NZ$2,387.02 – NZ$2,625.07

Advanced Analytics with R and Microsoft Technologies - Wellington Nov 2017

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Wellington TBA

Wellington, Wellington

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Course Title: Advanced Analytics with R, Microsoft SQL Server, Power BI, and Azure Machine Learning

Length: 3 days

Prerequisite: This course is a beginner to advanced level course. You don't need any prerequisites for attending in this course.

Instructor: Dr. Leila Etaati


You keep hearing about the machine learning and R recently. R become a language for data analysis and machine learning that makes the need for learning it more clearly. Moreover, Microsoft introduces R server as a comprehensive platform for using machine learning and R functionality inside the data analysis tools such as SQL Server 2016 and Power BI.

At this training, you will learn:

Day 1: Azure ML, R basics

In the first day, you will be familiar with basic concepts of Machine Learning in Azure ML and some basic concepts of R in RStudio and Microsoft Visual studio 2015. In Day 1 you will learn;

Azure ML:

  • The main functionality of Azure ML and how to set it up.
  • Different components in Azure environments (Data format conversion, Data input and output, Data Transformation and so forth.
  • How to work with different algorithms, and how to use them for predictive, descriptive and prescriptive analysis.
  • How to evaluate created model and analysis the evaluation output
  • How to enhance the model accuracy via cross validation and feature selection
  • How to create a API from model and how to call the created API in Excel.
  • How to write a Simple R code in Azure ML.
  • Create a simple ML Experiment in Azure ML.

R:

  • The basic of R language.
  • Installing R studio, setting up R server in SQL Server, setting up R in power BI,
  • Main data structure in R, Managing Data with R, Exploring and Understanding Data in R (exploring numeric variable, categorical variable and relationship between variables).
  • How to use some of the main packages in R such as ggplot2, dplyer, sqldf and so forth.
  • The main concepts of basic statistics and how they can be helpful like: mean, median, standard division, and so forth.
  • Practice in R and using some packages


Day 2: R algorithms and Power BI

The main aim of days 2 is to learn some of main algorithms, and understand how they work and how they can solve different type of real life problems. You will familiar with these algorithms and their syntax in R, and how to use them in Power BI. Moreover, you will learn how to embed some R visualization in Power BI.

In day 2 you will learn;

  • How classification algorithm like KNN works. and its relevant code in R.
  • Decision Tree concepts and its relevant R codes
  • How Associative Rules works, and what is the concepts behind it, plus the relevant codes
  • How to write R codes in Power BI for transformation, and also creating new queries
  • How to create interactive R reports in Power BI
  • How to call azure ML API into Power BI
  • Predict numeric data (e.g. using linear regression, multiple regression, logistic regression and so forth)
  • Recommendation (content-based filtering and collaborative filtering).


Day 3: R algorithms and SQL Server 2016

In third day, you will learn how to bring analytics and intelligence using SQL server 2016. Moreover, you will also learn some other important machine learning algorithms.

In Day 3 you will learn:

  • Concepts and R codes for
  • Neural Network algorithm
  • Time series algorithm
  • Regression algorithm
  • Recommendation (content-based filtering and collaborative filtering). Moreover, you will learn how to use machine learning in SQL Server 2016 and in SSRS.
  • Using R SQL Server 2016 for rung the R code inside the SQL Server scripts will be shown.
  • The general procedure for creating R diagram in SSRS will be discussed
  • Two different scenarios will be discussed in class so audience will understand how to create a machine learning process in SQL Server 2016.


This course is full of hands on labs, and you will experiment all examples through real-world demos. At the end of the 3-day training course, you will be able to use techniques and concepts of this training in your Analytics challenges.

Instructor: Dr. Leila Etaati

leila_web_pass

Dr. Leila Etaati gained her PhD in University of Auckland. She is world well-known speaker in Machine Learning and Analytics topics, and spoke in world's best international conferences in Data Platform topics, such as; PASS Summits, PASS Rally, SQL Nexus, Microsoft Ignite, and so on. She has more than 10 years experience in Data Mining and Analytics. She is also Microsoft Most Valuable Professional (MVP) because of her dedication on Microsoft Analytics and Machine Learning technologies. She writes blog posts in RADACAD and also publishes YouTube videos in our channel. She also is an invited lecturer in universities such as University of Auckland, and Unitec, and some other universities. She worked in many industries including banking financial, power and utility, manufacturing, tourism, and so on.

Course Details:

http://radacad.com/advanced-analytics-training

Group discounts:
For group discounts of 3+ people from same company, please contact us.

Location: Auckland, New Zealand. Exact address; TBD


Cancellation:

Cancellation up to 5 weeks before the event: fully refund minus administration fee ($50) and credit-card processing fees (if applicable).

Cancellation from 5 weeks to 2 weeks before the event: 50% cancellation charge, 50% refund

Cancellation from 2 weeks before the event: 100% cancellation charge, 0% refunded.

In case that cancellation happens from RADACAD you will be offered to choose either full refund or transfer to another date.

Transfer:

Transfer fee to another event date* (up to 2 weeks before event): Transfer fee $125

Transfer fee to another event date* (from 2 weeks to 1 day before event): Transfer fee $400

Transfer fee at the day of event*: $650

*transfer can be done only once, and it can be only transferred to another date not later than 6 months from the original event.

No Show:

No fee will be refunded for no show.

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