Nux Software Solutions offers the best Google Cloud Data Engineer training courses in Coimbatore. Our advanced programs are designed to enhance your performance and provide invaluable hands-on experience in the field of data engineering.
The Google Cloud Data Engineer certification is ranked among the top-paying IT certifications globally. Our program equips you with the skills necessary to excel as a professional cloud architect and prepares you for the industry-recognized Google Cloud Professional Cloud Architect certification.
Gain practical experience in deploying solution elements, including infrastructure components such as networks, systems, and application services. Our course features numerous hands-on projects through Qwiklabs, ensuring you're job-ready upon completion.
Upon successful completion of our program, you'll receive a certificate of completion to showcase your expertise to potential employers. For those aiming to become Google Cloud certified, we provide guidance on registering for the official certification exam and offer additional preparation resources.
Becoming Google Cloud certified demonstrates your proficiency in cloud architecture and Google Cloud Platform. It showcases your ability to design, develop, and manage solutions that drive business objectives – skills highly sought after in today's tech industry.
Take the next step in your data engineering career with Nux Software Solutions' Google Cloud Data Engineer training in Coimbatore. Join us to transform your cloud engineering aspirations into reality.
Chapter 1.
Introduction
Chapter 2.
Data Processing Fundamentals, Data Processing Concepts, Data Processing Pipelines
Chapter 3.
Storage and Databases, Introduction to Data Storage in GCP, Working with Data, Cloud Storage, Service Accounts, Cloud SQL, Creating a Cloud SQL Instance and Loading Data,
Cloud Firestore, Cloud Spanner, Working with Cloud Spanner, Cloud Memorystore, Comparing Storage Options
Chapter 4.
Big Data Ecosystem, MapReduce, Hadoop & HDFS, Apache Pig, Apache Spark, Apache Kafka
Chapter 5.
Pipelines with Cloud Dataflow, Dataflow Introduction, Pipeline Lifecycle, Dataflow Pipeline Concepts, Advanced Dataflow Concepts, Dataflow Security and Access, Using Dataflow
Chapter 6
Managed Spark with Cloud Dataproc, Dataproc Overview, Dataproc Basics, Working with Cloud Dataproc, Advanced Dataproc, Cloud Dataproc with the GCS Connector
Chapter 7
NoSQL Data with Cloud Bigtable, Bigtable Concepts, Bigtable Architecture, Bigtable Data Model, LAB: Working with Cloud Bigtable, Bigtable Schema Design, Bigtable Advanced Concepts, Loading and Querying Data with Cloud Bigtable
Chapter 8
Data Analytics with BigQuery, BigQuery Basics, Using BigQuery, Partitioning and Clustering, Best Practices, Securing BigQuery, BigQuery Monitoring and Logging, Machine Learning with BigQuery ML
Chapter 9
Orchestration with Cloud Composer, Cloud Composer Overview, Cloud Composer Architecture, Advanced Cloud Composer
Chapter 10
Introduction to Machine Learning, Machine Learning Introduction, Machine Learning Basics, Machine Learning Types and Models, Overfitting, Hyperparameters, Feature Engineering
Chapter 11
Machine Learning with TensorFlow, Deep Learning with TensorFlow, Introduction to Artificial Neural Networks, Neural Network Architectures, Building a Neural Network
