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Key Highlights

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Big Data Fundamentals

Introduction of Big Data

Linux Commands

HDFS Commands

SQOOP ARCH and HANDSON : How Import data from Target RDBMS TO HDFS | USecase1: With Primary Key and Without Primary Key | UseCase2: Boundary Query Without columns and With Columns | UseCase3: Incremenatl Load | Usecase4: How to Import all tables at a time |  Usecase5: How to Import all Tables with Exclude Tables | UseCase6: How to Create Sqoop Job |  UseCase7: How to Use $Conditions in Sqoop | UseCase8: How to Import data from RDBMS to HIVE TABLE | Usecase9: How to Process Semi Structured data using Sqoop | Usecase10: Sqoop Export from HDFS to RDBMS

Big Data Hadoop and Spark
HIVE ARCH AND HANDSON :Different Types OF Tables In Hive | PARTITIONING | Different Types Of Partitioning | Bucketing | How to Perform Both Partitioning and Bucketing using one table | Joins(Reducer Side Joins and MapSide Joins) | How to Semi Structured Data using Hive | Different File Format In Hive | How to perform Updates and Deletes in Hive | Hive Complex Types |Hive UDf HBASE ARCH AND HANDSON : Differnce Between Hive,SQL and HBASE | How to create tables,insert,update and delete | How to import data from rdbms to HBASE using Sqoop | How to Load CSV DATA INTO HBASE TABLE | HIVE to HBASE INTEGRATION PIG AND MAPREDUCE
SCALA: What Is Scala |  Differnce between JAVA and SCALA | SCala Variables | For,While and Do while Loop | Condiotional Statements | String,String Methods,String Interpolation | Functions |  Higher Order Functionss | Anonymous Functions | Closure Function | Currying Function | Collections(Array,set,tuple,map and list) | File Handling | Exception Handling | Traits
Spark vs Map Reduce |Architecture of Spark | Spark Shell introduction | Creating Spark Context | Spark Project with Maven in Eclipse | Cache and Persist in Spark | File Operations in Spark  
RDD: What is RDD | Transformations and Actions | Loading data through RDD | key-value pair RDD |Pair RDD oeprations | Running spark application with Spark-shell |Deploying Application With Spark-Submit  
Spark-SQL: Introduction to Spark SQL | Hive vs SparkSQL | Processing different fileformats using Spark SQL | Data Frames | DAG Lineage Graph | Cluster types | Optimizers | Structured Streaming | RDDs to Relations
Spark Streaming: Introduction to Spark Streaming | Architecture of spark Streaming | Spark Streaming vs Flume | Introduction to Kafka | Kafka Architecture | Spark Streaming integration with Kafka Overview |Real Time Examples
SQL Database

Introduction | RDBMS | Constraints | Normalisation | Syntax | Operators | Database querie | Table queries | Indexes | Handling | Duplicates | Indexes

Mongo DB

Introduction | Advantages | Environment | Data Modelling | Database | Collections | Documents | Records | Indexing | Aggregation | Replication | Sharding | Backup |Deployment

Amazon Web Services (AWS)
AWS basics, Cloud services and pricing | Overview of Datacenters, Datacenter components
Importance and need of servers, Compute power | AWS compute services Elastic Cloud Compute (EC2) | Virtual Private Cloud, Serverless framework
Storage Services S3, Relational Database Service | DynamoDB, Creating DynamoDB table | Launching of a MySQL database instance | Creating a CloudFront distribution
Identity & Access Management (IAM) | Security with IAM users, groups, and policies
Logging, auditing and resource management |Cloud watch, Cloud formation & AWS CLI
Business Analysis
Business Analyst – Who, What, Why? | BA – qualities, skills, roles, responsibilities | Fundamentals of Business Analysis | Hierarchical Structure of IT Team | IIBA, BABOK, CBAP, CCBA Overview | CMMI Overview | Project Stakeholder | Types of Stakeholder | Software Project and Types of Software Project | Software Contract and Types of Software Contract

Introduction of SDLC | Need of a BA in SDLC | Phases of SDLC | “SDLC Methods | Waterfall Model and Agile, Scrum |  Iterative and Incremental |V Model and Spiral Model” |”SDLC Pre-requisites and Activities | Common Criteria and Deliverables” | Software Maintenance lifecycle model |Software testing lifecycle model

Why do we need good Requirements | Why do Project Fail? | Importance of Requirement– Statistics | What is Requirements Engineering | Role of a Business Analyst

