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GCP Data Engineer Training in Vizag

Google Cloud Platform (GCP) is among the technologies that are most rapidly developing in cloud computing. Various companies require data engineers who are capable of processing, managing, and analysing huge amounts of data on the cloud. Whether you’re a student, working professionals from Vizag or from any place, Version IT provides a full GCP Data Engineer Training Program online. Our course provides knowledge of how to design pipelines of data, operate data warehouses, and create end-to-end data solutions using GCP services.

12 Modules

with Certifications

Certificate

After Completion

English

Language

Why Choose GCP Data Engineering?

Data engineering has become an essential requirement of the digital economy. Companies rely on accurate data information in decision-making. The services offered by GCP, which are BigQuery, Dataflow, Pub/Sub and Dataproc can help provide scalable solutions to the businesses of the current era.

A certified GCP Data Engineer can:

  • Establish and gain confidence in sound data processing systems.
  • Create real-time and batch data pipelines.
  • Fuel decision-making using smart analytics.
  • Reduce expenses through optimization of cloud architecture.

Your future career as a GCP Data Engineer will enable you to work in a live cloud environment and this is achievable by attending best GCP Data Engineer Training in Vizag.

About Version IT’s GCP Data Engineer Online Training in Vizag

Version It is one of the top GCP Data Engineer Training Institute. We are trained according to the most recent Google Cloud Professional Data engineer certification model. It is constructed on practical education through live projects hence you will be a completed course person with job-ready skills.

The highlights of our GCP Data Engineer training program are as follows:

– GCP qualified professionals that introduce practical experience.

– Hands-on activities and collaborative laboratories to support learning.

– Preparation guide to the exam Google Professional Data Engineer.

– Placement support and career guidance of the students and professionals.

Whether it is the first time you are introduced to cloud computing or you are an IT expert and wish to upgrade to be a successful data engineer in GCP, this course provides a straightforward map of becoming an effective one.

GCP Data Engineer Course Skills You Will Learn

Through our training, you will acquire the knowledge of the theoretical and practical side of GCP data engineering. You will get to know how to:

  • Navigate the Google Cloud Platform and its console
  • Use BigQuery to warehouse and query
  • Create ETL pipelines in Cloud Dataflow and Dataproc
  • Process real-time data in Pub/SUB and Data Fusion
  • Manage data in Cloud Storage with advanced partitioning
  • Deploy machine-learning models in BigQuery ML
  • Manage IAM roles, and how to optimize performance and control costs.

These are skills that will equip you with complex data-engineering situations in the modern business world.

Course Curriculum for GCP Data Engineer Training

Our GCP Data engineer course in Vizag is structured into modules which are focused to take you through the basics up to the advanced topics. The curriculum covers:

  • Introduction to the cloud and to GCP fundamentals
  • In-depth analysis of BigQuery to work with the structured and unstructured data
  • Practical training of the scalable pipelines in the ETL system through Dataflow, Dataproc, and Cloud Data Fusion
  • Analysis of the data in real time with Pub/Sub
  • Data storage and integration using Cloud Storage, Firestore, and partitioning methods
  • Overview of the BigQuery ML as the predictive analytics
  • Work with the data in real life within the finance sector, healthcare, retail and e-commerce.

This architecture will make sure that you can deal with both batch processing and real-time analytics on the cloud.

Who Can Join This Training?

We serve a wide audience of learners:

  • IT professionals wishing to upskill in cloud data engineering, new graduates and those wishing to enter the field of data engineering.
  • Database administrators and developers who need to leave their previous technologies and move to cloud-based technologies
  • Big Data professionals who want to specialize in GCP
  • Anyone studying toward the Google Cloud Professional Data Engineer certification

There will be no previous GCP experience, but it is desirable to have some knowledge of the basics of database and SQL.

Career Opportunities after GCP Data Engineer Training

As a certified GCP Data Engineer, one can access good positions like:

  • GCP Data Engineer
  • Big Data Engineer
  • Cloud Data Architect
  • Business Intelligence Engineer
  • High-level Data Analyst with the help of GCP tools

The top firms (Google, Spotify, HSBC, PayPal, Verizon, and Twitter) are aggressively hiring certified engineers.

A GCP Data Engineer in India will make an average of 8 LPA up to 18 LPA, based on experience, organization and knowledge. The future of the career in Vizag and at large in India is very bright owing to the rising cloud adoption.

Why Choose Vizag for GCP Training?

Vizag is emerging as an IT centre in Andhra Pradesh with the new technology companies heavily investing in the city. The employment of certified specialists in the field of data and clouds is high, which leaves many opportunities locally and internationally. Your GCP Data Engineer Training in Vizag is a great opportunity to receive the highest-quality education and the possibility to enter this market.

Certification Guidance

The training is consistent with Google Cloud Professional Data Engineer certification exam, which evaluates your skills in system design, pipeline creation, operating machine-learning models on GCP, and compliance, security, and scalability. To succeed successfully, we offer practice exams, case studies and mock tests to our trainers.

Projects You Will Work On

During the course, you will build real world projects, including real time log analysis with Pub/Sub and BigQuery; customer churn prediction pipeline with BigQuery ML, data warehouse solution with BigQuery analytics, and batch processing jobs with Cloud Dataflow and Dataproc. Such practical experiences are necessary in getting data engineering jobs.

