[Hindi] PySpark Industry-Level Mastery / Databricks Certified Spark 3 Developer Training

About Course

Course Consists on 500 Hands on Exercises and Two End to End Pyspark Project
Live doubt sessions every weekend,
Overall 100 hours of learning,
30 hours of Python training,
Pyspark 500 hands-on exercises ,
Two real time projects(LIVE sessions),
Databricks certification training,
Streaming data processing scenarios with : Kafka and Spark,
Best industry practices for optimization for PySpark projects

Curriculum :

Apache Spark Introduction
Spark Internals | Spark Architecture In Depth Tour
Python Foundations
RDD Programming in PySpark
SparkSQL Introduction
Intense Hands on | SparkSQL DFs
SparkSQL Advanced Concepts | Optimizations
PySpark 500 Exercises
Spark Streaming and Kafka
All optimization techniques used in Industries for Spark Applications.
Creating and Deploying spark Applications on AWS EMR
End to End PySpark Project on AWS Cloud.

Course Content

Spark Introduction

Spark Introduction

01:00:03

Spark Architecture

PySpark Installation on Windows

Pre Requisite 1 : The Python Adventure

Python | Pre requisites

03:58
Session 1 | Setup and Cloning Repo

01:03:19
Session 2 | python | Variables and Printing

53:55
Session 3 | Python | Formatting and Escape Sequences

29:22
Session 4 | Python | Decision making | if elif else

50:10
Session 5 | Python | List Tuple Set Dictionaries

51:53
Session 6 | Python | Loops

46:30
Session 7 | Python | Gaming using loops

33:51
Session 8 | Python | List comprehension | String slicing

45:57
Session 9 | Python | Slicing and step

01:00:55
Session 10 | String Manipulation

51:57
Session 11 | String Manipulation 2

01:14:27
Session 12 | list comprehension

56:52
Session 13 | Functions Introduction

01:05:47
Session 14 | Functions 2

01:09:21
Session 15 | lambda functions

01:00:30
Session 16 | File IO

01:08:12
Session 17 | Modules | Exception handling

02:19:51
Session 18 | Regular Expressions

01:00:27
Session 19 | RE | OOP Introduction

01:25:25
Session 20 | Class Instance Attributes

53:10
Session 21 | Class Methods vs Instance Methods vs Static Methods

02:10:18
Session 22 | Dunder methods | Operator overloading

01:04:14
Session 23 | Property Decorator

54:39
Session 24 | Encapsulation and Private attributes

54:39
Session 25 | Abstraction and Spark Introduction

01:47:44

RDD Operations

SparkSQL

pyspark-practice-hands-on-200

Pyspark200 Setup

01:13:39
Creating DFs using textFiles

44:14
Creating DF using Binary file Formats

24:55
Creating DF doubts

01:03:34
Creating DF using mysql, s3

03:14
Select SelectExpr

35:06
Select Filter Intermediate

17:00
withColumn and withColumnRenamed

01:25:11
sort orderBy

34:25
groupBy and aggregate

32:01
join operations

35:59
set operations

39:59
Window Operations

01:19:09
Data Cleaning

54:26
distinct and dropDuplicates

15:26
pivot unpivot

37:37
UDF

35:21

PySpark DF Scenarios and Databricks Certification Practice

Spark SQL Advanced

Certification Dump Discussion

PySpark 500

Deploying Spark Applications on AWS EMR

End To End PySpark Project

Course Material

Kafka Sessions

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About Course

What Will You Learn?

Course Content

Spark Introduction

Spark Introduction

Spark Architecture

Spark Achitecture Overview | Driver, Cluster Manager, Executor, RDD

RDD Operations | Types of Transformations | DAG

Spark Application | Job | Stages | tasks

Spark Architecture End to End

Spark Deploy Modes

PySpark Installation on Windows

PySpark Installation on windows

Pre Requisite 1 : The Python Adventure

Python | Pre requisites

Session 1 | Setup and Cloning Repo

Session 2 | python | Variables and Printing

Session 3 | Python | Formatting and Escape Sequences

Session 4 | Python | Decision making | if elif else

Session 5 | Python | List Tuple Set Dictionaries

Session 6 | Python | Loops

Session 7 | Python | Gaming using loops

Session 8 | Python | List comprehension | String slicing

Session 9 | Python | Slicing and step

Session 10 | String Manipulation

Session 11 | String Manipulation 2

Session 12 | list comprehension

Session 13 | Functions Introduction

Session 14 | Functions 2

Session 15 | lambda functions

Session 16 | File IO

Session 17 | Modules | Exception handling

Session 18 | Regular Expressions

Session 19 | RE | OOP Introduction

Session 20 | Class Instance Attributes

Session 21 | Class Methods vs Instance Methods vs Static Methods

Session 22 | Dunder methods | Operator overloading

Session 23 | Property Decorator

Session 24 | Encapsulation and Private attributes

Session 25 | Abstraction and Spark Introduction

RDD Operations

RDD Basics

RDD exercises Hands On | PySpark

RDD practice | PySpark

Broadcast Vraiables | PySpark

Accumulator and SparkSQL Introduction | PySpark

SparkSQL

Introduction to sparkSQL

DF vs DS | Catalyst Optimizer

Creating DataFrames from various Sources

SC vs SS | TempView vs GlobalTempView | PySpark

DF Structured Transformations | PySpark

Executor Memory Architecture

pyspark-practice-hands-on-200

Pyspark200 Setup

Creating DFs using textFiles

Creating DF using Binary file Formats

Creating DF doubts

Creating DF using mysql, s3

Select SelectExpr

Select Filter Intermediate

withColumn and withColumnRenamed

sort orderBy

groupBy and aggregate

join operations

set operations

Window Operations

Data Cleaning

distinct and dropDuplicates

pivot unpivot

UDF

PySpark DF Scenarios and Databricks Certification Practice

Session : 1

Session : 2

Session : 3

Session : 4

Session : 5

Session : 6

Session : 7

Session : 8