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Cloud Data Engineering Course with Placement

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Curriculum Designed & Delivered By Data Engineering & Data Science Experts from Amazon, Oracle, Boston Consulting Group, Google, McKinsey and Company, Accenture, etc.

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Are You Ready To Transform Your Career?

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Download the syllabus by filling the form.

Prepare For AWS & GCP Certifications

Professional Data Engineer

AWS Certified Big Data - Specialty

Cloud Data Engineering Certification Course with Placement

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Benefits For You

  • Get Industry Endorsed Certificate : Join the industry endorsed program by Ivy Pro School. A Unique Collaboration between academia and industry specifically focused on maximizing employability.
  • Join the Data Industry : Opportunity to work in one of the fastest growing and rewarding industries in the world.
  • Flexibility of learning from anywhere : Specialized learning program developed to be delivered live online. Give yourself freedom to attend from anywhere. All you need is a laptop and a good internet connection.
  • Work on Real-life Cases / Projects : Hands-on learning on real-life projects/case studies on Big Data Analytics and Data Engineering using Hadoop, Spark, Kafka, Hive and create Automated Data Pipeline using AWS.
  • Focus on Holistic development : We have an all round development approach where we equip you with skills such as CV building, LinkedIn Profile building, networking skills, Interview skills and other crucial job oriented skills.
  • Get AWS / GCP Certified - Prepare for AWS / GCP Certifications

Data Science Course Curriculum

1. SQL and Database Understanding

Understanding of transactional databases (MySQL, PostgreSQL), ACID properties , Basic DDL, DML, DCL
ER diagrams
Transaction, Concurrency Control
Indexing
Types of Keys, Join Operations, Group By, Case When Statements, Nested Queries
Triggers
Stored Procedures
Views and Materialized views
Window functions (Rank, Dense Rank, Row Number, Lag, Over Clause, Partition By, Sum, Avg, Min, Max, First_Value, Last_Value
Running Sum or Average Related Queries ( Row preceding, Unbounded)

2. Python

Basic Data Structures ( List, Tuple, Dictionary), Conditional operations, Looping, Functions, Lambda Functions, List Comprehension, Command line arguments
Regex
Pandas Library
Numpy Library (Moderate Level)
JSON, CSV, Datetime, Boto3, Requests Libraries
MySQL Connector
3. Big Data Terminologies
Technical understanding of Distributed Computation & Storage
Structured, Unstructured, Semi Structured Data
File Formats : CSV, JSON, Parquet, AVRO, ORC
Horizontal Vs Vertical Scaling
File Compressions Techniques
4. Data Warehousing
Facts
OLAPS
Dimensions
Star Schema
Snowflake Schema
Data Model Types
Data Integrity
Metadata
Slowly Changing Dimensions
Data Warehouse Design Questions (Ex - Design Amazon's Data Warehouse)
5. Hadoop
Complete Architecture
Map-Reduce Functioning
HDFS
YARN
Blocks, Splits, Maps, Data Spilling, Heartbeats, Data Replication, FS Image, Checkpointing, High availibility
Hadoop Daemons (Namenode, Datanode, Secondry Namenode, Standby Namenode)

6. Apache Hive
Hive Installation
Query Syntax
Bulk Data Load
Internal Vs External Tables
Static & Dynamic Partitioning
Bucketing
Map Side Join, Bucket Join and Sort Merge Bucket Join
Hive SerDe
UDF's in Hive
Query Optimization

7. MongoDB
Introduction to MongoDB and it's Architecture
Data Modeling with MongoDB - Schema design, Handling relationships between documents
Advanced MongoDB Features - Aggregation framework, Text Search, Geospatial queries
MongoDB Administration - Deploying and configure MongoDB in a production environment
Scaling MongoDB - Horizontal scaling with sharding, Building and Managing a distributed MongoDB cluster

8. Spark
Complete Architecture
Spark Core
RDDs
Spark SQL - Spark SQL data structures, Advanced data manipulation, Analyzing data
Building and optimizing Spark SQL applications
Spark Read/Write operations
Lineage Graph, Lazy Evaluation
Actions, Transformations, Optimized Joins, Brodcaster, Accumulator
Understanding of Spark UI, Stages, Tasks
Spark Submit Command Options
Job optimization techniques
Spark Catalyst Optimizer
Static and Dynamic Resource allocation
"Understanding Memory Usage in Spark
a) Cache & Persist
b) Java Serializer vs Kryo Serializer"
Spark Streaming
Integration with Spark SQL with Spark Streaming and GraphX

