Big Data Scientist Certification Exam Preparation With Edureify AI

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240 min
Duration
120
Questions
75
Passing Score

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Learning Progress

Big Data Technologies 85%
Data Science and Analytics 92%

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95%
Latest Score
Above passing threshold

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Big Data Scientist Syllabus

Big Data Technologies

Understanding and applying various big data technologies such as Hadoop, Spark, and NoSQL databases.

20%
Weight
24
Questions
120
Marks

Hadoop Ecosystem

  • Hadoop Distributed File System (HDFS)
  • MapReduce Programming Model
  • Hadoop YARN
  • Hive, Pig, and HBase

Apache Spark

  • Spark RDDs
  • Spark DataFrames
  • Spark SQL
  • Machine Learning with Spark

Data Science and Analytics

Understanding of data science methods and techniques, including statistical analysis and machine learning.

25%
Weight
30
Questions
150
Marks

Statistics for Data Science

  • Descriptive Statistics
  • Probability Theory
  • Inferential Statistics

Machine Learning Algorithms

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

Data Processing and Storage

Understanding how to process and store large datasets using big data tools and technologies.

20%
Weight
24
Questions
120
Marks

NoSQL Databases

  • MongoDB
  • Cassandra
  • HBase

Data Processing Frameworks

  • Apache Flink
  • Apache Beam
  • Stream Processing

Data Visualization

Ability to visualize and communicate insights from big data using appropriate tools and techniques.

15%
Weight
18
Questions
90
Marks

Visualization Tools

  • Tableau
  • Power BI
  • D3.js

Data Visualization Principles

  • Charts and Graphs
  • Storytelling with Data
  • Interactive Dashboards

Big Data Security

Understanding how to secure big data environments and protect sensitive information.

10%
Weight
12
Questions
60
Marks

Data Privacy and Compliance

  • GDPR
  • Data Encryption
  • Data Masking

Security in Big Data Technologies

  • Security Measures for Hadoop
  • Spark Security
  • Access Control and Authentication

Real-World Data Science Applications

Applying big data science techniques to solve business problems and real-world issues.

30%
Weight
36
Questions
180
Marks

Business Intelligence with Big Data

  • Predictive Analytics
  • Customer Segmentation
  • Recommendation Systems

Big Data in Healthcare

  • Healthcare Predictive Modeling
  • Patient Data Analysis

Big Data in Finance

  • Fraud Detection
  • Risk Management

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1

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2

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3

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