Grow Data Skills - Data Engineering Bootcamp 2.0

Fast Track Data Engineering Bootcamp
(NooB 2.0 LIVE Batch)

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Language English
Sessions 24
Duration3 Months
Starts On Coming Soon
Validity 1 Year
Mode Live

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This course includes

100+ hours content live lecture
60 minute live doubt session after each class and doubt support on discord
5 Industry level real world projects
Learn while solving real life examples in live lectures
BigData Projects on AWS Cloud
Projects will be covered from scratch
Hands on exercises & quizzes after each module
Career & Interview Preparation guidance
Resume Preparation
Linkedin Profile Making
Certificate of completion

Tools you'll learn

Course Content

MySQL Installation guide Connection & set up
DDL, DML, DCL in SQL
Data type of SQL
Create, Insert, Update, Alter, Delete, Drop, Truncate Operations
Views in SQL
Operators in SQL
WHERE clause, ORDER BY clause, GROUP BY & Having Clause
Aggregations Group Concat & Roll UP
CASE-WHEN Statement
Joins in SQL - Inner, Left, Right, Full, Self
Correlated subqueries IN, NOT IN, ANY, ALL, EXISTS, NOT EXISTS
Window Functions
Frame Clause in Window Functions
Common Table Expressions - Recursive, Iterative

5 V’s of BigData
Distributed Computation
Distributed Storage
Cluster, Commodity Hardware
File Formats
Types of Data
Hadoop Complete Architecture - HDFS, Map Reduce, YARN

Hive Architecture
Hadoop & Hive Setup on GCP Dataproc Cluster
HQL (Hive Query Language)
Working with different file formats in Hive
Partitioning and Bucketing in Hive
Optimized Joins in Hive
Optimizing Hive Queries

Kafka Cluster
Brokers
Topics
Partitions
Producer-Consumer
Offset Management
Replicas
Commits
Sync & Async Commits
Confluent Kafka Setup
Topic Creation
Schema Registry
Key, Value Message
Message in Kafka Topics based on Random and Constant Keys
Kafka Producer Code with Serialisation
Kafka Consumer Code with De-Serialization
Consumer Groups
Working with JSON, CSV Data

CAP Theorem
What is MongoDB and MongoDB Atlas?
MongoDB vs Relational Database
MongoDB features
MongoDB use cases and applications
MongoDB architecture
Node
Data Centre
Cluster
Data replication
Write operation
Read operation
Indexing
MongoDB Atlas Setup
Understanding different ways to communicate with MongoDB
Query data from MongoDB tables
Create APIs for MongoDB table data
Queries on MongoDB using Python
Bonus - Apache Cassandra Complete (Recorded Session)

Spark Complete Architecture
Memory Management in Spark
Spark Core, Dataframes & Functions in PySpark
Use SQL in PySpark
PySpark Structured Streaming With Kafka
Common Failures in Spark and their solutions
Optimization Techniques in Spark
Implement PySpark Application on GCP Dataproc Cluster
What is Databricks?
Databricks Setup
Create Cluster on Databricks
Data Import & Export in Databricks
PySpark Notebook on Databricks
Excute PySpark Code on Databricks Cluster

Introduction of Airflow
Different Components of Airflow
Installing Airflow
Setup Airflow Using GCP Cloud Composer
Understanding Airflow Web UI
DAG Operators & Tasks in Airflow Job
Create & Schedule Airflow Jobs For Data Processing

OLAP vs OLTP
What is a Data Warehouse?
Difference between Data Warehouse, Data Lake and Data Mart
Fact Tables
Dimension Tables
Slowly changing Dimensions
Types of SCDs
Star Schema Design
Snowflake Schema Design
Data Warehousing Case Studies
Inroduction of SnowFlake Data Warehousing Service
SnowFlake Architecture
Complete Setup of SnowFlake
Create Data Warehouse on SnowFlake
Analytical Queries on SnowFlake Data Warehouse
Undestanding SnowPark (Execute PySpark Application on SnowFlake)
What is GCP BigQuery?
GCP BigQuery Architecture
Complete Setup of GCP BigQuery
BigQuery Tables & Data Load
Create Data Warehouse on GCP BigQuery
Analytical Queries on GCP BigQuery Tables
Analytical Queries on GCP BigQuery Tables
Data Read & Write From BigQuery Tables in PySpark

