Who should take Data Engineering on Google Cloud Platform course?
This course is designed for developers responsible for data processing tasks like extracting, loading, transforming, cleaning, and validating data. It's also ideal for those looking to design data pipelines, integrate analytics and machine learning, query datasets, and create reports.
What are the prerequisites for this course?
To get the most out of the course, participants should have completed the Google Cloud Fundamentals: Big Data & Machine Learning course or have equivalent experience. Basic SQL proficiency, experience with data modeling and ETL activities, and familiarity with Python programming are also recommended. Additionally, some understanding of machine learning and statistics is beneficial.
What data types does the Data Engineering on Google Cloud Platform course cover?
The course covers structured, unstructured, and streaming data. You'll learn how to process batch and real-time data flows using powerful GCP services like Cloud Dataflow, Cloud Dataproc, and Cloud Pub/Sub.
What will I learn about machine learning?
You'll be introduced to integrating machine learning capabilities into your data pipelines using ML APIs, BigQuery ML, and Cloud AutoML. This will enable you to build powerful models without extensive coding experience.
Is this Data Engineering on Google Cloud Platform course hands-on?
Yes, the course features 50-60% hands-on labs, allowing you to apply your learnings to practical scenarios and simulate real-world data engineering challenges.
What are the course delivery options?
The course is available in both virtual and face-to-face formats. Both options offer interactive learning experiences with certified instructors and live sessions.
What are the learning outcomes of this course?
By the end of the course, you'll be able to: Design and build scalable data pipelines on GCP for diverse data types. Process both batch and streaming data efficiently with auto-scaling features. Extract valuable insights from large datasets using BigQuery and advanced analytics tools. Leverage unstructured data for valuable insights through Spark and ML integration. Generate real-time insights from streaming data for agile decision-making. Build machine learning models using Cloud AutoML and BigQuery ML, even without extensive coding.
How does CloudThat stand out for this training?
CloudThat offers several advantages: Specialized GCP focus: We provide in-depth GCP training with authorized trainers and real-world expertise. Hands-on learning: Our labs and projects help you apply theory to practice. Customized learning paths: We cater to beginners, intermediate learners, and advanced professionals. Interactive learning experience: We utilize engaging teaching methods to keep you motivated. Placement assistance: We can help you connect with GCP job opportunities. Continuous learning updates: We ensure our content reflects the latest GCP trends and best practices. Positive reviews and testimonials: We have a strong track record of satisfied learners.
I have more questions. How can I get in touch?
Please visit our website or contact us directly for more information and to discuss your specific needs.