Master Data Engineering with Google Cloud Platform Course Online

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Data Engineering on Google Cloud Platform Course Overview

The Data Engineering on Google Cloud Platform certification validates an individual's ability to design, build, maintain, and troubleshoot data processing systems using Google Cloud. Certified data engineers fuse architecture, development, and operations skills to provide business solutions using Google Cloud's big data products. Industries utilize this certification to identify professionals proficient in machine learning and data analysis. They create operational databases, design data processing systems, optimize Google Cloud for scalability and efficiency, and ensure solution quality and security. Hence, they drive AI initiatives, implement real-time analytics for real-time decision making, and enable various business insights through reliable data infrastructure.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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The 1-on-1 Advantage

Get 1-on-1 session with our expert trainers at a date & time of your convenience.
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Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.
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4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.
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Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

Module 1: Google Cloud Dataproc Overview
  • Creating and managing clusters.
  • Leveraging custom machine types and preemptible worker nodes.
  • Scaling and deleting Clusters
  • Lab: Creating Hadoop Clusters with Google Cloud Dataproc
  • Running Pig and Hive jobs.
  • Separation of storage and compute.
  • Lab: Running Hadoop and Spark Jobs with Dataproc.
  • Lab: Submit and monitor jobs.
  • Customize cluster with initialization actions.
  • BigQuery Support.
  • Lab: Leveraging Google Cloud Platform Services.
  • Google’s Machine Learning APIs
  • Common ML Use Cases
  • Invoking ML APIs
  • Lab: Adding Machine Learning Capabilities to Big Data Analysis
  • What is BigQuery
  • Queries and Functions.
  • Lab: Writing queries in BigQuery.
  • Loading data into BigQuery.
  • Exporting data from BigQuery.
  • Lab: Loading and exporting data.
  • Nested and repeated fields.
  • Querying multiple tables
  • Lab: Complex queries
  • Performance and pricing.
  • The Beam programming model.
  • Data pipelines in Beam Python.
  • Data pipelines in Beam Java.
  • Lab: Writing a Dataflow pipeline
  • Scalable Big Data processing using Beam.
  • Lab: MapReduce in Dataflow.
  • Incorporating additional data.
  • Lab: Side inputs
  • Handling stream data.
  • GCP Reference architecture
  • What is machine learning (ML).
  • Effective ML: concepts, types.
  • ML datasets: generalization
  • Lab: Explore and create ML datasets.
  • Getting started with TensorFlow.
  • Lab: Using tf.learn.
  • TensorFlow graphs and loops + lab.
  • Lab: Using low-level TensorFlow + early stopping.
  • Monitoring ML training.
  • Lab: Charts and graphs of TensorFlow training.
  • Why Cloud ML?
  • Packaging up a TensorFlow model.
  • End-to-end training
  • Lab: Run a ML model locally and on cloud
  • Creating good features.
  • Transforming inputs.
  • Synthetic features
  • Preprocessing with Cloud ML.
  • Lab: Feature engineering.
  • Stream data processing: Challenges.
  • Handling variable data volumes.
  • Dealing with unordered/late data.
  • Lab: Designing streaming pipeline
  • What is Cloud Pub/Sub?
  • How it works: Topics and Subscriptions
  • Lab: Simulator.
  • Challenges in stream processing.
  • Handle late data: watermarks, triggers, accumulation
  • Lab: Stream data processing pipeline for live traffic data.
  • Streaming analytics: from data to decisions
  • Querying streaming data with BigQuery.
  • What is Google Data Studio?
  • Lab: build a real-time dashboard to visualize processed data.
  • What is Cloud Spanner?
  • Designing Bigtable schema
  • Ingesting into Bigtable
  • Lab: streaming into Bigtable.
Live Online Training (Duration : 32 Hours) 4100 + If you accept merging of other students. Per Participant & excluding VAT/GST
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
Date On Request
Data Engineering on Google Cloud Platform
Course Prerequisites
- Proficiency in SQL language
- Basic understanding of Google Cloud Platform (GCP)
- Familiarity with big data tools like Hadoop and Spark
- Fundamental knowledge of database concepts
- Experience in data modeling and data warehousing
- Basic programming skills, especially Python or Java

Data Engineering on Google Cloud Platform Certification Training Overview

Data Engineering on Google Cloud Platform certification training is designed to enhance your expertise in designing, building, and maintaining data processing systems and databases on Google Cloud. The course covers key topics such as Google Cloud's big data and machine learning products, data processing technologies, data transformation, and relational database handling. It also elaborates on real-world scenarios of data engineering in Google Cloud, providing comprehensive knowledge for implementing solutions in a cloud-based infrastructure.

Why Should You Learn Data Engineering on Google Cloud Platform?

Learning Data Engineering on Google Cloud Platform provides valuable skill sets such as scaling data servers, analyzing data, and managing large data sets. It helps in developing proficiency in Google Cloud’s big data and machine learning tools, enhancing employability in the fast-growing technology market. It also enables individuals to be recognized as a Google Certified Professional Data Engineer.

