CERTIFIED DATA ENGINEER CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ENGINEER LEAD MENTORS

DATA ENGINEER COURSE FEES IN KOHIMA

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

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

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UPCOMING DATA ENGINEER ONLINE CLASSES IN KOHIMA

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 KOHIMA

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 KOHIMA

In an era where data is considered the new currency, data engineers are the masterminds behind harnessing the power of big data. They design and develop scalable data pipelines, utilizing cutting-edge technologies to process and analyze vast amounts of information. According to industry reports, the big data market is projected to reach $103 billion by 2027, highlighting the increasing demand for skilled data engineers.

DataMites presents an extensive Data Engineer Course in Kohima, delivering a comprehensive learning experience over a period of 6 months and spanning more than 150 hours. The course includes 50+ hours of live online training, ensuring interactive and engaging sessions. Participants will engage in 10 capstone projects and 1 client project, allowing them to apply their skills to practical scenarios. With a 365-day flexi pass and access to a cloud lab, learners have the freedom to practice and experiment with various data engineering tools and technologies.

Here are 10 reasons to choose DataMites for Data Engineer Training in Kohima:

Renowned Faculty: DataMites boasts a team of expert faculty members, including the esteemed data professional Ashok Veda, providing comprehensive guidance and mentorship throughout the course.

Comprehensive Curriculum: The course curriculum is carefully designed to cover all essential concepts and skills necessary for data engineering, ensuring a well-rounded learning experience.

Global Certification: DataMites offers globally recognized certifications, such as IABAC, NASSCOM FutureSkills Prime, and JainX, validating learners' expertise and competency in the field of data engineering.

Flexible Learning Options: DataMites provides flexibility in learning options, allowing participants to choose between data engineer training online in Kohima or data engineer training offline in Kohima based on their preferences and convenience.

Real-World Projects: The training program incorporates hands-on projects that involve working with real-world data, enabling learners to gain practical experience and develop problem-solving skills.

Internship Opportunities: DataMites offers data engineer course with internship in Kohima to students, providing them with a chance to apply their knowledge in a professional setting and gain valuable industry exposure.

Placement Assistance: The training program includes data engineer training with placement in Kohima and job references, supporting students in connecting with potential employers and enhancing their career prospects.

Learning Materials: Participants receive hardcopy learning materials and books, ensuring easy access to reference materials even after completing the course.

Engaging Learning Community: DataMites nurtures an exclusive learning community where learners can interact, collaborate, and share insights with fellow data enthusiasts, creating a supportive and engaging learning environment.

Affordable Pricing and Scholarships: DataMites aims to make quality education accessible by offering competitive pricing and scholarships to deserving candidates.

Kohima, the capital city of Nagaland, is a captivating location in Northeast India, surrounded by picturesque hills and rich tribal culture. It provides an inspiring environment for learning. Known for its historical significance, Kohima offers a unique blend of cultural heritage and natural beauty. By choosing DataMites for Data Engineer Training Courses in Kohima, students can benefit from industry experts, acquire practical skills, and explore promising career opportunities in the field of data engineering.

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

ABOUT DATA ENGINEER COURSE IN KOHIMA

Data engineering involves designing, building, and maintaining the infrastructure and systems to collect, process, and store vast amounts of data. It focuses on creating reliable, scalable, and efficient data pipelines to support data analytics, machine learning, and other data-driven applications.

While there is no specific educational qualification required, a bachelor's or master's degree in computer science, data science, or a related field is often preferred by employers for pursuing a career in data engineering.

Yes, coding is a prerequisite for data engineering. Proficiency in programming languages such as Python, SQL, and others is essential for data engineers to develop and maintain data pipelines, perform data transformations, and work with databases.

Python is a widely preferred programming language for data engineering due to its versatility, rich ecosystem of libraries, and ease of use in tasks like data manipulation, data integration, and building scalable data pipelines.

While data engineering involves some mathematical concepts, it is primarily focused on the design and implementation of data systems and processes. The level of mathematical complexity in data engineering tasks may vary depending on the specific project requirements.

Yes, data engineering is considered a promising career choice for the future. With the increasing volume and complexity of data generated by organizations, the demand for skilled data engineers who can efficiently handle and process this data is expected to grow significantly.

The eligibility requirements for enrolling in a Data Engineer Course in Kohima may vary depending on the training institute. Generally, a basic understanding of programming and databases, along with a passion for working with data, can be beneficial.