What are requirements? And Characteristics of Requirements | Types of Requirements |Business Requirements | User Requirements and System Requirements | Functional Requirements and Non-Functional Requirements Implementation Requirement and UI Requirements

Initial Exploration | Form Business Requirements | Provide Solution to satisfy BusinessRequirements | Create Functional Specifications/Use Cases | Validate Requirements with Customer | Form SRS and Seek Approval | Requirements Framework

Sources of Requirement Elicitation | Skills for Requirement Elicitation | Stakeholder Identification | Surveys and Questionnaire | Interviewing and Focus Group Interviews | Brainstorming and Reverse Engineering | Prototyping and Wire Frames | JAD – Joint Application Development | Observation and Task Analysis | Domain Analysis and Persona Challenges in Requirement Elicitation

Classifying and Prioritizing Requirements | Fish Bone Diagram – Causal Effect | Pareto’s Diagram – 80:20 Rule | Moscow Prioritization | Kano Analysis | Requirements Allocation and Validation | Requirements Pre-Review and Review | Requirements Walkthrough and Sign Off

How to write Business Requirement document? | How to write Software Requirement specification | Introduction to Software Requirement Specification | Understanding SRS syntax with IEEE Standards | What are Use Case and Use Case Narrative? | Relationship between Use Cases | How to write Use Cases? | Use Case Narrative Flows – Primary Flow Alternative Flow, | Exceptional Flow|Activity Diagram,Class Diagram, E-R Model, Sequence Diagram, State Diagram, Collaboration Diagram

Business Process of existing system | GAP Analysis – PIECES Framework | Domain Properties and Stakeholders | Feasibility Study | Evaluation of Alternatives using Cost –Benefits Analysis

Use case Description and Use Case Diagram | Activity Diagram | What are Use Case and Use Case Narrative? |Relationship between Use Cases | How to write Use Cases? | Use Case Narrative Flows – Primary Flow, Alternative Flow, Exceptional Flow | Pre-condition, Post-condition, Exception handling and Triggers

Sequence Diagram | Class Diagram | Software Requirement Specification

RTM – Requirements Traceability Matrix | Requirements Change Management |Requirements Risk Management | Impact Analysis

Different dimensions of scope | Managing Scope at different stages of the Project Product Scope and Project Scope | Issues in scope management | Measurement of
Scope and Metrics

Steps in Risk Management | Risk Identification | Risk Analysis and Prioritization Risk Response – Strategy, Actions & Response Owners | Risk Monitoring and Control | Risk Management Documents

Introduction to Estimation | The Importance of Estimation | What is Estimation? | The Estimation Process Overview | Problems with Estimations | Estimation Techniques

Importance of CEM | Traditional and modern view | Understanding Customer and Managing Expectations | Issues in Customer Expectation Management | Handling
Dicult Situations | Expectation Management Life-Cycle

Quality Management System | Concept of Quality | Metrics and Measurements | Defect Prevention | Defect analysis tools and techniques

Communication: Introduction | Email Communication | Teleconference and Meetings | Assertiveness and Scenarios

Understanding IT project hierarchy | Project Charter and Requirements Process | RACI Matrix and Requirements Planning | Work Efforts & Estimations | Managing Requirements BA’s plan to feed into Project Plan

Define Prototyping and Importance of prototyping | Types of Prototyping | Prototyping as methodology | User Interface Prototyping |Advantage and Disadvantages of Prototyping

Business Requirement Document (BRD) | Use case document (USD) | Software Requirement Specification Document (SRS) | Change Request Process Document | Functional Requirement Specification (FSD) | Business Process Questionnaire Document Project Requirement Management and development process Document | Scope management Document | Requirement Traceability matrix document

Use Case Diagram and Class Diagram | Sequence Diagram and Collaboration Diagram |Activity Diagram and State Diagram

Rational Requisite Pro | Microsoft Visio – UML Tool | Team Foundation Server (TFS) |JIRA – Agile Tool | SVN – Configuration Management Tool | Axure – Prototype Tool

The Product Backlog Creation | High-level Project and Process Plan | Sprint Planning Meeting | The Sprint and Daily Scrum Meetings | Sprint Review Meeting | Sprint Retrospective | Next Sprint and Repeat | Post-Sprint Functional Testing by PO | PrereleaseTesting prior to Release to Customer | Release to Customer