Target Audience for Data Engineering on Google Cloud Platform Certification Training

• IT professionals, developers, and software engineers seeking knowledge on cloud computing.
• Data analysts and business intelligence professionals who want to leverage Google Cloud for data solutions.
• Individuals aiming for Google Cloud certification.
• Teams migrating storage and databases to cloud-based ecosystems.

Why Choose Koenig for Data Engineering on Google Cloud Platform Certification Training?

• Certified Instructors: Koenig's certified trainers ensure quality and comprehensive education.
• Career Boost: The data engineering training can dramatically improve your job prospects.
• Customized Training: Tailor made programs to meet individual learning needs.
• Destination Training: Option for immersive, focused learning at their various global sites.
• Affordable: High-quality training programs at competitive pricing.
• Highly Recognized: Known as a top training institute in the IT field.
• Flexible Dates: Enables learning at your own pace and convenience.
• Online Training: Allows remote, real-time learning under expert guidance.
• Wide Course Range: Offers a great variety of IT and professional courses.
• Accredited Training: Legitimate, recognized courses that boost your credibility in the industry.

Data Engineering on Google Cloud Platform Skills Measured

After completing Data Engineering on Google Cloud Platform certification training, an individual can acquire skills including designing, building, and maintaining data processing systems. They would have an understanding of machine learning algorithms, have the ability to design and implement data solutions using Google's managed services, ensure data security and reliability, and effectively visualize data for analysis. Moreover, they would gain the ability to leverage, deploy, and continuously train pre-existing ML models. They would become proficient in using services like Cloud Storage, BigQuery, Dataproc, and Cloud Dataflow.

Top Companies Hiring Data Engineering on Google Cloud Platform Certified Professionals

Major companies such as Google, Microsoft, Deloitte, Accenture, IBM, and SAP are hiring Data Engineering on Google Cloud Platform certified professionals. These companies look for experts to utilize Google Cloud technologies, analyze and process data, and create machine learning models to improve business efficiencies.

Learning Objectives - What you will Learn in this Data Engineering on Google Cloud Platform Course?

The learning objectives of a Data Engineering on Google Cloud Platform course are to surface in-depth knowledge of designing, building, and managing robust, secure, scalable, and dynamic solutions on Google Cloud. Participants will acquire skills to process big data through specific Google Cloud services such as Cloud Storage, Dataflow, and Bigtable. They will understand the operational aspects of machine learning models and develop proficiency in data lifecycle management. The course aims to equip learners in creating a data infrastructure, managing data processing systems, ensuring compliance with data security standards and understanding Google Cloud's crucial data processing systems.

FAQ's

You can pay through debit/credit card or bank wire transfer.
Buy-Now. Pay-Later option is available using credit card in USA and India only.
You will receive the letter of course attendance post training completion via learning enhancement tool after registration.
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Yes you can.
Yes, we do. For details go to flexi
Yes, we also offer weekend classes.
1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
Yes, course requiring practical include hands-on labs.
You can buy online from the page by clicking on "Buy Now". You can view alternate payment method on payment options page.
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Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
Yes, we do offer corporate training More details
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You can request a refund if you do not wish to enroll in the course.
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We do accept all major credit cards from Visa, Mastercard, American Express, and Discover.
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Yes, we do accept partial payments, you may use one payment method for part of the transaction and another payment method for other parts of the transaction.
Yes, if we have an office in your city.
Yes, fee excludes local taxes.
Yes, we do.
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).

Prices & Payments

Yes of course.
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Travel and Visa

Yes we do after your registration for course.

Food and Beverages

Yes.

Others

Yes, if you send 4 participants, we can offer an exclusive training for them which can be started from Any Date™ suitable for you.
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“It is an interesting story and dates back half a century. My father started a manufacturing business in India in the 1960's for import substitute electromechanical components such as microswitches. German and Japanese goods were held in high esteem so he named his company Essen Deinki (Essen is a well known industrial town in Germany and Deinki is Japanese for electric company). His products were very good quality and the fact that they sounded German and Japanese also helped. He did quite well. In 1970s he branched out into electronic products and again looked for a German name. This time he chose Koenig, and Koenig Electronics was born. In 1990s after graduating from college I was looking for a name for my company and Koenig Solutions sounded just right. Initially we had marketed under the brand of Digital Equipment Corporation but DEC went out of business and we switched to the Koenig name. Koenig is difficult to pronounce and marketeers said it is not a good choice for a B2C brand. But it has proven lucky for us.” – Says Rohit Aggarwal (Founder and CEO - Koenig Solutions)
All our trainers are fluent in English . Majority of our customers are from outside India and our trainers speak in a neutral accent which is easily understandable by students from all nationalities. Our money back guarantee also stands for accent of the trainer.
Medical services in India are at par with the world and are a fraction of costs in Europe and USA. A number of our students have scheduled cosmetic, dental and ocular procedures during their stay in India. We can provide advice about this, on request.