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Google Certified Professional Data Engineer

Hello Cloud Gurus! Data management, data analytics, machine learning and artificial intelligence are all hot topics. And who does these better than Google? Our Google Certified Professional Data Engineer course will help prepare you for the certification exam so you can take that next step in your Cloud career and demonstrate your proficiency in one of the most in-demand disciplines in the industry today. The primary focus of this course is to prepare you for the GCP Professional Data Engineer certification exam. Along the way you’ll solidify your foundations in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies. This course will teach you how to: * Design, build and operationalize data solutions * Process data streams in real-time * Efficiently store and access data in the cloud * Use the GCP pre-trained AI APIs (vision, speech and text) * Train and operationalize ML models. The Google Cloud Professional Data Engineer is for data scientists, solution architects, devops engineers and anyone wanting to move into machine learning and data engineering in the context of Google. Students will need to have some familiarity with the basics of GCP, such as: storage, compute and security; some basic coding skills (like Python); and a good understanding of databases. You do not need to have a background in data engineering or machine learning, but some experience with GCP is essential. This is an advanced certification and we strongly recommend that students take the Google Certified Associate Cloud Engineer exam before embarking on this course. However, anyone who is motivated and wants to understand how big data and machine learning is done on GCP will still find value with this course. Keep being awesome, Cloud Gurus!

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Know what's good

, what to watch for

, and possible dealbreakers

Possibilities are explored in machine learning and big data applicable to GCP

Best suited to students with GCP experience

Provides certification in Professional Data Engineering

Taught by A Cloud Guru, recognized for their work in this field

Intended for those experienced in GCP and data engineering

Relevant to solution architects, devops engineers, and data scientists

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Google Certified Professional Data Engineer with these activities:

Review Python Coding

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Reinforce foundational coding skills in Python to strengthen your understanding of programming concepts and prepare for more advanced topics in data engineering.

Browse courses on Python 3

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Revisit online tutorials on Python basics
Solve coding challenges on platforms like LeetCode or HackerRank
Build a simple Python project to apply your skills

Join a GCP Community or Discussion Group

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Connect with other GCP enthusiasts and professionals to share knowledge, ask questions, and participate in discussions related to data engineering and machine learning.

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Join relevant GCP communities on platforms like Stack Overflow or Reddit
Participate in discussions and ask questions related to your learning journey
Collaborate with others on projects or study sessions

Practice BigQuery Queries

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Enhance your data analytics capabilities by practicing BigQuery queries to extract meaningful insights from large datasets.

Browse courses on Data Analytics

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Explore BigQuery's documentation and tutorials
Complete exercises and practice queries on the BigQuery website
Create custom datasets and tables to practice querying real-world data

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Design a Data Pipeline Architecture

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Solidify your understanding of data engineering principles by creating a detailed plan for a data pipeline architecture, considering data sources, transformations, and storage.

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Identify the data sources and their characteristics
Design the data transformations and processing steps
Choose appropriate storage solutions for different data types
Create a visual representation of the data pipeline architecture

Attend a GCP Data Engineering Workshop

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Gain practical experience and delve deeper into specific aspects of GCP data engineering through hands-on workshops led by industry experts.

Browse courses on Professional Development

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Research and identify relevant GCP Data Engineering workshops
Register and attend the workshop
Actively participate in hands-on exercises and discussions

Explore GCP Machine Learning APIs

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Expand your knowledge of machine learning by exploring the capabilities of GCP's pre-trained AI APIs, such as those for vision, speech, and text analysis.

Browse courses on Computer Vision

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Review the documentation and tutorials for each API
Experiment with the APIs using provided sample code and datasets
Build small projects to apply your understanding of the APIs

Contribute to Open Source Data Projects

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Enhance your practical skills and contribute to the data engineering community by participating in open source projects, such as data processing pipelines or machine learning models.

Browse courses on Community Involvement

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Find open source data projects aligned with your interests
Review the project documentation and contribute to issues
Propose and implement new features or improvements

Build a Machine Learning Model

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Apply your knowledge of machine learning by building a complete model, including data preparation, feature engineering, model training, and evaluation.

Browse courses on Machine Learning Models

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Choose a dataset and define the problem statement
Prepare and clean the data
Explore and select appropriate machine learning algorithms
Train and evaluate the model
Deploy and monitor the model in production

Career center

Learners who complete Google Certified Professional Data Engineer will develop knowledge and skills that may be useful to these careers:

Data Engineer

A Data Engineer designs, builds, and operationalizes data solutions. They process data streams in real-time, efficiently store and access data in the cloud, and use the GCP pre-trained AI APIs (vision, speech and text) to train and operationalize ML models. This course helps build a foundation in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer uses the GCP pre-trained AI APIs (vision, speech and text) to train and operationalize ML models. This course helps build a foundation in data engineering and machine learning, ensuring that by the end of the course you will be able to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist uses the knowledge of data engineering and machine learning to design and build data processing solutions, operationalize machine learning models and gain a working knowledge of relevant GCP data processing tools and technologies.

See salaries and explore the career path for Data Scientist

Solution Architect

A Solution Architect designs and builds data processing solutions. This course may be useful to develop the skills needed in this role, such as data engineering, machine learning, and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for Solution Architect

DevOps Engineer

A DevOps Engineer operationalizes machine learning models. This course may be useful to develop the skills needed in this role, such as data engineering, machine learning, and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for DevOps Engineer

Data Analyst

A Data Analyst processes data streams in real-time and efficiently stores and accesses data in the cloud. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for Data Analyst

Cloud Engineer

A Cloud Engineer designs, builds, and operationalizes data solutions. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

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Systems Engineer

A Systems Engineer designs, builds, and operationalizes data solutions. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for Systems Engineer

Database Administrator

A Database Administrator efficiently stores and accesses data in the cloud. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for Database Administrator

Security Engineer

A Security Engineer designs, builds, and operationalizes data solutions. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

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Network Engineer

A Network Engineer efficiently stores and accesses data in the cloud. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

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Software Engineer

A Software Engineer designs, builds, and operationalizes data solutions. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

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Web Developer

A Web Developer designs, builds, and operationalizes data solutions. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

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Data Management Analyst

A Data Management Analyst efficiently stores and accesses data in the cloud. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for Data Management Analyst

Business Analyst

A Business Analyst designs, builds, and operationalizes data solutions. This course may be useful to develop the skills needed in this role, such as data engineering and the use of GCP pre-trained AI APIs.

See salaries and explore the career path for Business Analyst

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Google Certified Professional Data Engineer.

Deep Learning

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Comprehensive overview of deep learning, covering the basics of deep learning, as well as more advanced topics such as convolutional neural networks and recurrent neural networks.

Google Certified Professional Data Engineer

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