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GICT Big Data Science

Obtain a Certification in Big Data Science

Under CITREP+ funding

* Conditions Apply

Courses are delivered by GICT only in Singapore. For other locations, contact our authorised partners directly by clicking here.
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Objective of the Certified Big Data Science Analyst Course (CBDSA)

A big data science analyst’s main objective is to organize and analyze large amounts of data, often using software specifically designed for the task. The result of the analysis needs to be simple enough for all invested stakeholders to understand — especially those working outside of IT.

A data scientist’s approach to data analysis depends on their industry and the specific needs of the business or department they are working for. Before a data scientist can find meaning in structured or unstructured data, business leaders and department managers must communicate what they’re looking for. As such, a data scientist must have enough business domain expertise to translate company goals into data-based deliverables such as prediction engines, pattern detection analysis or even optimization algorithms.

Certified Big Data Science Analyst (CBDSA) course covers the concept of Business Analytics and Big Data technologies with its strategic importance to any organization. Participants will be introduced to the concept of business analytics with big data technologies: Hadoop, Hive and HBase. The course deals with basic principles, concepts, and techniques/tools used for big data and business analytics, which includes data mining, Hadoop, HDFS & MapReduce, Apache HBase and Apache Hive. Also, this course covers different types of business analytics with real life use cases including association rule mining and regression models. Participants will get good picture of all these concepts and how they all are interconnected to each other in organizational context.

Big Data Science Course Outline:

  • Unit 1: Introduction to Business Analytics
  • Unit 2: Data/Information Architecture for Business Analytics
  • Unit 3: Data Mining Tool
  • Unit 4: Data Mining Techniques
  • Unit 5: Introduction to Big Data
  • Unit 6: Introduction to Hadoop
  • Unit 7: Hadoop HDFS & MapReduce
  • Unit 8: Apache HBase
  • Unit 9: Apache Hive

Course Outcome

  • Acquire knowledge of complete Big Data Technologies stack from Data Storage, Data Processing, Data Visualisation to Data Analytics
  • Learn necessary skills to manage and analyse big data
  • Implement key predictive modelling Algorithms on RapidMiner Tool
  • Perform Exploratory data analysis and data pre-processing techniques
  • Identify the right tool for solving real life big data problems
  • Gain hands on expertise in using Big Data Technologies Like Hadoop, Map Reduce, HBase and Hive


  • 40 Hours (5 Days) Classroom Training

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