9. Kafka
Producer
Consumer
Kafka Cluster,Cluster Setup, Brokers
Topics, Partitioning, Offset, Polling, Data Replication, Data Retention
Consumer Group
ZooKeeper

10. Cloud Essentials & Fundamentals of AZURE
Azure Different Services (Iaas,Paas,Saas)
Azure Managed Identity and active directory management
Azure Network Security Group with different deployement models (Public, Private,Hybrid)
Microsoft Azure Key Vault
Azure Monitor with cost caluclator
Azure CLI Commands
Azure Virtual Machine

11. BigData in AZURE

Azure Blob/queue/table
Azure SQL database
Azure Data Lake gen 1 /gen 2
Azure Synapse analytics
Azure Cosmos DB
Azure Data Factory (Data Pipeline)
Azure Event Hubs
Azure Databricks (Data Processing)
Azure Scaling and Monitoring

Tailor Made Curriculum

Industry focused technical curriculum augmented with candidate focused soft skills enhancement programme.

1:1 Mentorship

Get taught and mentored by Elite Data Engineer Experts

Become a Target Hire!

Ivy Pro School focuses on your complete and holistic development so that you can become the "Target Hired"!

How Ivy Pro School Prepare You For Data Engineer Career

Build Job Ready Skills

Master essential skills of Big Data Analytics and Data Engineering using Hadoop, Spark, Kafka, Hive and create Automated Data Pipeline using AWS. With these Skills you can bag a job with top MNC's

Complete capstone real-life projects, including multiple industry-worthy capstone projects to showcase your skills to employers.

Capstone Projects

Make yourself hireable with personalized career coaching and 1:1 mentorship from industry experts

Launch your dream career

Cloud Data Engineering Certification Course

Module 1

Module 2

Module 3

Module 4

SQL for Data Engineering

Python Essentials for Data Engineering

Big Data Processing

Azure Cloud Engineering

ImageImage ImageImage

Building an E-commerce data Pipeline

Collecting and Processing Dairy Production sensor Data

Building an E-commerce data Pipeline

Collecting and Processing Dairy Production sensor Data

Building an E-commerce data Pipeline
Collecting and Processing Dairy Production sensor Data

IoT Device Managament for Smart home Ecosystem

Become a Pro in Industry Relevant Tools

The founder and Director of Ivy Professional School. He is ranked among Top 20 Data & Analytics Academicians (by Analytics India Magazine), a Data Consultant and a Serial Entrepreneur with 15+ years of global experience in data science consulting for 50+ world’s leading companies and coaching 7,000+ learners from 100+ leading organizations and elite colleges like IIT Kgp, IIM Kolkata, IIT Delhi, Presidency University, ISI, Jadavpur University, Madras School of Economics, etc. Worked with a Big 5 consulting firm in New York / Chicago / Washington DC / Houston.

Prateek Agrawal

Sreenivas Kalahasti

Lead Data Scientist , Big Data Engineer and MLOps Architect" with experience in Machine Learning, Artificial Intelligence,

Data Modelling, Analytics, Mining and Implementation of tens of enterprise level AI solutions that helped organization transform to data informed and AI enabled. Expert in Oracle, MySQL, Sybase, SQServer, HP-Vertica

Arpendu Ganguly

Arpendu is a Data Scientist and has 8+ years of experience in applying ML/DL algorithms and advanced econometric modelling techniques across diverse industrial sectors and multiple geographies to deliver data driven insights and incremental business value.

Our Mentors

Our Alumni Works At

Ivy Professional School in Action!

Be Certified By Ivy Professional School

Complete the Data Engineering course successfully to obtain this prestigious recognition from Ivy Professional School. Receive this accolade with the accomplishment of your course.

Share it with your friends, colleagues, seniors and potential employers. Open the gates of opportunities for that professional leap you have worked hard for.

Prepaid Payment

with Placement

Pay us full fees of Rs 90,000 + GST upfront

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Apply Now

Pay us full fees of Rs 55,000 + GST upfront

Prepaid Payment

without Placement

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Rs 90,000 + GST

Apply Now

Prepaid Payment with Placement Assistance

Rs 55,000 + GST

BEST OFFER

Prepaid Payment with Guaranteed Placement

Our offer

Payment Plans

Flexible payment option available

Flexible payment option available

How To Get Started?

STEP 1:

Fill in our simple application form. This is followed by a multistage assessment which is designed to assess your hunger, aptitude, learning ability and overall fit for our programme. Entry to this highly prestigious programme is highly competitive and is mainly based on your attitude towards learning and working rigorously.