The cost associated with Data Engineer Training in Kohima can vary depending on factors such as the training provider, program duration, and delivery mode. The cost of data engineer training in Kohima typically ranges between 40,000 INR and 1,00,000 INR, depending on the specific training program and institute. It is recommended to research and compare different training options to determine the specific cost.

Upon completing Data Engineer Training, potential job prospects include roles such as Data Engineer, Database Administrator, ETL Developer, Data Integration Specialist, or Big Data Engineer. Job opportunities can be found in various industries that deal with large volumes of data, including technology, finance, healthcare, and e-commerce.

Essential skills for a successful data engineer include proficiency in programming languages (such as Python, SQL), data modeling, database management, ETL (Extract, Transform, Load) processes, knowledge of big data technologies, cloud platforms, problem-solving abilities, and strong communication skills for effective collaboration with cross-functional teams.

FAQ’S OF DATA ENGINEER COURSE IN KOHIMA

DataMites® offers comprehensive data engineer training that equips individuals with the skills and knowledge needed to excel in the field. Their training programs cover essential topics such as data modeling, ETL processes, big data technologies, cloud platforms, and more. With experienced instructors, practical hands-on exercises, and industry-relevant curriculum, DataMites® strives to empower students with the expertise required to tackle real-world data engineering challenges and succeed in this rapidly growing field.

The DataMites Certified Data Engineer Training program in Kohima covers a comprehensive curriculum that includes:

  • Data modeling and database design

  • ETL (Extract, Transform, Load) processes and tools

  • Data integration techniques and technologies

  • Data warehousing concepts and implementation

  • Big Data technologies like Hadoop, Spark, and Kafka

The cost of DataMites Data Engineer Training in Kohima falls within the range of INR 26,548 to INR 68,000, offering flexibility for learners to choose the option that suits their budget.

  • The Data Engineer Course at DataMites® in Kohima is open to professionals who have a background in IT, computer science, engineering, or a related field.

  • Individuals with a basic understanding of programming, databases, and data analysis are eligible to participate in the Data Engineer Course at DataMites® in Kohima.

  • Aspiring data engineers who have a keen interest in working with big data, data processing, and data infrastructure can enroll in the Data Engineer Course at DataMites® in Kohima.

  • Professionals who are looking to upskill or transition their career to data engineering can participate in the Data Engineer Course at DataMites® in Kohima.

  • Graduates and postgraduates who want to gain specialized knowledge and practical skills in data engineering can join the Data Engineer Course at DataMites® in Kohima.

The DataMites Data Engineer Course in Kohima offers flexible duration options, with online instructor-led training typically spanning 6 months and involving more than 150 learning hours.

There are several advantages of opting for online data engineer training from DataMites®:

Flexibility: Online training allows you to learn at your own pace and schedule, giving you the flexibility to balance your studies with other commitments.

Accessibility: You can access the training materials and resources from anywhere with an internet connection, eliminating the need for travel or relocation.

Interactive Learning: Online training often includes live instructor-led sessions, interactive exercises, and discussions, providing a dynamic learning experience.

Cost-effective: Online training is typically more affordable than in-person courses, as it eliminates expenses such as travel and accommodation.

Updated Course Material: Online training providers like DataMites® regularly update their course material to reflect the evolving field of data engineering, ensuring that you learn the most up-to-date practices and technologies.

Industry-relevant Content: DataMites® designs its online data engineer training programs to cover the latest industry trends, tools, and techniques, ensuring that you gain relevant skills and knowledge.

Support and Networking: Online training platforms often offer support from instructors and provide opportunities to connect with fellow learners, fostering a supportive learning community.

Self-paced Learning: Online data engineer training allows you to progress at your own speed, enabling you to spend more time on challenging topics and move quickly through familiar concepts.

DataMites®'s Flexi-Pass offers learners the opportunity to select from a range of courses and attend them at their convenience. It allows individuals to design their own learning path and gain knowledge in multiple areas.

Certainly! Upon successfully completing the Data Engineer training program from DataMites®, you will be awarded industry-recognized certifications from esteemed organizations like the International Association of Business Analytics Certifications (IABAC), Jain (Deemed-to-be University), and NASSCOM FutureSkills Prime. These certifications serve as a testament to your expertise in data engineering and can greatly enhance your professional profile and career prospects.

The Data Engineer Course in Kohima at DataMites® is conducted by a qualified and experienced instructor who has extensive knowledge and practical experience in the field of data engineering.

For learners in Kohima, DataMites® provides ON DEMAND classroom training for Data Engineer courses, giving students the chance to attend traditional in-class sessions and enhance their learning experience.

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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