Learn how to do forecasting using data science in 2 hours

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Learn how to do forecasting using data science in 2 hours

Course Details

Cost

$8/mo

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  • On demand

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Skillshare online courses
In Skillshare’s unique philosophy, everyone is a teacher, and everyone is a learner. Rather than a traditional lecture format, courses are offered within a global online learning community in which learners collaborate and learn by doing. Instructors are industry leaders who share their skills with anyone who wants to learn. No credits are offered. Founded by online entrepreneurs Michael Karnjanaprakorn and Malcolm Ong, Skillshare’s online “campus” was launched in April 2011. Its catalog h...
In Skillshare’s unique philosophy, everyone is a teacher, and everyone is a learner. Rather than a traditional lecture format, courses are offered within a global online learning community in which learners collaborate and learn by doing. Instructors are industry leaders who share their skills with anyone who wants to learn. No credits are offered. Founded by online entrepreneurs Michael Karnjanaprakorn and Malcolm Ong, Skillshare’s online “campus” was launched in April 2011. Its catalog has grown from 15 to more than 250 online courses that cover creative arts, entrepreneurship, branding and marketing, lifestyle and technology. The School of MakeOurMark, with courses in photography, illustration and tattooing, was launched in October 2013, and the School of Design went live the following month. Among the instructors who have taught courses are Seth Godin, founder of online marketing firm Yoyodyne, who teaches a class on entrepreneurship; DJ Young Guru, who leads a course on mixing and recording; and actor, writer and director James Franco, whose course focuses on screenwriting for short films. You can begin a Skillshare collaboration by taking an introductory course in a particular area to learn, for example, the fundamentals of Photoshop and expand your knowledge with a five-part, in-depth Photoshop series.

Provider Subject Specialization
Arts & Design
Business & Management
32 reviews

Course Description

Imagine you want to predict sales, purchases, temperatures, or stock prices using a rigorous approach. Until recently, you had to be well versed in advanced mathematics and programming. Luckily, the tools have become cheaper and much easier to understand for the novice. You no longer need to be an seasoned data scientist or machine learning pro.

So, what can be forecasted? You can apply these techniques to any phenomenon you observe. Intuitively the predictions and models you generate will be "better" the more "structure" your phenomenon has. You cannot for example forecast the roulette results, because they are totally random! But you can probably forecast quite well your sales, salary, customers, expenses, website visitors, etc.

In this class, we will review how to use R (a leading free statistical software) for doing quite advanced forecasting, ignoring all the complicated statistical jargon. 

...

Imagine you want to predict sales, purchases, temperatures, or stock prices using a rigorous approach. Until recently, you had to be well versed in advanced mathematics and programming. Luckily, the tools have become cheaper and much easier to understand for the novice. You no longer need to be an seasoned data scientist or machine learning pro.

So, what can be forecasted? You can apply these techniques to any phenomenon you observe. Intuitively the predictions and models you generate will be "better" the more "structure" your phenomenon has. You cannot for example forecast the roulette results, because they are totally random! But you can probably forecast quite well your sales, salary, customers, expenses, website visitors, etc.

In this class, we will review how to use R (a leading free statistical software) for doing quite advanced forecasting, ignoring all the complicated statistical jargon. 

Statistical forecasting (aka time series analysis), is both a rigorous science and an art. Several experts, working with the same data, could potentially produce different forecasting models, each with its own pros/cons. Over the past years, there has been a plethora of automatic forecasting techniques which attempt to reduce the "human factor" of the approach (choosing one model among several ones). These techniques have gained a lot of popularity within companies doing forecasting on a large scale, such as banks, insurers, etc. But certainly, this has opened lots of possibilities for non-experts requiring to do forecasting.

After finishing this class, you should be able to: load data into R, produce a statistical forecasting model, validate the predictions and model accuracy, and work with those predictions.

This class will aim to teach the essential concepts behind these techniques, avoiding any mathematical and statistical concept, as much as possible. The list of topics will be roughly:

  1. Quick and direct introduction to R
  2. Reading data into R
  3. Essential introduction to time series and forecasting
  4. Forecasting in R. Leveraging the automatic methods
  5. Some forecasting
  6. Want to learn more? Some suggestions
  7. Exercise
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