CERTIFIED DATA ENGINEER CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ENGINEER LEAD MENTORS

DATA ENGINEER COURSE FEES IN ALLAHABAD

Live Virtual

Instructor Led Live Online

110,000
63,945

  • IABAC® & JAINx® Certification
  • 6-Month | 150+ Learning Hours
  • 50+Hour Live Online Training
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

55,000
36,645

  • IABAC® & JAINx® Certification
  • One year access to Self Learning
  • 10 Capstone Projects
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Classroom

In - Person Classroom Training

110,000
69,195

  • IABAC® & JAINx® Certification
  • 6-Month | 150+ Learning Hours
  • 50+Hour Classroom Training
  • 10 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

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UPCOMING DATA ENGINEER ONLINE CLASSES IN ALLAHABAD

BEST CERTIFIED DATA ENGINEER CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR DATA ENGINEER COURSE

Why DataMites Infographic

SYLLABUS OF DATA ENGINEER CERTIFICATION IN ALLAHABAD

MODULE 1: DATA ENGINEERING INTRODUCTION

• What is Data Engineering?
• Data Engineering scope
• Data Ecosystem, Tools and platforms
• Core concepts of Data engineering

MODULE 2: DATA SOURCES AND DATA IMPORT

• Types of data sources
• Databases: SQL and Document DBs
• Connecting to various data sources
• Importing data with SQL
• Managing Big data

MODULE 3: DATA PROCESSING

• Python NumPy Package Introduction
• Array data structure, Operations
• Python Pandas package introduction
• Data wrangling with Pandas
• Managing large data sets with Pandas
• Data structures: Series and DataFrame
• Importing data into Pandas DataFrame
• Data processing with Pandas

MODULE 4: DATA ENGINEERING PROJECT

• Setting Project Environment
• Data Ingestion through Pandas methods
• Hands-on: Ingestion, Transform Data and Load data

MODULE 1: PYTHON BASICS

• Introduction of python
• Installation of Python and IDE
• Python objects
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
• Operator’s precedence and associativity

MODULE 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• String object basics and inbuilt methods
• List: Object, methods, comprehensions
• Tuple: Object, methods, comprehensions
• Sets: Object, methods, comprehensions
• Dictionary: Object, methods, comprehensions

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Iterators
• Generator functions
• Lambda functions
• Map, reduce, filter functions

MODULE 5: PYTHON NUMPY PACKAGE

• NumPy Introduction
• Array – Data Structure
• Core Numpy functions
• Matrix Operations

MODULE 6: PYTHON PANDAS PACKAGE

• Pandas functions
• Data Frame and Series – Data Structure
• Data munging with Pandas
• Imputation and outlier analysis

MODULE 1 : OVERVIEW OF STATISTICS 

  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's  Minimum Sample Size
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Biased Random Sampling Methods
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Confidence Interval
  • Parametric Hypothesis Testing Methods
  • Hypothesis Testing Errors : Type I And Type Ii
  • One Sample T-test
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test

MODULE 5 : CORRELATION AND REGRESSION 

  • Correlation Introduction
  • Direct/Positive Correlation
  • Indirect/Negative Correlation
  • Regression
  • Choosing Right Method

MODULE 1: DATA ENGINEERING INTRODUCTION

• What is Data Engineering?
• Data Engineering scope
• Data Ecosystem, Tools, and platforms
• Core concepts of Data engineering

MODULE 2: DATA WAREHOUSE FOUNDATION

• Data Warehouse Introduction
• Database vs Data Warehouse
• Data Warehouse Architecture
• ETL (Extract, Transform, and Load)
• ETL vs ELT
• Star Schema and Snowflake Schema
• Data Mart Concepts
• Data Warehouse vs Data Mart — Know the Difference
• Data Lake Introduction
• Data Lake Architecture
• Data Warehouse vs Data Lake

MODULE 3: DATA SOURCES AND DATA IMPORT

• Types of data sources
• Databases: SQL and Document DBs
• Connecting to various data sources
• Importing data with SQL
• Managing Big data

MODULE 4: DATA PROCESSING

• Python NumPy Package Introduction
• Array data structure, Operations
• Python Pandas package introduction
• Data structures: Series and DataFrame
• Importing data into Pandas DataFrame
• Data processing with Pandas

MODULE 5: DOCKER AND KUBERNETES FOUNDATION

• Docker Introduction
• Docker Vs. regular VM
• Hands-on: Running our first container
• Common commands (Running, editing, stopping, and managing images)
• Publishing containers to DockerHub
• Kubernetes Orchestration of Containers
• Build Docker on Kubernetes Cluster

