Testimonials for Monika Wahi’s data science courses on LinkedIn Learning are posted here. Read what learners are saying to help you decide if you want to take the courses!
Tag Archives: LinkedIn Learning
Need online curriculum in data science or public health that keeps the learners engaged? I share a links to free resources as well as my hacks to interest high!
Want to get started learning about SAS macros? This blog post provides SAS macros for beginners with video tutorials to walk beginners and code newbies through the basic steps!
Want to get started with SAS, but don’t want the headache? I make it easy for you! Take my FREE course in getting started with SAS ODA!
What is the CEPH, and how does it relate to the other organizations in US public health? This blog post explains the history and function of the CEPH, and how it connects to the rest of Big Public Health in the US.
Getting data for meta-analysis together can be challenging, so I walk you through the simple steps I take, starting with the scientific literature, and ending with a gorgeous and evidence-based Forrest plot!
Monika posts her “data science newbie do-it-yourself starter kit”, with links to cheap or free learning resources for the data science newbie who wants to get started in healthcare analytics.
This is my first blog post in a series of five where I talk about data-related misconduct outlined in the book “Bad Blood”, and provide guidance on how to prevent it.
We experience artificial intelligence all the time on the internet in terms of friend suggestions on social media, internet ads that reflect what we have been searching for, and “smart” recommendations from online stores. But the reality is that even the people who build those formulas cannot usually explain why you were shown a certain […]
This lively panel discussed many topics around designing and implementing machine learning pipelines. Two main issues were identified. The first is that you really have to take some time to do exploratory research and define the problem. The second is that you need to also understand the business rules and context behind the data.
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