Advanced Data Engineering

Edupristine

This program features a comprehensive curriculum meant to polish your knowledge of Big Data tools and make you an expert in the Big Data system.

Online

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study, Campus Based/Physical Classroom	Mode of Delivery Video and Text Based

Course overview

The importance of Data analysis has amplified in the last few years. The Advance Data Engineering training course will present you with the knowledge you require to evaluate data-sets with great expertise.

The Advance Data Engineering online course is self-paced. You will have access to industry-specific and industry-relevant study material. Furthermore, you will be groomed by industry experts in the art of Big Data Tools such as Apache NIFI, MongoDB, SparkStreaming, KAFKA, SparkRDD, HUE, SparkSQL, Python, FLUME, and DataFrame.

The practical projects will put you into a real-life simulation. There will also be after course engagement sessions and dedicated discussion forums to lay your doubts to rest. Furthermore, you will receive job updates, along with reliable career management and resume building aids. Additionally, you will also get unrestricted access to the LMS for a full year.

Incidentally, the EduPristine Advance Data Engineering curriculum will provide you with ample opportunities to showcase your skills as a data engineer. Finally, you will be receiving the Advance Data Engineering Certification after completing this programme.

The highlights

Forty hours of self-paced industry-specific course material
Expert mentors
Practical projects
One year access to LMS
Discussion community
After course engagement (ACE)
Niche career assistance
Resume services
Data Engineering certification

Program offerings

Extensive faculty network
Profound alumni pool
Career service
Soft skills development
Real life projects
Experimental training
Corporate training
Classroom training

Course and certificate fees

certificate availability

Yes

certificate providing authority

Edupristine

Who it is for

Data analyst Data scientist Data engineer

What you will learn

Knowledge of big data Knowledge of mongodb Knowledge of python Knowledge of kafka

The Advance Data Engineering programme will expose you to the following Big Data Tools, including:

FLUM
KAFKA
A host of Spark tools like SparkRDD, SparkSQL, and SparkStreaming
DataFrame
Apache NIFI
HUE
Python
MongoDB

The syllabus

Apache Flume

Flume Agent

Source
Channel
Sink

Flume Event

Configuration File

Examples

Example 1 – Spool source and console sink
Example 2 – Spool Source and HDFS Sink
Example 3 – Fan-out (single source with multiple Sink)
Example 4 – Netcat Source with console sink

Kafka

Kafka Architecture

Producer
Consumer
Topic
Broker

Benefits of Kafka

Start single broker on a single node

Multiple broker on a single node

Check Fault tolerance - Multiple Broker

Spark Core - Python

Introduction to Python programming

Spark Architecture and Tungsten Engine optimization

Spark 2.0 Performance Improvements

RDD

Lineage

RDD operations

Transformations
- Map
- FlatMap
- Filter
- Distinct
- Sampling
- Ma Values
- FlatMapValues
- Union
- GroupBy
- Cogroup
- KeyBy
- reduceByKey
- foldByKey
- groupByKey
- aggregateByKey
- combineByKey
- JOIN
- MapPartition
- mapPartitionWithIndex
- Coalesce
- Repartition
Actions
- Take
- Top
- Collect
- Take Ordered
- Count
- CountByValue
- First
- Max
- Min
- Reduce
- Fold
- Aggregate
- CountByKey
- Lookup
- CollectAsMap

Accumulator

Broadcast

Persist(Cache) RDD

SparkSQL and Dataframe

SparkSession

DataFrame

Simple data in DataFrame

Complex data in DataFrame

DataFrame created using SQLContext

JOINS in DataFrame

Analyzing data Using Spark SQL

External Datasets using Spark SQL

Inferred Schema

Explicit Schema

Window Function

Use case - Analyzing Crime Data using Grouping, Aggregating and ordering

Use case – Analyzing player data

Catalyst optimizer

SPARK Streaming

Theory

Streaming data

DStream

Stateless Transformations

Stateful Transformations

Demo - Listen for streaming text data on a host and port (Stateless)

Demo – updateStateByKey

Demo - Window operation

Window size
Sliding interval

Demo – countByWindow

Demo – reduceByWindow

Summary Function
Inverse Function

Demo – reduceByKeyAndWindow

Spark streaming with Kafka Topic

Structured Streaming in Spark 2.x

MongoDB

No-SQL Databases Types

Mongod to start using Configuration file

Database

Collection

Document

Mongo Import

Mongo Export

How to update/save/remove documents in collections

How to Query documents in MongoDB collections

Aggregate

MongoDB Map reduce

Lookup

Working with Mongo Shell

Index

Single Key Index
Text Index
Index and Performance
Unique Index
Sparse Index
TTL Index (TimeToLive)
Rebuild & Compact

User Management

Create Super/Admin User
Create normal Users
Drop User

Replication

Replica Set Primary
Replica Set Secondaries
Replica Set Arbiter
Replica Set Oplog
Replica Demo
Failover
Freeze
Stepdown
Chaining
Write Concern

Shard

Config Servers
Shard Key
Shard Demo

Backup and Repair

mongodump and mongorestore
Data File Backup

Storage Engines

mmapv1
wiredTiger

CAP Theorem

Live Project

Analytics Project Scenario using PySpark, Spark Streaming, Flume, and Kafka (Sentiment Analysis using Spark on Twitter data)

Understanding different tools usage in real project

How it helps

Using the Advance Data Engineering programme from EduPristine, your knowledge about big data will improve exponentially. You will become an expert in wielding Big Data Tools which are relevant today.

You will be made market-ready due to experimental and practical training sessions. There will be practical case studies, where you will mix with industry experts and expert faculty members will groom you. Additionally, you will get access to the discussion forums and the after-course engagement sessions to expand your knowledge and network with people.

The career services will update you about job opportunities and help structure your resume. After completing the course, you will be a certified Advance Data Engineer. EduPristine has diverse alumni who work at DHFL, Infosys, Amazon, The Indian Express and Deloitte, among others.

FAQs

Why should I undertake the Advance Data Engineering training programme from EduPristine?

The Advance Data Engineering programme will prepare you with the skill-sets required to analyze big data. You will learn how to organize data sets and put them into clear structures. After completing the course, you will be a certified Advance Data Engineer.

What is the structure of the Advanced Data Engineering programme?

Only 30 applicants are accepted per batch for the Advance Data Engineering programme. The course material is expansive and immersive and has been built to make you industry-ready.

What additional benefits will be made available to me?

Apart from the course material and expert faculty members, you will receive career coaching and mentoring. Additionally, you will receive updates about potential employment opportunities. The resume building exercises are designed to help better your resume and help you with that first impression. Moreover, you will also have 1-year access to the learning module, and to the discussion network.

How can I contact EduPristine?

You can send an email at care@edupristine.com or visit their registered offices at Mumbai, Hyderabad, Bengaluru, Pune, or Delhi. Furthermore, you may prefer calling on 1800 200 5835 or requesting a call-back.

Which companies hire certified Data Engineers?

After successful completion of this course, you can work in companies such as Amazon, Accenture, HSBC, Infosys, Axis Bank, Deloitte, The Indian Express, among others.

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