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GCP Data Engineering Mastery

AWS Services For Data Engineering With Projects

By Shashank In Grow Data Skills

Live Classes (26-April-2025)
English
Completion Certificate

Demo Class Video

1 Year

Validity (From the date of Enrollment)

50 Hours

Duration

12

Sessions

5

Projects

INR 3500

Admission Open - 10 Seats Left Now

Buy Now

This course includes

Content Duration50 Hours
Total Sessions12
Total Industry Projects5
Recording of each live class will be provided.
(So don't worry if you miss attending any live class)
GCP Cloud
Quality Assignments & quizzes after each module
Interview preparation guide
Dedicated placement assistance
Resume & Linkedin profile making
Doubt support on private discord community
Certificate of completion

Tech stack you'll learn

GCP Services For Data Engineering With Projects

Course Content

Get credit card of Visa/Mastercard type (Don't try with Debit Card, Net Banking or UPI etc).
Enable Online & International Transactions - Enable this via your bank app or customer service and make sure to enable AutoPay as well.
Use the same name on the card and GCP account to avoid verification issues.
While setting up Billing profile in GCP or at any step if it asks for address then make sure the address matches what’s registered in your bank credit card.
Avoid Using VPN - VPNs can trigger fraud detection and block your account.
GCP does not charge you during the Free Tier or 90-day trial unless you upgrade. Set budget alerts to monitor spending.

✅ Class - 1

Overview of GCP Free Tier account setup
Gcloud CLI setup
Google Cloud Storage (GCS)
Create & Access Buckets, File in GCS from CLI
Create & Access Buckets, File in GCS from Python Script
IAM (Identity and Access Management) & Role Based Access
Setup & Access Cloud compute machine (GCP Compute Engine)
Server health monitoring and alerting (GCP Cloud Monitoring & Cloud Logging)

✅ Class - 2

GCP Cloud Functions
GCP Cloud Functions implementation and Execution
GCS event notification trigger in GCP Cloud Functions
GCP Cloud Functions code testing with test event
GCP Cloud Functions code packaging and deployment with & without external library dependency

✅ Class - 3

Scheduling of GCP Cloud Functions (GCP Cloud Scheduler)
Setup GCS Create/Update/Delete Object notification trigger event
Read CSV data from GCS in GCP Cloud Functions using notification trigger
CICD in GCP
Setup GCP Cloud Build and Connect with Github
CICD pipeline for GCP Cloud Functions using GCP Cloud Build

✅ Class - 1

GCP Pub-Sub Setup
Topics & Subscribers in GCP Pub-Sub
Implementation & Execution of Producer and Consumer code for GCP Pub-Sub
Setup & Access MySQL database in GCP using GCP Cloud SQL

✅ Class - 2

Setup & Acccess GCP Bigtable
CDC Stream in GCP Bigtable
Fundamentals of GCP Dataflow for Stream Data Processing
Data sync pipeline from GCP Pub-Sub to GCP BigTable using GCP Dataflow
CDC stream processing using GCP Dataflow

✅ Class - 1

GCP Dataproc Setup
PySpark driven data pipeline execution on GCP Dataproc
GCP Data Fusion Overview
GCP Data Fusion Connection
PySpark based End-to-End ETL pipeline implementation on GCP Data Fusion
Trigger & Scheduling of GCP Data Fusion jobs
Streaming data processing using GCP Data Fusion

✅ Class - 2

BigQuery Overview
BigQuery Architecture
Capacitor — Columnar Format
Colossus — Storage
Dremel — Execution Engine
Borg — Compute
Jupiter — Network
BigQuery Studio
Industrial Project - 1 : Travel Bookings Streaming data ingestion into BigQuery(Industrial Project)
Tech Stack: Python GCP Storage, GCP Pub-Sub, BigQuery, Dataflow
Automation of ETL pipelines and flows using GCP Workflows

✅ Class - 1

Setup Airflow on GCP using Composer
Create and schedule Airflow Dag with sequential tasks using BashOperator and PythonOperator
Create and schedule Airflow dag with parallel tasks using BashOperator and PythonOperator
Airflow Exercise - 1 : End-To-End Airflow Dag to Create Dataproc Cluster, Run PySpark Job on cluster and Delete GCP Dataproc cluster
Airflow Exercise - 2 : Airflow Dag to support data backfilling via parameterized date inputs and use if Variables in Airflow

✅ Class - 1

Industry Project - 2 : Flight Booking Data Pipeline with Airflow & CICD
Industry Project - 3 : Credit Card Transactional Analysis For Fraud Risk

✅ Class - 2

Industry Project - 4 : Car Rental Batch Ingestion with SCD2 Merge in BigQuery Table
Industry Project - 5 : News Data Analysis with Event-Driven Incremental Load in BigQuery

✅ Class - 3

Few Exclusive Real Time Streaming Based Data Engineering Projects on GCP

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

Class Start Date:

26-April-2025

Mode of the Course:

Live

Course Duration:

50 Hours

Total Sessions:

Total Projects:

Class Timing:

Saturday & Sunday [9:00 AM - 12:00 PM Live Teaching, 12:00 PM to 1:00 PM Live Doubt Session] (IST)

Class Duration:

3 Hours Live Teaching, 60 minutes Doubt Solving

Course Validity:

1 year (Starting From Day Of Enrollment)

Programming Language Used:

Python

Prerequisite:

Basics of Python, SQL, Spark OR You Can Check 👉

Data Engineering & Python

⚠️ Important Notice :

The video may not work on Linux due to DRM restrictions. It is only accessible on Chrome when using Windows or macOS.

Workaround: To access the video on Linux, you can create a Windows virtual machine (VM) and watch the video through the VM. Alternatively, you can use our Android or iOS application to view the video on your mobile device.

Instructor

Shashank Mishra

Shashank Mishra is a seasoned Data Engineer with over 7 years of experience at top companies like Expedia, Amazon, PayTM, and McKinsey & Company. He specializes in Big Data, Cloud, and architecting scalable data pipelines across industries. A proud MCA graduate from NIT Allahabad, Shashank is passionate about sharing his expertise. Through his YouTube channel, E-Learning Bridge (177k+ subscribers), and LinkedIn (175k+ followers), he has mentored over 14,000 aspiring data professionals, helping them launch successful careers in Data Engineering.