> For the complete documentation index, see [llms.txt](https://docs.launchboard.app/industry-connect-2024/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.launchboard.app/industry-connect-2024/founding-cohort/google-data-analytics-pacing.md). # Google Data Analytics Pacing Successfully completing the eight Coursera courses for the [Google Data Analytics Professional Certificate](https://www.coursera.org/professional-certificates/google-data-analytics) earns you a professional certificate issued through Credly, like [this one](https://www.credly.com/badges/98de3211-7c0c-4316-9d96-c5c2ceb7c617). While you can complete the courses at your own pace, we have outlined a pacing guide to help ensure you make diligent progress towards completion. ### Your Learning Strategy Develop a learning strategy that works for you. Consider the points below as you plan your work. * **What days of the week and times of the day do you intend to make progress?** Consider when access to a computer and the internet is consistent, and recognize where the environment (e.g. noise-level and table space) is conducive to getting things done. * **Who are your advocates?** Of course the Industry Connect team is advocating for you, but you will want others to cheer you on with your effort and progress in this program. Plan to share your progress with a family member, coach, or teacher. They will likely remind you to stick with it and see it through. * **Don't hesitate to find help.** Be quick to ask for help on Slack or during our Friday meetings -- whether you have technical questions or you are facing some other hurdle. Lean on your advocates for help and encouragement. ### Pacing Schedule Remember, if you fall behind, you can always catch-up. These are not hard deadlines.

Course	Target Completion Date
Coursera Course 1 (~27 hrs) Foundations: Data, Data, Everywhere	2/23/24
Coursera Course 2 (~27 hrs) Ask Questions to Make Data-Driven Decisions	3/15/24 👕
Coursera Course 3 (~32 hrs) Prepare Data for Exploration	4/5/24
Coursera Course 4 (~32 hrs) Process Data from Dirty to Clean	5/10/24
Coursera Course 5 (~32 hrs) Analyze Data to Answer Questions	5/31/24
Coursera Course 6 (~32 hrs) Share Data Through the Art of Visualization	6/21/24
Coursera Course 7 (~32 hrs) Data Analysis with R Programming	7/12/24
Coursera Course 8 (~27 hrs) Google Data Analytics Capstone: Complete a Case Study	7/26/24 💻

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