation and Web Analytics Analyst , Strategic Analytics Manager , Business Science Data Planner , Digital Analyst , Business Intelligence Engineer ,
For information about Global Edulink, please visit our college page on www.nightcourses.com by clicking here.

Course Provider

Global Edulink



CityPoint, 1 Ropemaker Street, London, EC2Y 9HU, Dublin, United Kingdom

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Global Edulink
CityPoint, 1 Ropemaker Street, London, EC2Y 9HU
Dublin
Dublin
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