S3
Lambda
IAM
CLOUDWATCH
EC2
SNS
SQS
EMR
GLUE
RDS
ATHENA
REDSHIFT

Batch Data Pipeline Project - 1 (GCP/AWS, Hive, PySpark, Airflow)
Batch Data Pipeline Project - 2 (GCP/AWS, Hive, PySpark, MongoDB/Cassandra, Airflow)
Real Time Data Pipeline Project - 1 (GCP/AWS, Kafka, PySpark Structure Streaming)
Real Time Data Pipeline Project - 2 (GCP/AWS, Kafka, PySpark Structure Streaming)
Batch & Real Time Data Pipeline Project on AWS (S3, Kinesis, DynamoDB, EventBridge Pipe, Lambda, Redshift, Athena, Cloud Composer, BigQuery, PySpark)

Attention Seeking Resume Preparation and Interview Strategies
Strategies To Crack Tech Interviews

Linkedin Profile Making
How To Expand Your Professional Network On Linkedin
How To Use Various Job Portals
How To Approach For Referrals

Course Schedule

Course Starts:

Coming Soon

Course Duration:

3 Months

Class Schedule:

LIVE [Saturday, Sunday]

Mode of the Course:

LIVE mode

Class Timings:

Saturday & Sunday [9:00 AM - 11:30 AM Live Teaching, 11:30 AM to 12:30 PM Live Doubt Session] (IST)

Extra Classes:

In case Extra class is needed, it will be scheduled on weekdays [ Wednesday or Thursday , 9:30 PM to 11:30 PM] (IST)

Class Duration:

2.5 Hours Live Teaching, 60 minutes Doubt Solving

Class Recording Provided:

Yes

Course Validity:

1 year

Programming Language Used:

Python

Prerequisite:

Check Our Python Bootcamp

Instructor

Shashank Mishra

Shashank Mishra is a seasoned Data Engineer with over 6 years of industry experience, worked at leading companies like Amazon, PayTM, and McKinsey & Company.

Why Data Engineer?

Map your interest to check if Data Engineer profile is a close match for you.

Who should become a Data Engineer?

Check if you are a good fit for a Data Engineer role.

Mandatory skill sets

You need to acquire these skill sets to become a Data Engineer.

Career growth of a Data Engineer

Growth of a Data Engineer from 0 to 10+ Years Of Experience.

Empowering aspiring data professionals to soar with upskilling opportunities.

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E-mail: support@growdataskills.com

Location: Gurgaon

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Fast Track Data Engineering Bootcamp (NooB 2.0 LIVE Batch)

Language English

Sessions 24

Duration3 Months

Starts On Coming Soon

Validity 1 Year

Mode Live

Tools you'll learn

Course Content

Module 1 - SQL

Module 2 - BigData Fundamentals & Hadoop

Module 3 - Apache Hive & Hadoop Cluster On GCP

Module 4 - Confluent Kafka

Module 5 - MongoDB (NoSQL DataBase)

Module 6 - Apache Spark (PySpark) On Databricks & GCP Cloud

Module 7 - Apache Airflow With GCP Cloud Composer

Module 8 - Data Warehousing With SnowFlake & GCP BigQuery

Module 9 - AWS

Module 10 - Industrial Projects

Module 11 - Resume And Interview Strategies

Module 12 - Guidance For Effective Job Searching

Course Schedule

Instructor

Shashank Mishra

Why Data Engineer?

Who should become a Data Engineer?

Mandatory skill sets

Career growth of a Data Engineer

Namaste 🙏

Fast Track Data Engineering Bootcamp
(NooB 2.0 LIVE Batch)