Requirement Development Process – For New Development Project | Requirement Management Process – For Maintenance Project | Change Request (CR) Process

What is Project Management? | Project Management Phases | Project Management Knowledge Areas | Project Management Tools

BABOK Introduction | BABOK Knowledge Areas | Business Analysis Planning | Enterprise Analysis | Requirement Elicitation | Requirement Analysis | Solution Assessment and Validation | Requirement Management and Communication

Agile Perspectives | Business Intelligence Perspectives | Information Technology Perspectives | Business Architecture Perspectives | Business Process Management

Data Analytics

Data Analytics across Domains | What is Analytics? | Types of Analytics | AI vs ML vs DL vs DS

Introduction to statistics and Central Limit Theorem | Measures of Central Tendancies and Measures of Spread | Descriptive Statistics with Real Time Examples | Measuring Scales | Inferential Statistics with Real Time Examples

Hypothesis Testing and Goodness of Fit test | Introduction to Statistical Tests | Statistical Test with Real Time Example | Analysis of Variance(ANOVA) & Analysis of Covariance (ANCOVA) | Probability Theory for Data Analytics | Types of Probability Distribution

Data Science with Python

Python Intro,IDE and Python Packages | Python Programming | Python Data Types – Dictionary, List and Set

Numpy Packages – Array Handling and Manupulation | Pandas Packages – Dataframe and Loading Excel, CSV File | Matplotlib Packages – Line graph and Visualisation

Histogram, Scatter Diagram, Box Plot and Bar Graph, Area Chart, Dual Axis, Array reshaping, reverse matrix, analysis

Python – Operators and String Manupulation | Control Structures(IF,IF-ELSE,IF-ELIF-ELSE, WHILE & FOR LOOP)

Python – Data Preparation Process | Python – Functions WITH and WITHOUT arguments Python – File Processing and Data Collection Methods

Python – Time Series Analysis and Forcasting | Python – Simple Predictive Analysis

Data Science with Python | Data Science Application across Multiple Domain and Business Function | Data Science Project LifeCycle

Multiple Predictive Model using Python | Python – Simple and Multiple Predictive Model in Practical | Python Correlation Analysis | Python Classifcation Model Building

Data Science – Experimental Design Analysis | Classifcation Technique – Discriminant Analysis | Data Science – Association Rule – Apriori Algorithm | Data Science – Building Recommendation System – (Market Basket Analysis)

Data Architecture Design, Data Warehousing and it’s Schema Design |Image Processing and Image Extraction | Image Processing and Object Recognition | Summarisation of Data Science Algorithm (Data Science Process)

Machine Learning

Machine Learning Introduction

Linear Regression | Logistics Regression | ANOVA and ANCOVA | Linear Discriminant Analysis

Naïve Bayes | K-Nearest Neighbour | SVM- Support Vector Machine | -Decision Tree and Random Forest

Factor Analysis | Cluster Analysis | Association Rule | Correlation

Time Series Analysis

Deep Learning

Deep Learning Fundamentals
Working of Neural Networks
Gradient Descent and Back Propagation
Activation Function

Tensorflow Introduction

Building Artificial Neural Networks (ANN)
Deep Learning-ANN-classification

intro to CNN

Introduction to RNN & Sequence prediction using RNN

Introduction to LSTM,
Sequence prediction using LSTM
Applications in text analytics , stock prediction , time series data

Natural Language Processing

Basics of NLP
Removing Stop Words
Stemming & lemmatization
Parts of speech tagging
TFIDF vectorizer
Senmiment Analysis

Text Classification with Linear Models
Language Modelling with Probabilistic Graphical Models and Neural Networks
Word Embeddings and Topic Models
Machine Translation and Sequence-To-Sequence Models

Data Visualization using Tableau

Tableau introduction
Different types of visualization using Tableau
Tableau Dashboard Creation
Tableau Story line creation
Time series using Tableau
Different types of Joins Using Tableau
Tableau Features – Filters and format the Column
Real time project using Tableau
Tableau Highlighter
Data Blending using Tableau
Table Calculation using Tableau
Parameters and Set using Tableau
Advanced Data Preparation using Tableau
Hierarchical clustering using Tableau
Complete Course Revision using Tableau

Power BI

Power BI Services | Advantages of Visual analytics 

Installation Process of Power BI Desktop and Getting Familiar with Interface

Filters | Splitting Columns | Groups| Merging | Conditional Columns 

Cardinality | Cross Filters | DAX Functions

Different Types of Visual Features | Drill Down | Formatting Visuals 

How to Export Desktop Reports to Cloud Service and Explore my Workspace, Sharing with Others.


