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Industry  Speak

Mr. Ramesh Hariharan

In the emerging era, AI will simplify any decision-making. Engineering the right type of data platforms would be a key differentiator! Leading scalable data engineering initiatives will be critical for successful analytics transformation. Praxis is best positioned to offer the best of both worlds (data science & data engineering) and provide the right curriculum to be future ready!

Mr. Ramesh Hariharan

Co-founder and Director
Data Engineering

latentview

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Mr.Sidharth Reddy

At Genpact, our work with leading enterprises around the world, has taught us that laying a good data foundation requires a few key components, and talent is one of the most critical factors. Through this partnership, we aim at nurturing a new generation of students who can apply their theoretical knowledge on data engineering, big data management, data governance, data cognition engines and more, to solve real world business challenges.

Mr.Sidharth Reddy

Vice President & Global Head of Data
Advanced Analytics delivery for banking and capital markets

genpact

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Dr. Sourav Saha

The digital era has created a new benchmark for successful Organization whose reputation today is determined not only on revenue but also on the amount of Data they handle and process. This is where the Data Engineers take the centre stage with the knowledge of the Cloud Computing platforms, tools and techniques for ensuring the assimilation, storage and processing of Big Data. Today, as the human civilization prepares at creating unprecedented value through Artificial Intelligence (AI), the Data Engineers ensure the continuous fuel for AI, i.e. Data. I am excited at the career potential of the Data Engineering graduates coming out of the program and look forward to seeing them contributing to a better future for everyone.

Dr. Sourav Saha

Dean Academics

Praxis

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9-month post graduate program with online/ in class learning options
Weekend only Part-time program – learn without quitting your job
Knowledge partners
partners

Exciting campus placement opportunities

Data Engineering – The fastest growing tech career in the world

Who are Data Engineers?

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 becoming more important with the advent and availability of data in our daily lives.

Data engineers are professionals skilled in the collection of data, storing it, parsing it for patterns & insights, 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.

Why should you aspire for a career in Data Engineering?
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:

India

$10.6 billion to grow 4 times to $42.3 billion by 2025

Global

$29 billion to grow to $106 billion by 2025

India

will account for 41% of the Global DE market by 2025

What are the different roles and profiles in Data Engineering?

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.

Data science

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.

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.

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. She has extensive knowledge of database tools, languages like Python, Java and Scala, and distributed systems like Hadoop.

Program Objective

The Data Engineering program at Praxis, in association with Genpact and Latentview Analytics as Knowledge Partners, is designed to create professionals who become immediately productive for the organization. The program equips professionals 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. We want to give this opportunity to both those executives who are engaged in their careers and do not want to give up their existing assignments, and those who would like to attend physical classes and reap the benefits of a campus environment. This is why this program is available in a dual-learning mode.

Learning Outcomes
On successful completion of the course, the 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 the appropriate use cases using Big Data technologies

Program Highlights

IT Risk and Security Strategy
300+ hours of immersive learning with In-class/online learning options
IT Risk and Security Strategy

Program co-created with Genpact and LatentView Analytics

IT Risk and Security Strategy
Expert faculty pool of academicians and industry practitioners
IT Risk and Security Strategy
Exciting Campus Placement Opportunities
IT Risk and Security Strategy
Membership to the Praxis Global Alumni Network
IT Risk and Security Strategy
Migrating and managing a Business System on the Cloud
  • Program Coverage
  • Placements
  • Fees and Scholarship
  • Eligibility
  • Selection Process
  • Online Fee Payment
The 9 months program is divided into three trimesters of two-months each covering

  • Working with traditional data
  • Engineering platforms for big data and
  • Running enterprise business on cloud

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.

Topics Covered
Working with Traditional Data Engineering Platforms for Big Data Running Enterprise Business on Cloud
Trimester 1 Trimester 2 Trimester 3
Concepts of Data Warehousing and RDBMS Data Security and Privacy Understanding Enterprise Business data generation
Algorithms and Data Structures Big Data ecosystem and NoSQL on Hadoop - MongoDB and Cassandra Application orchestration - Dockers & Kubernets
Python functional programming Streaming Data Analytics with Spark Cloud Data Lake using AWS and Azure for Enterprise Data Management
SQL programming Applied Machine Learning using MLOPs Data Visualization
Data Modeling & ETL  Administer Data Pipelines using Apache Airflow, Kafka and Storm Capstone Project
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 could 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.

PGDM is a 2 year full time program aimed at combining the art and science of theoretical learning with the virtues of practical training. 

In order to ensure academic excellence, Praxis sought inputs from XLRI in its initial years. The program at Praxis is, on the one hand, rooted in the principles of academic rigor and discipline, and, on the other, designed to offer multiple touch-points with the industry. 

