README.Rmd

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output:
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    variant: markdown_github
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knitr::opts_chunk$set(
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# zementisTutorials

[![Build Status](https://travis-ci.org/alex23lemm/zementisTutorials.svg?branch=master)](https://travis-ci.org/alex23lemm/zementisTutorials)
[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/alex23lemm/zementisTutorials?branch=master&svg=true)](https://ci.appveyor.com/project/alex23lemm/zementisTutorials)

## Overview

zementisTutorials offers several tutorials around data science, Zementis, and PMML.

## Installation

You can install zementisTutorials from github with:

```{r installation, eval=FALSE}

# install.packages("devtools")
devtools::install_github("alex23lemm/zementisTutorials")
```

## Usage

The following courses are currently offered via zementisTutorials and can be executed using the learnr package:

**De-mystifying Data Science** 

The course introduces the data science process and common analytics terminology hands-on using R. Students will solve a real-world data science problem on their own. The course is completely self-contained and no prior analytics or R knowledge is required.

```{r eval=FALSE}

learnr::run_tutorial("data_science_introduction", package = "zementisTutorials")
```


**Zementis Introduction**

Basic introduction to Zementis Server from an end-user perspective. Students will learn how to deploy a ML model to Zementis Server and how to score new data using file uploads, the embedded REST client, an external REST client, and the Zementis Excel Add-In.

```{r eval=FALSE}

 learnr::run_tutorial("zementis_introduction", package = "zementisTutorials")
```