GCP DATA ENGINEER Training in Pune/ Online
Duration of Training : 32 Hrs
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Why Radical Technologies
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.
Module 2: Running Dataproc Jobs
- Running Pig and Hive jobs.
- Separation of storage and compute.
- Lab: Running Hadoop and Spark Jobs with Dataproc.
- Lab: Submit and monitor jobs.
Module 3: Integrating Dataproc with Google Cloud Platform
- Customize cluster with initialization actions.
- Lab: Leveraging Google Cloud Platform Services.
Module 4: Making Sense of Unstructured Data with Google’s Machine Learning APIs
- Google’s Machine Learning APIs.
- Lab: Adding Machine Learning Capabilities to Big Data Analysis.
Module 5: Serverless data analysis with BigQuery
- 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.
Module 6: Serverless, autoscaling data pipelines with Dataflow
- 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.
- GCP Reference architecture.
Module 7: Getting started with Machine Learning
- What is machine learning (ML)
- Effective ML: concepts, types.
- ML datasets: generalization.
- Lab: Explore and create ML datasets.
Module 8: Building ML models with Tensorflow
- Getting started with TensorFlow.
- TensorFlow graphs and loops + lab.
- Lab: Using low-level TensorFlow + early stopping.
- Lab: Charts and graphs of TensorFlow training.
Module 9: Scaling ML models with CloudML
- Packaging up a TensorFlow model.
- Lab: Run a ML model locally and on cloud.
Module 10: Feature Engineering
- Preprocessing with Cloud ML.
- Lab: Feature engineering.
Module 11: Architecture of streaming analytics pipelines
- Stream data processing: Challenges.
- Handling variable data volumes.
- Dealing with unordered/late data.
- Lab: Designing streaming pipeline.
Module 12: Ingesting Variable Volumes
- How it works: Topics and Subscriptions.
Module 13: Implementing streaming pipelines
- Challenges in stream processing.
- Handle late data: watermarks, triggers, accumulation.
- Lab: Stream data processing pipeline for live traffic data.
Module 14: Streaming analytics and dashboards
- 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.
Module 15: High throughput and low-latency with Bigtable
- Designing Bigtable schema.
- Lab: streaming into Bigtable.
Most Probable Interview Questions for Google Cloud Platform / GCP Data Engineer
- Interview Question No. 1 for Google Cloud Platform / GCP Data Engineer : Can you explain your experience with Google Cloud Platform (GCP) and how it relates to your role as a Data Engineer?
- Interview Question No. 2 for Google Cloud Platform / GCP Data Engineer : How do you approach designing data pipelines on Google Cloud Platform? Can you walk us through a project where you implemented such pipelines?
- Interview Question No. 3 for Google Cloud Platform / GCP Data Engineer : What are some common challenges you’ve faced when working with BigQuery, and how did you overcome them?
- Interview Question No. 4 for Google Cloud Platform / GCP Data Engineer : Can you discuss your experience with data transformation and processing using GCP Dataflow?
- Interview Question No. 5 for Google Cloud Platform / GCP Data Engineer : How do you ensure data integrity and reliability when designing and implementing databases on Google Cloud Platform?
- Interview Question No. 6 for Google Cloud Platform / GCP Data Engineer : Can you explain the significance of Pub/Sub in the context of real-time data processing on GCP?
- Interview Question No. 7 for Google Cloud Platform / GCP Data Engineer : Have you worked with any specific GCP services or tools for data visualization and analytics? If so, can you provide examples of projects where you utilized these tools?
- Interview Question No. 8 for Google Cloud Platform / GCP Data Engineer : How do you optimize data storage and retrieval performance in Google Cloud Storage?
- Interview Question No. 9 for Google Cloud Platform / GCP Data Engineer : What strategies do you employ to monitor and troubleshoot data pipelines and processing jobs in GCP?
- Interview Question No. 10 for Google Cloud Platform / GCP Data Engineer : Can you discuss your experience with deploying and managing data processing applications on Google Kubernetes Engine (GKE)?
- Interview Question No. 11 for Google Cloud Platform / GCP Data Engineer : How do you ensure data security and compliance when working with sensitive information on GCP?
- Interview Question No. 12 for Google Cloud Platform / GCP Data Engineer : Can you describe a scenario where you had to scale data processing resources dynamically based on workload demands in GCP?
- Interview Question No. 13 for Google Cloud Platform / GCP Data Engineer : How do you approach data modeling and schema design for databases hosted on Google Cloud SQL?
- Interview Question No. 14 for Google Cloud Platform / GCP Data Engineer : Have you utilized GCP’s machine learning services in any of your data engineering projects? If so, can you provide examples?
- Interview Question No. 15 for Google Cloud Platform / GCP Data Engineer : Can you discuss your familiarity with GCP’s identity and access management (IAM) and its relevance to data engineering tasks?
- Interview Question No. 16 for Google Cloud Platform / GCP Data Engineer : What strategies do you employ to optimize costs when provisioning and managing data infrastructure on GCP?
- Interview Question No. 17 for Google Cloud Platform / GCP Data Engineer : Can you share your experience with orchestrating and scheduling data workflows using GCP’s Composer or Cloud Scheduler?
- Interview Question No. 18 for Google Cloud Platform / GCP Data Engineer : How do you handle data versioning and lineage tracking in a GCP environment?
- Interview Question No. 19 for Google Cloud Platform / GCP Data Engineer : Can you discuss your experience with data migration projects to Google Cloud Platform from other cloud providers or on-premises solutions?
- Interview Question No. 20 for Google Cloud Platform / GCP Data Engineer : How do you stay updated with the latest developments and best practices in GCP data engineering?
Google Cloud Platform / GCP Data Engineer – Course in Pune with Training, Certification & Guaranteed Job Placement Assistance!
Welcome to Radical Technologies, your premier destination for comprehensive training in Google Cloud Platform (GCP) Data Engineering. At Radical Technologies, we specialize in offering cutting-edge courses and certifications tailored to empower aspiring professionals with the skills and expertise needed to excel in the dynamic field of cloud data engineering.
Our institute, located in Pune, is renowned for its excellence in providing top-notch Google Cloud Data Engineer courses, training, and certifications. With a focus on practical learning and real-world applications, we ensure that our students not only grasp theoretical concepts but also gain hands-on experience in utilizing GCP services effectively.
With a team of experienced instructors who are industry experts in GCP data engineering, we provide personalized attention to each student, ensuring that they receive the guidance and support needed to succeed. Our curriculum covers a wide range of topics, including data processing, storage, analytics, machine learning, and more, all within the context of Google Cloud Platform.
At Radical Technologies, we understand the importance of job placement assistance in today’s competitive market. That’s why we offer comprehensive support to our students, including resume building, interview preparation, and networking opportunities with potential employers. Our goal is not just to train students but to empower them to secure fulfilling careers in the field of cloud data engineering.
Whether you’re a beginner looking to kickstart your career or an experienced professional aiming to upskill and advance in your field, our Google Cloud Data Engineer courses are designed to meet your needs. Join us at Radical Technologies and embark on a transformative learning journey towards becoming a proficient GCP Data Engineer.
Experience the Radical difference – where excellence meets opportunity, and where your aspirations become achievements. Unlock your potential with us today and embark on a rewarding career in Google Cloud Platform Data Engineering.
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