In response to the changing demand of the industry, and in order to train the students to take up industry-specific roles, Praxis has reorganized its curriculum to target four industry verticals. In addition to opting for one or more specializations, students are given the option of choosing an industry vertical as an area of concentration in the following verticals:

Core Courses
Data science
Data Science
Data science
Data Science
Data science

Consumer Insights and Market Intelligence
Data science

Commercial Banking and Project Finance
Data science
Data Science
Data science
Data Science
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Analytics
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Finance
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Human Resource management
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence
Data science

Commercial Banking and Project Finance
Data science

Consumer Insights and Market Intelligence
Data science

Consumer Insights and Market Intelligence

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  • eligibilityB.Tech, BCA/MCA or B. Sc/M. Sc Computer Science /IT
  • eligibilityMinimum 50% or 5 GPA in 10th, 12th and Graduation
Whom 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
  • eligibility

    Candidates who have a technology background, are passionate about technology and are good at programming

  • eligibility

    Fresh graduates with engineering or computer science backgrounds who wish to be part of the big data ecosystem

  • eligibility

    People with work experience in the traditional technology areas who want to switch to new age ‘hot’ domains

step 1

Step 1 : Online Application at
Click Here
step 1

Step 2 : Evaluation of Profile and Scores

step 1

Step 3 : Personal Interview
(online)

The Praxis Placement Program is a structured process committed to creating quality placement opportunities for all enrolled students. It has had a consistently 90% + placement record for its data science program and the placement team has already tied-up 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.

Past Recruiters at Praxis in Data Science
Axis Bank Bridgei2i Analytics Solutions Colgate-Palmolive
Citi Bank DBS eClerx
E&Y Fractal Analytics Genpact
Happiest Minds Consulting Hexaware Technologies   HSBC Analytics
ICICI Bank IDFC First Bank    Infosys
Kantar Group Kotak Mahindra Bank Landmark Group
Latentview Analytics L&T Financial Services Mahindra and Mahindra
Mindtree Nielsen NPCI
Oppo PwC   Pepsico
Tata Capital Tata Consultancy Services Tata IQ
Tata Steel BSL LtD Vedanta Wipro
  • Fees
  • Praxis Scholarships

All figures in Indian National Rupees INR

Academic Fee Course Material Refundable Deposit Installment
Admission Confirmation 25000 25,000
First Installment 77500 10000 10,000 97500
Second Installment 77500 10000 87500
Total 180000 20000 10,000 2,10,000

Please note:

*Academic Fee includes Tuition, Library and Academic activity fee.

Refunds: After admission the entire amount paid by the student shall stand forfeited except the refundable deposit mentioned above. This applies to dismissals as well as withdrawals, voluntary or otherwise, from the institute’s rolls.

Laptop: Each student must have a wi-fi enabled personal laptop before the start of classes. For the data engineering program, the laptop has to be a 64 bit machine and should be equipped with a minimum of 8 GB RAM.

Educational Loans: Praxis has tied up with Credila and Avanse Financial Services for student loans, details of which would be furnished on selection.

Disputes: Any disputes are subject to the jurisdiction of Kolkata courts only

Praxis WiT (Women in Tech) Scholarships is an initiative to encourage and support greater women’s participation in tech and data careers. This is in line with our belief that gender diversity in the workforce, especially in tech, brings immense value to the organization, the economy, and society.

The Praxis Women in Tech (WiT) Scholarship will be awarded to all selected women aspirants applying for the Praxis PG Program in Data Engineering

Why Women in Tech:

  • Digital is largely about tech and data and people proficient in tech and data are poised to play leadership roles in shaping our world
  • Women are acutely under-represented in the fields of tech and data, despite global conversations on gender diversity in the workforce
  • The world needs more tech and data talent and women can fill this gap and drive sustainable careers and financial independence
  • Decades of research suggests that diversity leads to enhanced innovation and problem solving and more women in tech implies better solutions to global problems.

Eligibility: All selected women candidates for the Post Graduate Program in Data Engineering

Scholarship Amount: INR 1 lac. Applicable PGPDE Course fee for Women-in-Tech will be INR 1 Lac

Get inspired by the Women in Tech Praxites
  • Sakshi Singh

    Sakshi Singh

    Associate JP Morgan Chase & co. Class of 2017

  • NEHA NEHRA

    NEHA NEHRA

    Senior Business Analyst
    GEP Worldwide, Prague
    Class of 2016

  • MOUMITA GHOSH

    MOUMITA GHOSH

    Deputy Manager – Data Science
    ICICI Bank
    Class of 2020

Please note

1.For transferring the fee online towards the course fee, the following payment gateway charges would need to be borne by the student:

Details Charges
Credit Cards Transactions 1.1% + Taxes as applicable
Net Banking Transactions Rs 20/- + Taxes as applicable
Debit Cards Transaction (above Rs. 2000/-) 1.0 % + Taxes as applicable
International Cards 2.65 % + Taxes as applicable
Amex 1.40 % + Taxes as applicable
Wallets (Money on Mobile/ MobiKwik / Oxigen / Pay u Money /Citrus Money) 1.95 % + Taxes as applicable
Cash Collection Centre 2.00 % + Taxes as applicable
UPI Rs18
2.You would be re-diverted to a payment gateway by Schoolpay
3.Fees are paid into the ‘Praxis Business School Foundation’ bank account.
Click here to pay the fees