Google Advanced Data Analytics study materials
Google Advanced Data Analytics study resources

Google Advanced Data Analytics study plan

Google Advanced Data Analytics · Give each week a clear focus.

8 weeks · About 5 hours per week

Week 1

Data projects, communication and accountable business value

  • Review Data projects, communication and accountable business value using the mapped guide and reference terms.

  • Attempt relevant questions before reading answers and explain the distinction or calculation.

Your checkpoint

A checked study log for Data projects, communication and accountable business value, with supporting reasoning and unresolved questions.

Week 2

Python and dataframe reasoning for applied analytics

  • Review Python and dataframe reasoning for applied analytics using the mapped guide and reference terms.

  • Attempt relevant questions before reading answers and explain the distinction or calculation.

Your checkpoint

A checked study log for Python and dataframe reasoning for applied analytics, with supporting reasoning and unresolved questions.

Week 3

Statistical inference, regression and model assumptions

  • Review Statistical inference, regression and model assumptions using the mapped guide and reference terms.

  • Attempt relevant questions before reading answers and explain the distinction or calculation.

Your checkpoint

A checked study log for Statistical inference, regression and model assumptions, with supporting reasoning and unresolved questions.

Week 4

Intelligent search, learning and evaluation

  • Review Intelligent search, learning and evaluation using the mapped guide and reference terms.

  • Attempt relevant questions before reading answers and explain the distinction or calculation.

Your checkpoint

A checked study log for Intelligent search, learning and evaluation, with supporting reasoning and unresolved questions.

Week 5

Data, Databases, and Information Retrieval

  • Review Data, Databases, and Information Retrieval using the mapped guide and reference terms.

  • Attempt relevant questions before reading answers and explain the distinction or calculation.

Your checkpoint

A checked study log for Data, Databases, and Information Retrieval, with supporting reasoning and unresolved questions.

Week 6

Identity, access and cryptographic protection

  • Review Identity, access and cryptographic protection using the mapped guide and reference terms.

  • Attempt relevant questions before reading answers and explain the distinction or calculation.

Your checkpoint

A checked study log for Identity, access and cryptographic protection, with supporting reasoning and unresolved questions.

Week 7

Data projects, communication and accountable business value & Python and dataframe reasoning for applied analytics & Statistical inference, regression and model assumptions & Intelligent search, learning and evaluation & Data, Databases, and Information Retrieval & Identity, access and cryptographic protection

  • Apply the cases before reading model responses.

  • Retest recurring errors with a mixed set and compare preparation with the actual syllabus.

Your checkpoint

A checked study log for Data projects, communication and accountable business value, Python and dataframe reasoning for applied analytics, Statistical inference, regression and model assumptions, Intelligent search, learning and evaluation, Data, Databases, and Information Retrieval, Identity, access and cryptographic protection, with supporting reasoning and unresolved questions.

Week 8

Data projects, communication and accountable business value & Python and dataframe reasoning for applied analytics & Statistical inference, regression and model assumptions & Intelligent search, learning and evaluation & Data, Databases, and Information Retrieval & Identity, access and cryptographic protection

  • Apply the cases before reading model responses.

  • Retest recurring errors with a mixed set and compare preparation with the actual syllabus.

Your checkpoint

A checked study log for Data projects, communication and accountable business value, Python and dataframe reasoning for applied analytics, Statistical inference, regression and model assumptions, Intelligent search, learning and evaluation, Data, Databases, and Information Retrieval, Identity, access and cryptographic protection, with supporting reasoning and unresolved questions.

Milestones

Week 2: Explain the principal concepts using evidence rather than memorized option positions.

Week 5: Apply subject concepts to cases and identify assumptions and limits.

Week 8: Review mixed performance and the exact current qualification requirements.