MODULE 6: DATA ORCHESTRATION WITH APACHE AIRFLOW

• Data Orchestration Overview
• Apache Airflow Introduction
• Airflow Architecture
• Setting up Airflow
• TAG and DAG
• Creating Airflow Workflow
• Airflow Modular Structure
• Executing Airflow

MODULE 7: DATA ENGINEERING PROJECT

• Setting Project Environment
• Data pipeline setup
• Hands-on: build scalable data pipelines

MODULE 1 : AWS DATA SERVICES INTRODUCTION 

  • AWS Overview and Account Setup
  • AWS IAM Users, Roles and Policies
  • AWS Lamdba overview
  • AWS Glue overview
  • AWS Kinesis overview
  • AWS Dynamodb overview
  • AWS Anthena overview
  • AWS Redshift overview

MODULE 2 : DATA INGESTION USING AWS LAMDBA 

  • Setup AWS Lamdba  local development env
  • Deploy project to Lamdba console
  • Data pipeline setup with Lamdba
  • Validating data files incrementally
  • Deploying Lamdba function

MODULE 3 : DATA PIPELINE WITH AWS KINESIS 

  • AWS Kinesis overview and setup
  • Data Streams with AWS Kinesis
  • Data Ingesting from AWS S3 using AWS Kinesis

MODULE 4 : DATA WAREHOUSE WITH AWS REDSHIFT 

  • AWS Redshift Overview
  • Analyze data using AWS Redshift from warehouses, data lakes and operations DBs
  • Develop Applications using AWS Redshift cluster
  • AWS Redshift federated Queries and Spectrum

MODULE 5 : DATA PIPELINE WITH AZURE SYNAPSE 

  • Azure Synapse setup
  • Understanding Data control flow with ADF
  • Data Pipelines with Azure Synapse
  • Prepare and transform data with Azure Synapse Analytics

MODULE 6 : STORAGE IN AZURE 

  • Create Azure storage account
  • Connect App to Azure Storage
  • Azure Blog Storage

MODULE 7: AZURE DATA FACTORY

  • Azure Data Factory Introduction
  • Data transformation with Data Factory
  • Data Wrangling with Data Factory

MODULE 8 : DATA ENG PROJECT WITH AZURE/AWS

  • Hands-on Project Case-study
  • Setup Project Development Env
  • Organization of Data Sources
  • AZURE/AWS services for Data Ingestion
  • Data Extraction Transformation  

MODULE 1: DATA WAREHOUSE FOUNDATION

• Data Warehouse Introduction
• Database vs Data Warehouse
• Data Warehouse Architecture
• ETL (Extract, Transform, and Load)
• ETL vs ELT
• Star Schema and Snowflake Schema
• Data Mart Concepts
• Data Warehouse vs Data Mart — Know the Difference
• Data Lake Introduction
• Data Lake Architecture
• Data Warehouse vs Data Lake

MODULE 2: DOCKER FOUNDATION

• Docker Introduction
• Docker Vs. regular VM
• Hands-on: Running our first container
• Common commands (Running, editing, stopping and managing images)
• Publishing containers to Docker Hub
• Kubernetes Orchestration of Containers
• Build Docker on Kubernetes Cluster

MODULE 3: KUBERNETES CONTAINER ORCHESTRATION

• Kubernetes Introduction
• Setting up Kubernetes Clusters
• Kubernetes Orchestration of Containers
• Build Docker on Kubernetes Cluster

MODULE 4: DATA ORCHESTRATION WITH APACHE AIRFLOW

• Data Orchestration Overview
• Apache Airflow Introduction
• Airflow Architecture
• Setting up Airflow
• TAG and DAG
• Creating Airflow Workflow
• Airflow Modular Structure
• Executing Airflow

MODULE 5: DATA ENGINEERING PROJECT

• Setting Project Environment
• Data pipeline setup
• Hands-on: build scalable data pipelines

MODULE 1 : DATABASE INTRODUCTION 

  • DATABASE Overview
  • Key concepts of database management
  • CRUD Operations
  • Relational Database Management System
  • RDBMS vs No-SQL (Document DB)

MODULE 2 : SQL BASICS 

  • Introduction to Databases
  • Introduction to SQL
  • SQL Commands
  • MY SQL  workbench installation
  • Comments
  • import and export dataset

MODULE 3 : DATA TYPES AND CONSTRAINTS 

  • Numeric, Character, date time data type
  • Primary key, Foreign key, Not null
  • Unique, Check, default, Auto increment

MODULE 4 : DATABASES AND TABLES (MySQL) 

  • Create database
  • Delete database
  • Show and use databases
  • Create table, Rename table
  • Delete table, Delete  table records
  • Create new table from existing data types
  • Insert into, Update records
  • Alter table