Enroll in GCP Data Engineer Training in Vizag

At Version IT we make learners certified cloud data professionals by undertaking rigorous training, undergoing expert guidance and comprehensive placement support.

Topics You will Learn

Designing flexible data representations. Considerations include:

  • future advances in data technology
  • changes to business requirements
  • awareness of current state and how to migrate the design to a future state
  • data modeling
  • tradeoffs
  • distributed systems
  • schema design

Designing data pipelines. Considerations include:

  • future advances in data technology
  • changes to business requirements
  • awareness of current state and how to migrate the design to a future state
  • data modeling
  • tradeoffs
  • system availability
  • distributed systems
  • schema design
  • common sources of error (eg. removing selection bias

Designing data processing infrastructure. Considerations include:

  • future advances in data technology
  • changes to business requirements
  • awareness of current state, how to migrate the design to the future state
  • data modeling
  • tradeoffs
  • system availability
  • distributed systems
  • schema design
  • capacity planning
  • different types of architectures: message brokers, message queues, middleware, serviceoriented

Building and maintaining flexible data representations
Building and maintaining pipelines. Considerations include:

  • data cleansing
  • batch and streaming
  • transformation
  • acquire and import data
  • testing and quality control
  • Connecting to new data sources

Building and maintaining processing infrastructure. Considerations include:

  • provisioning resources
  • monitoring pipelines
  • adjusting pipelines
  • testing and quality control

Analyzing data. Considerations include:

  • data collection and labeling
  • data visualization
  • dimensionality reduction
  • data cleaning/normalization
  • defining success metrics

Machine learning. Considerations include:

  • feature selection/engineering
  • algorithm selection
  • debugging a model

Machine learning model deployment. Considerations include:

  • performance/cost optimization
  • online/dynamic learning

Performing quality control. Considerations include:

  • verification
  • building and running test suites
  • pipeline monitoring

Assessing, troubleshooting, and improving data representations and data processing
infrastructure.

Recovering data. Considerations include:

  • planning (e.g. fault-tolerance)
  • executing (e.g., rerunning failed jobs, performing retrospective re-analysis)
  • stress testing data recovery plans and processes
  • Applications of Data structures
  • Types of Collections
  • Sequence
  • Strings, List, Tuple, range
  • Non sequence
  • Set, Frozen set, Dictionary
  • Strings
  • What is string
  • Representation of Strings
  • Processing elements using indexing
  • Processing elements using Iterators
  • Manipulation of String using Indexing and Slicing
  • String operators
  • Methods of String object
  • String Formatting
  • String functions
  • String Immutability
  • Case studies
  • What is tuple?
  • Different ways of creating Tuple
  • Method of Tuple object
  • Tuple is Immutable
  • Mutable and Immutable elements of Tuple
  • Process tuple through Indexing and Slicing
  • List v/s Tuple
  • Building (or selecting) data visualization and reporting tools. Considerations include:
    automation
  • decision support
  • data summarization, (e.g, translation up the chain, fidelity, trackability, integrity)

Advocating policies and publishing data and reports.

Designing secure data infrastructure and processes. Considerations include:

  • Identity and Access Management (IAM)
  • data security
  • penetration testing
  • Separation of Duties (SoD)
  • security control
  • Designing for legal compliance. Considerations include:
    legislation (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children’s
    Online Privacy Protection Act (COPPA), etc.)
  • audits
  • Arithmetic Operators
  • Comparison Operators
  • Python Assignment Operators
  • Logical Operators
  • Bitwise Operators
  • Shift operators
  • Membership Operators
  • Identity Operators
  • Ternary Operator
  • Operator precedence
  • Difference between “is” vs “==”
  • Conditional control statements
  • If
  • If-else
  • If-elif-else
  • Nested-if
  • Loop control statements
  • for
  • while
  • Nested loops
  • Branching statements
  • Break
  • Continue
  • Pass
  • Return
  • Case studies
  • What is List
  • Need of List collection
  • Different ways of creating List
  • List comprehension
  • List indices
  • Processing elements of List through Indexing and Slicing
  • List object methods
  • List is Mutable
  • Mutable and Immutable elements of List
  • Nested Lists
  • List_of_lists
  • Hardcopy, shallowCopy and DeepCopy
  • zip() in Python
  • How to unzip?
  • Python Arrays:
  • Case studies
  • What is set?
  • Different ways of creating set
  • Difference between list and set
  • Iteration Over Sets
  • Accessing elements of set
  • Python Set Methods
  • Python Set Operations
  • Union of sets
  • functions and methods of set
  • Python Frozen set
  • Difference between set and frozenset ?
  • Case study

Let Your Certificates Speak

Certificate

All You Need to Start this Course

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Still Having Doubts?

The course will prepare you to create scalable data pipelines, operate with large-scale data on Google Cloud, and create machine-learning models. You will use the fundamental services like BigQuery, Dataflow and Cloud Dataproc to build end to end solutions.

The target market of this training is on IT graduates, working professionals and data analysts. It can also be used by anyone who wishes to start a cloud-based data engineering career by using Google Cloud technologies.

Majority of the institutes include specific course of Google Cloud Professional Data Engineer exam preparation in their curriculum and cover all major topics to pass exam.

Yes, the course work will feature on-the-job projects and working lab sessions. Students are exposed to working with, processing, and analyzing big data using Google Cloud solutions.

GCP Data Engineers are also demanded highly. Professional opportunities encompass cloud migration, data pipeline development, and analytics projects in major companies.

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