If you progress past all the assessment rounds, you will get the opportunity to sign the ISA and join our ELITE programme. This 24 week programme aims to focus on your holistic development which includes providing you with the latest data analytics relevant skill sets ( SQL, PYTHON, etc.) as well as having your soft skills. ( Networking skills , interview skills , business communication skills)

STEP 2:

About halfway into the learning programme , we start referring you to top companies. We provide complete guidance and assistance with regard to the job application process and strive to ensure that our candidates are "Job Ready" in every possible aspect.

STEP 3:

Application and Assignment

Intense Learning Programme

Guaranteed Placement

What our students say about us?

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Testimonials

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The course and curriculum is very much industry oriented and covers straight from basic to advanced levels. The journey till now have been smooth and great owing to experienced faculty of the program. My doubt never goes unanswered in any class and what i especially liked about the faculty is how they make a person understand the concepts thoroughly.



Vani Agarwal

Ivy is undoubtedly one of the best Data Science Institutes when it comes to faculty and teaching. I've studied from a lot of teachers over the years but haven't seen more informed, dedicated and helpful faculty than of Ivy. The course structure is extremely well formulated with lots of opportunities for one to grow and explore themselves.

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Testimonials

Shreya Gupta

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Projects

In this video you will find our student Sambit Behera explain how to analyze key functionalities within the Dataset and develop a Machine Learning model using the key features to predict the Promotion of an Employee in an Organization using Python.


Also how to extract Business Insights using various Analysis and Plotting techniques (Grouped Bar Plot & Box Plot) to help the Organization take a better decision to Promote an efficient Employee.

Save Your Seat Now!

Reach-Out to us at info@ivyproschool.com or Call us at 7676882222.

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India's Top Cloud Data Engineering Course with Placement

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FAQ

1. Who should enroll in this course?

This course is ideal for aspiring data engineers, data analysts and scientists looking to enhance their technical skills, software engineers aiming to transition into data-focused roles, and anyone interested in building scalable data systems and pipelines.
2. What are the prerequisites for this course?
While not mandatory, it is beneficial to have basic programming knowledge in Python, Java, or Scala, an understanding of SQL, and familiarity with basic data structures and algorithms.

3. What tools and languages will I learn?
You will gain hands-on experience with programming languages such as Python and SQL, big data frameworks like Apache Hadoop and Apache Spark, ETL tools including Apache Airflow, cloud platforms such as Microsoft Azure (specifically Azure Data Factory), databases like MySQL and NoSQL (MongoDB), and data warehousing with Apache Hive.
4. How long is the course?
The course is designed to be completed in approximately 4 to 6 months, with flexibility to accommodate your pace of learning.
5. What practical projects will I undertake?

Throughout the course, you will work on real-world projects, including designing and implementing data pipelines, building data lakes and data warehouses, executing ETL processes, streaming data processing with Apache Kafka, and utilizing cloud services for scalable data solutions.

6. Do I need prior experience with cloud platforms?
No prior experience is needed. The course covers the use of popular cloud platforms (Azure) in detail.
7. How does this course differ from a Data Science course?
While Data Engineering focuses on the infrastructure and pipelines needed for processing data, Data Science involves analyzing this data to extract insights and build predictive models. This course emphasizes building scalable data systems.

8. Will there be hands-on assignments?

Absolutely! The course is heavily focused on practical learning through hands-on assignments, project work, and real-world datasets.

9. What certification will I receive upon completion?
You will receive a certification from Ivy Pro School, validating your proficiency in Data Engineering, which can be highlighted on your LinkedIn profile or resume.

10. Are there exams or assessments?

Yes, assessments will include quizzes, coding assignments, and project evaluations to ensure comprehension and practical application of concepts.

11. Can I take this course while working full-time?
Yes, the course is designed for working professionals, offering flexible deadlines and the ability to learn at your own pace.
12. What kind of support is available during the course?

You will have access to instructor-led sessions (both live and recorded), peer discussions and forums, mentorship from industry experts, and regular feedback on assignments and projects.

13. What career opportunities can I pursue after completing this course?
Upon completion, potential career paths include Data Engineer, Big Data Engineer, Cloud Data Engineer, Data Architect, and ETL Developer.
14. What is the expected salary range for a Data Engineer?
Salaries for data engineers in India typically range from ₹8,50,000 to ₹15,00,000 annually, depending on experience and geographic location.
15. Is a degree necessary to become a Data Engineer?
While a degree in computer science or a related field is beneficial, relevant experience and skills in programming and databases are often more crucial for securing a role in data engineering.