MODULE 5 : SQL JOINS 

  • Inner join
  • Outer join
  • Left join
  • Right join
  • Cross join
  • Self join

MODULE 6 : SQL COMMANDS AND CLAUSES 

  • Select, Select distinct
  • Aliases, Where clause
  • Relational operators, Logical
  • Between, Order by, In
  • Like, Limit, null/not null, group by
  • Having, Sub queries

MODULE 7 : DOCUMENT DB/NO-SQL DB

  • Introduction of Document DB
  • Document DB vs SQL DB
  • Popular Document DBs
  • MongoDB basics
  • Data format and Key methods
  • MongoDB data management

MODULE 1: BIG DATA INTRODUCTION

• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE

• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
• Hands-on Map Reduce task

MODULE 3: PYSPARK FOUNDATION

• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE

• Introducing Spark SQL
• Spark SQL vs Hadoop Hive
• Working with Spark SQL Query Language

MODULE 5: MACHINE LEARNING WITH SPARK ML

• Introduction to MLlib Various ML algorithms supported by Mlib
• ML model with Spark ML.
• Linear regression
• logistic regression
• Random forest

MODULE 6: KAFKA and Spark

• Kafka architecture
• Kafka workflow
• Configuring Kafka cluster
• Operations

DATA ENGINEER TRAINING COURSE REVIEWS

ABOUT DATAMITES DATA ENGINEER TRAINING IN ALLAHABAD

The global data engineering market is on a remarkable growth trajectory, projected to reach an impressive value of USD 112.68 billion by 2023, with a phenomenal CAGR of 19.39%. This surge is fueled by the increasing need for robust data infrastructure and advanced analytics capabilities. As organizations strive to unlock the full potential of their data, data engineers play a crucial role in designing, building, and optimizing data pipelines and systems. With such exponential growth, data engineering offers exciting career prospects and opportunities for professionals seeking to make their mark in the data-driven world. 

Unlock the potential of data engineering with DataMites' Data Engineer Course in Allahabad. This extensive program spans over 6 months, comprising 150+ learning hours. Engage in 50+ hours of live online training led by industry experts, gaining valuable insights in real-time. Dive into 10 capstone projects and a client project to apply your knowledge to practical scenarios. Enjoy the flexibility of a 365-day Flexi Pass and access to Cloud Lab for continuous learning. DataMites also offers offline courses on demand for learners seeking in-person training in Allahabad.

10 Reasons to Choose DataMites for Data Engineer Training in Allahabad:

  • Guidance of Ashok Veda and Expert Faculty: Learn from Ashok Veda and a team of experienced faculty members renowned in the field of data engineering.

  • Comprehensive Course Curriculum: Gain comprehensive knowledge through a well-structured curriculum covering all aspects of data engineering.

  • Global Certification: Earn globally recognized certifications from IABAC, NASSCOM FutureSkills Prime, and JainX, bolstering your professional profile.

  • Flexible Learning Options: Choose between online data engineer training in Allahabad and ON DEMAND data engineer offline training in Allahabad to align with your schedule and learning preferences.

  • Real-world Projects: Work on projects using real-world data to acquire practical skills and industry experience.

  • Internship Opportunities: Avail of internship opportunities to gain hands-on exposure and practical insights.

  • Placement Assistance and Job References: Receive dedicated support for job placements and valuable job references.

  • Hardcopy Learning Materials and Books: Access high-quality hardcopy learning materials and books for a comprehensive learning experience.

  • DataMites Exclusive Learning Community: Engage with a vibrant learning community, interact with peers, and expand your professional network. 

  • Affordable Pricing and Scholarships: Explore affordable pricing options and scholarship opportunities to make the course accessible to all aspiring learners.

DataMites offers esteemed Data Engineer Certification in Allahabad, validating your expertise in data engineering. Allahabad, renowned for its historical significance and religious importance, fosters a rich cultural environment. The city's educational landscape and emerging IT sector offer promising opportunities for aspiring data engineers. Enroll in DataMites' Data Engineer course to explore the data-driven possibilities while immersing yourself in the vibrant atmosphere of Allahabad.

Along with the data engineer courses, DataMites also provides data analytics, data mining, data analyst, python training, mlops, AI expert, data science, deep learning, artificial intelligence, IoT, tableau, machine learning and r programming courses in Allahabad.

ABOUT DATA ENGINEER COURSE IN ALLAHABAD

Data engineering is the practice of designing, developing, and managing systems and processes that facilitate the efficient handling and analysis of large amounts of data. Its primary objectives include establishing reliable data pipelines, ensuring data quality and integrity, and enabling data-driven decision-making.