Capstone Projects

Capstone Projects

Data Analytics

Bank Loan Modeling solution execution

Data Analytics

Application of Machine Learning Algorithm in Attrition Project and its analysis

Machine Learning

Attribution analysis solution execution

Machine Learning

Bank Loan Modelling and its analysis

Machine Learning

Application of Machine Learning Algorithm in Bank Loan Modelling

Machine Learning

Merger and Acquisitions analytics

Machine Learning

LKP Project using Python

Machine Learning

Recommendation of new model

Artificial Intelligence

Telecom Churm case study using Sklearn

Artificial Intelligence

Recommendation Engine

Artificial Intelligence

Sentiment Analyser

Artificial Intelligence

Building Chatbot

Artificial Intelligence

Twitter Sentiment Analyser

Business Analysis

Online Recruitment Process

Data Visualization Tableau

Customer Loyalty Analytics and its Application

Data Visualization Tableau

Attrition Analysis and Bank Loan Modelling

Data Science using R

Solution- HR Analytics Attrition Analysis

Data Science using R

Merger and Acquisition


On completion of the Master Program in Big Data Engineering, aspirants will receive an Industry-endorsed Certificate along with additional certificates.




B.Tech and MBA ( Finance & Operation ), Ph.D in Data Analysis.


Management LDP Program, B. Tech./B.E. (Electronics & Telecommunication)



M.Tech (power electronics), MBA-HR, PhD in power quality improvement


M.B.A(Marketing & Finance )

Program Fees

LUMPSUM Fees - Rs. 55,000 + GST 18% applicable

INSTALLMENT Fees - Rs. 60,000 + GST 18% applicable

Regsitration Amount EMI 1 EMI 2 EMI 3 EMI 4+ Exam fees EMI 5+ GST 18%
10,000 15,000 15,000 15,000 5,000+6,000 10,800
  • Exam Fees of 6,000/- applicable for complete course.
  • EMI has to be paid every month. If not paid, fine of 500/- Rs. is applicable.

Our Faculty

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Dinesh Babu R

UrbanPro Excellence Award winner in Data Science Professional
CBAP Certified Professional
Senior Business Analyst in the MNC, Part time, Providing Business Analysis as well as Data Analysis training to both Indian as well as overseas students.
Qualification: P.hd in Data Analysis, MBA (Finance & Operation), B.Tech

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Ganesh Bhure (Management LDP Program, B.Tech/B.E. (Electronics and Telecommunication))

11yrs into training. Working on various training assignments onPython, Machine Learning, Data Analytics, Artificial Intelligence, Docker and Kubernetes, Leadership and Product Management.

Software professional with 16+yrs of experience. Handled innovation strategic roles, Technical Consultant, Technical Manager, Project Lead, Product Development, Project Management, BusinessAnalysis, Technical Design, Python, C, C++, Docker, Kubernetes, Scale Testing, Product Benchmarking, Data Analytics, Machine Learning, Artificial Intelligence, Data Science.

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Suryanarayana Murthy (MCA, B.Sc (Electronics))

9.5 Years IT Experience in Big Data Hadoop and PERL as a Developer.
5.5 Years of comprehensive experience as Big Data Developer, Practical exposure and strong knowledge in Big Data management

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Boddu Lingaiah (M.Tech (CS), B.Tech (CS))

5+ Year teaching experience in Full Stack Web Development.

Boddu Lingaiah has over 10+ Years of experience as Master Trainer at Edunet Foundation & worked as IT Faculty at KL University and Jain University.
Studied M.Tech at SKEC Karepalli as well as worked as Assistant Professior for 1.3 Year.

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Abhishek Srivastava (M.Tech (CS), MCA)

IIT Kanpur Certified Data Science Trainer
Teaching experience in Data science, Machine Learning, Deep Learning, Artificial Intelligence
Data Science Trainer with 5+ Years of experience executing Data Driven solution to increase effeciency, accuracy and utility of internal data processing. Experinced to give training on regression models, using predective data modeling and analysing Data scienceAlgorithm to deliver insights and implement action- oriented to business problems.


  • Introduction to Linux
  • Root
  • Basic commands
  • Editors
  • OS installation
  • Basic system configuration and administration
  • Understanding files and directories
  • Schedulers
  • User administration
  • Software installation