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What you’ll learn:
Data Science Practices test 01
Data Science Practices test 02
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Data Science grew through our experiences with Business Intelligence BI, a field that became popular in the 1990s. However, the last 20 years have seen unprecedented improvement in our ability to take action using Artificial Intelligence. As we adopt the BI methodologies to AI deployments, how will these methodologies morph to add considerations needed for model deployment, and machine learning?
Today’s Data Science work deals with big data. It introduces three major challenges:
- How to deal with large volumes of data. Data understanding and data preparation must deal with large-scale observations about the population. In the world of BI on small samples, the art of data science was to find averages and trends using a sample and then project it using universal population measures such as census to project to the overall population. Most of the big data provide significant samples where such a projection may not be needed. However, bias and outliers become the real issues
- Data is now available at high velocity. Using scoring engines, we can embed insights into high velocity. Data Science techniques offer significant real-time analytics techniques to make it possible. As you interact with a website or a product, the marketer or services teams can provide help to you as a user. This is due to insight embedded in high velocity.
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What will you need to succeed in this Exam?
- Excel, Statistics and Python knowledge is required though – you don’t need to be an expert but the basics need to be set (though there are refresher sections in this course!)
- NO Android, Java, Swift, or C knowledge is required!
What does this course offer you?
- This course consists of 2 practice tests.
- The practice test consists of 20 questions, timed at 30 minutes
- The questions are multiple-choice.
- Every question is associated with a knowledge area
- The answers are randomized every time you take a test
- Once the test was taken, you will get an instant result report with categories of strength to weakness.
- You can retake the tests over and over again as and when it suits you.
I’d be very happy to welcome you to the course!
Who this course is for:
- Beginner or advanced data reletated student or employe.
- Statistician, Data Scientics, Data Analysts, Data Mining
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