The Data Engineering program at Praxis, in association with Genpact, Chubb and LatentView Analytics as Knowledge Partners, is designed to create job-ready data professionals.
The program equips students with the know-how of existing tools and technologies for Data Management and Data Modelling and introduces them to the paradigms of Distributed Systems and Cloud Computing. The participants get to work on a Capstone Project that requires them to migrate data to Big-Data platforms and manage the system on the Cloud.
The overarching objective of the program is to equip students with the tools and techniques that enable them to get their first job in the exciting domain of Data Engineering. The program has been designed to offer working professionals the opportunity to upskill themselves without giving up their existing assignments.
On successful completion of the course, students will learn how to:
Re-engineer Enterprise Data Architecture
Work with relational and NoSQL data models
Create scalable and efficient data warehouses
Work efficiently with massive datasets
Build and interact with a Cloud-based Data Warehouse
Automate and monitor data pipelines
Develop proficiency in Stream Processing using Cloud Data Lake
Solve appropriate use cases using Big Data technologies
The fastest growing tech career in the world
Data engineering is the process of transforming raw data into valuable information.
It’s a critical process for businesses that want to make data-driven decisions and is assuming importance with the generation of massive volumes of data in our daily lives.
Data engineers are professionals skilled in the collection, storing and parsing of data and utilizing machine learning to analyze the data.
Their job requires a critical understanding of both software development tools as well as business skills required to convert that data into valuable information.
Data Engineering has emerged as a top career choice in today’s data driven world. The supply demand gap in this rapidly growing sector is galloping, creating excellent opportunities for people with the right skills.
Data Engineering Market Size
1. Data Engineer: A data engineer lays down the foundation for data management systems to ingest, integrate and maintain all the data sources. The person has knowledge of databases and understands the needs of the business and its long-time data scalability needs. Tools: SQL, XML, Hive, Pig, Spark, etc.
2. Database Administrator: A database administrator has extensive knowledge of traditional as well as new-age NoSQL and Cloud databases and ensures that the data generating and the data ingesting systems are up and running in a live business scenario.
3. Enterprise Data Architect: The enterprise data architect is responsible for visualizing and designing an organization’s enterprise data management framework that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control and purge data. They have extensive knowledge of database tools, languages like Python, Java and Scala and distributed systems like Hadoop.
4. ETL Engineer: The ETL engineer is responsible for maintaining the veracity of the data in the source and target systems. They ensure that the right kind of tools, permission and system pipelines are in place for smooth transfer of the data.
300+ hours of intensive online learning
Program co-created with Genpact, LatentView Analytics and CHUBB
Exciting placement opportunities for all candidates
Membership to the Praxis Global Alumni Network
The 9-month program is divided into three trimesters of two-months each covering:
The pedagogy comprises design of a contemporary and relevant curriculum delivery which is a blend of classroom lectures, use case discussions and hands-on labs and assessment based on tests, assignments and projects.
for Big Data
Business on Cloud
|Trimester 1||Trimester 2||Trimester 3|
|Concepts of Data Warehousing and RDBMS||Big Data ecosystem and noSQL on Hadoop.||Enterprise Data Management on Cloud|
|Data Management with Python||Streaming Data Analytics with Spark & Kafka||Application Orchestration|
|Data Visualisation||Administer Data Pipelines and DevOps||Applied Machine Learning using MLOps|
|SQL Programming||Python Functional Programming||Data Security and Privacy|
|Exploratory Data Analysis||Introduction to Machine Learning||Capstone Project|
Capstone Project is a multifaceted assignment that serves as a culminating academic and intellectual experience for students. The Capstone Project gives students the opportunity to apply their classroom learnings to real-world challenges faced by business.
Some examples of capstone projects cloud be – Migration of a Traditional Data Warehouse to a Cloud Data Lake; Building an Orchestrated Application on the Cloud for managing Sensor-Data; Real-time Streaming Feeds Analysis and Visualization using a combination of Kafka, Storm and real-time Data Visualization tools.
The Praxis Placement Program is a structured process committed to creating quality placement opportunities for all enrolled students. It has had a consistently high placement record.
The placement team has tie-ups with prospective recruiters for the Data Engineering Program.
On an average, for every data scientist in the team, an organisation requires 4-5 data engineers. Thus, there are plenty of exciting jobs available if you have data engineering skills.
|Total Program Fees||₹ 3,54,000 (incl. GST)|
|Program Application Fee||₹ 500|
|Registration Fee||₹ 15,000|
|Balance Payment||₹ 3,39,000|
B. Tech, BCA/MCA or B. Sc. / M. Sc. Computer Science / IT
Minimum 50% or 5 GPA in 10th, 12th and Graduation
Who is this program meant for?
This course is aimed at facilitating a smooth transition of the participants into the domain of data engineering. It is meant for candidates satisfying any of the following criteria:
Candidates who have a technology background, are passionate about technology and are good at programming.
Fresh Graduates with engineering or computer science backgrounds who wish to be part of big data ecosystem.
People with work experience in the traditional technology areas who want to switch to new age 'hot' domains.
Step 1 :
For Online Application, Click Here
Step 2 :
Evaluation of Profile and Scores
Step 3 :
Personal Interview (Online)
Please note: When transferring the fee online towards the course fee the following payment gateway charges would need to be borne by the student:
|Credit Card Transactions||1.1 % + Taxes as applicable|
|Net Banking Transactions||Rs. 20/– + Taxes as applicable|
|Debit Card Transactions (above Rs. 2000)||1 % + Taxes as applicable|
|International Card Transactions||2.65 % + Taxes as applicable|
|AMEX||1.4 % + Taxes as applicable|
|Wallets (Money on Mobile/ MobiKwik /
Oxigen / Pay u Money /Citrus Money)
|1.95 % + Taxes as applicable|
|Cash Collection Centre||2 % + Taxes as applicable|