To pursue a career in data engineering in Allahabad, individuals should consider the following actions:

  • Build a strong knowledge base in mathematics, statistics, and programming.

  • Acquire proficiency in programming languages like Python or SQL.

  • Develop expertise in database management systems and data manipulation techniques.

  • Familiarize themselves with big data technologies like Hadoop and Spark.

  • Enhance their skills through hands-on projects and practical experience.

Enrolling in data engineer training provides numerous benefits, such as:

  • Acquiring sought-after skills and knowledge in the field of data engineering.

  • Improving job prospects across diverse industries.

  • Gaining practical experience through hands-on projects and real-world applications.

  • Staying updated with the latest industry trends and advancements.

Absolutely, data engineering has a bright future ahead. As organizations increasingly rely on data for decision-making and the volume of data continues to grow rapidly, the demand for proficient data engineers is projected to remain high. Data engineering is essential in efficiently managing and processing data to extract valuable insights and support business success.

To join a data engineer training in Allahabad, individuals typically need to meet certain qualifications, which can vary depending on the course and institution. Generally, having a basic understanding of mathematics, statistics, and programming is beneficial. Knowledge of databases, SQL, and programming languages such as Python or Java can also be advantageous.

The price range for data engineer training in Allahabad typically varies based on factors such as the institution, duration of the program, and mode of delivery (online or classroom). Generally, the fees can range from around 40,000 INR to 1,00,000 INR.

DataMites is highly renowned as an institute that provides exceptional data engineer training. Their offerings include a comprehensive curriculum, industry-relevant projects, and experienced instructors who equip students with the essential skills in data engineering.

Upon completing data engineer training, individuals can explore diverse career prospects, including roles such as Data Engineer, Database Administrator, ETL Developer, Big Data Engineer, and Cloud Data Engineer. These opportunities span across industries such as technology, finance, healthcare, and e-commerce.

Yes, it is possible for individuals with no prior experience to secure data engineer job positions. Entry-level roles or positions as junior data engineers are often available for individuals without extensive experience. Additionally, gaining practical experience through internships or projects can also provide opportunities to enter the field.

Data engineer training holds great significance as it equips individuals with the skills and knowledge needed to thrive in the field. It encompasses vital concepts, tools, and techniques essential for constructing data pipelines, managing databases, and ensuring effective data processing and analysis. This expertise is invaluable in today's data-driven landscape, where organizations heavily rely on data for decision-making and achieving business success.

FAQ’S OF DATA ENGINEER COURSE IN ALLAHABAD

To obtain data engineering training in Allahabad, individuals can follow the process of enrolling at DataMites. DataMites offers comprehensive courses that cover essential data engineering concepts, tools, and techniques. With a strong emphasis on hands-on experience, practical projects, and guidance from experienced instructors, DataMites ensures individuals in Allahabad acquire the necessary skills in data engineering.

The DataMites Certified Data Engineer Training program in Allahabad encompasses a diverse range of topics, including data engineering concepts, tools, and technologies such as Hadoop, Spark, SQL, and data pipeline development. The program also incorporates practical exercises and hands-on projects to enhance your skills in these areas.

The Data Engineer Course at DataMites® in Allahabad welcomes applications from individuals who meet certain eligibility criteria. Generally, those with a background in computer science, mathematics, or related fields, as well as professionals interested in pursuing data engineering careers, are eligible to apply.

The duration of the DataMites Data Engineer Course in Allahabad typically varies based on the learning mode chosen. On average, online instructor-led training lasts for approximately 6 months, consisting of over 150 learning hours. However, self-paced learning options may have different durations.

Yes, DataMites® offers classroom training for Data Engineer courses in Allahabad, along with online training options. They provide flexibility in choosing the training mode that best fits your preferences and schedule.

The Data Engineer Course in Allahabad at DataMites® is conducted by knowledgeable instructors who specialize in data engineering concepts, tools, and industry practices. These instructors provide comprehensive guidance and support throughout the training program.

DataMites® provides a range of training formats for data engineering courses, including instructor-led online training, classroom training, and self-paced learning options. This allows individuals to choose the format that best suits their learning preferences and schedule.

Yes, DataMites® offers the option to attend demo classes without the need to pay the course fee upfront. This enables you to get a glimpse of the teaching methodology, course content, and interact with instructors before making a commitment.

Indeed, DataMites® understands the financial circumstances of learners and offers the flexibility to pay the course fee in installments. This allows individuals to pursue their data engineering training without facing a significant upfront financial burden.

Yes, DataMites® provides Data Engineer Courses in Allahabad with placement assistance. They offer career support, including resume building, interview preparation, and networking with potential employers to help participants secure job opportunities.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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