Best Data Analytics with Google Cloud Platform Online Course

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Course Highlights

The programme prepares aspiring Cloud Data Analysts for entry-level roles in the field.
Learners will complete hands-on labs in each course to practise key skills and produce work examples to show potential employers.
The final course includes an interactive capstone project that follows the full cloud data lifecycle and prepares learners for a career in Cloud Data Analytics.
The total time to complete the programme is approximately 90 hours.
The programme includes 5 courses, 19 modules, 183 videos, 15 labs, 160 readings, 82 quizzes, and one capstone.

Upon completion of the programme, learners will be able to:

Demonstrate the steps of the data journey from source to dashboard.
Assess the feasibility of a business request and translate it into actionable data analysis.
Identify appropriate data visualisation techniques for different types of data and analysis goals.
Effectively collect, process and store data.
Explain how to troubleshoot data workflow errors.
Develop career resources and practice resume and interview techniques for a role in Cloud Computing in Data Analytics.

Prepare you for entry-level roles as a Cloud Data Analyst.
Provides hands-on labs to practise key skills and produce work examples for potential employers.
Culminates in a capstone project that applies knowledge and skills to complete a full cloud data lifecycle project.
Teaches you to structure, store, access and visualise data using various cloud tools and integrations.
Includes supplementary content on foundational concepts for learners who do not have prior knowledge.

Aspiring Cloud Data Analysts.
Learners who have familiarity with foundational concepts, skills and tools in data analytics.
People who want to learn a basic understanding of SQL, data cleaning, analysis and visualisation, business intelligence, and a foundation in data communication via the design and interpretation of dashboards.

The programme has five courses:

Course 1: An Introduction to Data Analytics in Google Cloud (approx. 16 hours): Introduces cloud data analysis practices, defines the field, describes roles and responsibilities, and explores Google Cloud tools such as BigQuery and Google Cloud Storage.
Course 2: Data Management and Storage in the Cloud (approx. 24 hours): Explores how data is structured and organised, including data lakehouse architecture and cloud tools such as BigQuery, Google Cloud Storage and Dataproc.
Course 3: Data Transformation in the Cloud (approx. 16 hours): Explores the data journey, common data transformation techniques and the use of a data pipeline to transform high volumes of data.
Course 4: The Power of Storytelling: How to Visualise Data in the Cloud (approx. 24 hours): Focuses on developing skills in the five key stages of visualising data: storytelling, planning, exploring data, building visualisations and sharing data with others.
Course 5: Put It All Together: Prepare for a Cloud Data Analyst Job (approx. 11 hours): Combines and applies knowledge from courses 1-4 in an interactive capstone project and finalises resume updates and interview techniques.

Skills:

Cloud data analysis practices and the cloud data lifecycle
Writing effective queries for BigQuery and Google Cloud Storage/Dataproc
Understanding data lakehouse architecture, data governance and data lineage
Data transformation techniques, data pipelines, ETL/ELT and data mapping
Data visualisation and storytelling, UI/UX principles for dashboard design and Git version control
Assessing feasibility of business requests and troubleshooting data workflow errors

Tools: