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Big Data - Hadoop & PySpark for College students

Language: English

Instructors: Blismos Academy

$15

 

Course Curriculum
Introduction
Welcome to the Course Video
The Fundamentals
Data VS Information
Data Storage and Processing
Data Sources
Big Data Introduction
Fundamentals Assessment
The Foundations of Big Data
2.1 Emergence of Big Data
Emergence of Big Data
Basic Terminologies
Foundations Assessment 1
2.2 Central Theme of Big Data
Central Theme of Big Data
Requirements of Programming Model
Understand Distributed Processing through a Story
Foundations Assessment 2
Environment and Installations
OracleVMInstallation
1Oracle_VM_Installation_1
Google Cloud Platform Setup
How to install Ubuntu operating system on Virtual box
How to install PySpark on Ubuntu with Java and Python_3
How to configure Pyspark with Pycharm_with_Installation
Google Cloud Platform Setup
Hadoop Ecosystem
3.1 Introduction to Hadoop Ecosystem
Introduction to Hadoop Ecosystem
Hadoop Ecosystem Assessment 1
3.2 Hadoop Distributed File System
What is HDFS?
Nodes in HDFS
HDFS Assessment1
Storing File in HDFS
Reading File from HDFS
HDFS Assessment2
HDFS Assessment3
HDFS Commands Part 1
HDFS Commands Part2
HDFS Assessment 4
3.3 Map Reduce
Introduction to Map Reduce
Map Reduce Flow Example 1
Map Reduce Implementation
Map Reduce Example 2 - User View Count
Map Reduce Mappers and Reducers
MapReduce Assessment 1
Shuffle-Sort-Partitions
MapReduce Assessment 2
3.4 Hive
Transactional and Analytical Processing
What is Data warehouse?
Introducing Hive
Hive Assessment 1
Hive Hands-on1
Hive Hands-on2
Hive Hands-On Assessment 1
Hive vs RDBMS
Hive Architecture
Hive Metastore
Hive Assessment 2
Hive Hands-on2
Hive Hands_on Assessment 2
Primitive Datatypes in Hive
How storage works in Hive
Different types of Tables in Hive
Hive Assessment 3
Hive Hands-on4
Hive Hands-on5
Hive Hands-on Assessment3
Inserting the Data into Hive Tables
Hive User Defined Functions
Hive Assessment 4
Hive Hands-on6-Inserting data into Tables
Hive Hands_on Assessment 4
Hive Optimization Of The Queries Theory
Python for PySpark
Introduction to Programming
Introduction to Programming
Python Programming
Introduction to Python
Environment for Python
Executing Python Code
Python Assessment 1
Syntax, Indentation and Comments
Syntax, Indentation and Comments - Practical
Variables
Variable Practical's
Python Datatypes
Python Datatypes Practicals
Python Assessment 2
Python Operator Concepts
Python Operator Praticals
Control Flows in Python
Control Flows - IF ELSE Concepts
If Else Practical
Loops Theory
Loops Practical
Python Assessment 3
Python Function Concepts
Python Function Hands-on
Apache Spark
Introduction to Spark
Why Spark?
Advantages of Spark
What is Spark?
Components of Spark
History of Spark
Introduction to Spark Assessment1
Overview of the Spark
Architecture of Spark
Spark Session
Spark Sessionin Terminal & Jupyter notebook
Spark Language API
Overview of the Spark Assessment1
Dataframes and Partitions
How to Create Dataframe in Terminal and in Jupyter Notebook?
Spark Transformations
Spark Actions
Overview of the Spark Assessment2
Structured API Overview
Structured APIs - Dataframes and Datasets
Schema Definition
Spark Types
Structured API Execution
Structured API Overview Assessment1
Operations on Dataframes
Dataframe Columns
Columns as Expression
Dataframe Rows
Operations on Dataframe Assessment1
Ways of Creating Dataframe
Methods to Manipulate Columns
DataFrame Transformations
Operations on Dataframe Assessment2
Dataframe Transformation - Columns
Dataframe Transformations - Rows Part1
Dataframe Transformation - Rows Part2
Operations on Dataframe Assessment3
Working with Different Types of Data
Introduction to working with Different Types of Data
Working with Booleans
Working with Numbers
Working with Strings
Working with Strings Practical1
Working with String Practical2
Introduction to working with Different Types of Data Assessment 1
Introduction to working with Different Types of Data Assessment 2
Creating Dataframes from different sources
Data Sources Introduction
Read-API- Data Sources
Read-API-Practical
Write-API-Data Sources
Write-API-Practical
Creating Dataframes from different sources Assessment 1
Reading from CSV Files
Writing into CSV Files
Reading from JSON Files and Writing into JSON
Unstructured Data - Text File - Reading and Writing
Introduction to reading data from structured sources
Reading data from structured sources - Database - Concepts
Reading data from structured sources - Database - Practicals
Creating Dataframes from different sources Assessment 2
Aggregations
Introduction to Aggregations
Aggregataion Concepts - Count
Aggregation_Practical-1-Count
Aggregation Concepts - First, Sum and Average
Aggregation - Practical - 2FirstLastAverage
Aggregation Assessment 1
Aggregation concepts - Statistical Functions
Aggregation-Practical-3-StatisticalFunctions
Aggregation Assessment 2
Spark Joins
Spark Joins Theory-1-Introduction
Spark Joins Theory-2-How Joins Work
Spark Joins-Theory-3-Inner Joins
Spark Joins -Practical -1-Innerjoins
Saprk Joins - Theory-4 - Outer Joins
Spark Joins -Practical - OuterJoins
Spark Joins -Theory - 5-Left Semi & Anti Joins
Spark Joins - Practical - LeftSemiAntiJoins
Spark Joins -Theory -8-CommunicationStrategies
Joins Assessment
Resilient Distributed Datasets-RDDs
What is an RDD ?
Introduction to Low Level APIs
Properties Of RDD
When to use RDDs
Creating RDDs
RDD Practical-1-Creating RDDs
RDD Assessment 1
RDD Transformations
RDD - Transformations Practical
RDD Actions
RDD Actions - Practical

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