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2 Students

Description

What Will You Learn?

  • SparkR Programming
  • Big Data Tools for R
  • Power BI Data Visualization
  • Data Analysis
  • Geo Mapping with Power BI

Requirements

  • Basic Understanding of R Programming
  • Little or no understanding of GIS
  • Basic understanding of Programming concepts
  • Basic understanding of Data
  • Basic understanding of what Machine Learning is
  • NFT Certificate
  • 25 Lessons
  • Intermediate
  • English
  • +110 XP

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Curriculum

Course consist of total 3h 22min of content, in total.

Section 1: Introduction
07:43
Section 2: Setup and Installations
52:46
R Installation
05:10
Installing Apache Spark
12:07
Installing Java (Optional)
04:35
Testing Apache Spark Installation
02:33
Installing MongoDB
03:47
Installing NoSQL Booster for MongoDB
07:11
Installing SparkR
03:04
Configuring SparkR
14:19
Section 3: Building the Big Data ETL Pipeline with SparkR
46:23
Data Extraction
07:29
Data Transformation 1
13:36
Data Transformation 2
15:49
Data Exporting
09:29
Section 4: Big Data Machine Learning with SparkR and MLlib
41:50
Data Pre-processing
18:48
Building the Predictive Model
10:28
Creating the Prediction Dataset
12:34
Section 5: Data Visualization with Power BI
53:35
Installing Power BI Desktop
01:55
Installing MongoDB ODBC Drivers
03:29
Creating a System DSN for MongoDB
04:05
Loading the Data Sources
03:55
Creating a Geo Map
10:53
Creating a Donut Chart
08:24
Creating a Area Chart
08:15
Creating a Stacked Bar Chart
12:39
Section 6: Project Source Code
Source Code

About the Instructor

Edwin Bomela is a Big Data Engineer and Consultant, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development.

He is currently a consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.

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