Course Title: Power BI from Rookie to Rock Star
From 1 to 9 days (Lecture + Labs): depends on the modules you enrol.
In-Person or Online: Check the schedule of upcoming courses.
Type of training:
Public or private (contact us for more details)
The well-known worldwide training in Power BI field, and the most comprehensive Power BI training on the planet from one to nine days of training delivered by the well-known experts and MVPs, authors of books, and speakers of many conferences themselves. In this training course, you will learn Power BI from beginner to advance. You will learn how to use Power BI for simple data analysis situations as well as complex business intelligence scenarios. You will learn about Power BI Components such as Power Query (Get Data and Transform), Modelling and DAX, Visualization, Power BI Desktop as the main tool, Power BI Service, Gateway configuration, and architecture. You will learn all the concepts with live demos. Expect learning best practices with great scenarios in this course. This course is designed in separate modules based on the type of audience. If you are a data analyst, data wrangler, data modeler, or data architect, or even a data scientist, this course has many things to teach you all.
This course is delivered to thousands of people all around the world, check out only a few of the recommendations at the bottom of this page, and check some of our clients.
Instructor: Dr. Leila Etaati
Our trainer is the world well-known name in the Microsoft Data Science field. Leila Etaati is Microsoft AI, and Data Platform (Most Valuable Professional) focused on AI and BI Microsoft technologies; Microsoft has awarded her MVP because of her dedication and expertise in Microsoft BI technologies from 2016 till now, she is one of two AI MVP in Australia and New Zealand. She is a speaker in world’s best and biggest Microsoft Data Platform, BI and Power BI, AI conferences such as Microsoft Ignite, Microsoft Business Applications Summit, Microsoft Data Insight Summit, PASS Summits, PASS Rallys, SQLBits, TechEds, and so on. She is the author of some books on this topic, and she has more than 11 years’ experience in the Microsoft BI technologies and Data science. Leila is the co-founder of RADACAD and a consultant for more than seven years.
Advanced Analytics with Microsoft Technologies
This is the most comprehensive course for Microsoft Advanced Analytics and Data Science on the planet which split into modules. You can enroll in any of these modules separately or take the whole course. Modules designed independently, which means each module can be taken regardless of the order of modules. Here are a list and detailed agenda of each module:
- Module 1: Power BI for Data Scientists (2 days)
- Module 2: Data Science with Microsoft Cloud (2-days)
- Module 3: Advanced Data Science with Microsoft Services (2-days)
- Module 4: AI and Cognitive Services in Applications (1-day)
Module 1: Power BI for Data Scientists – 2 days course
This training is designed for people who want to do Machine Learning (ML) inside Power BI. In this training, you will learn different ways to use R languages for the aim of machine learning, visualization, data cleaning in Power BI.
In this two days training, you will learn some main concepts of machine learning. You will learn some basics of R language and How to use it in Power BI visualization, Power Query (data wrangler part of Power BI), and how to use it for creating custom visual. Also, the training will cover some of the main algorithms for machine learning such as Predictive analytics (Decision-Tree, Decision Forest, KNN, SVM), Descriptive analysis (Clustering, Market Basket Analysis) and Forecasting (Time Series). Finally the pre-build advanced analytics visual in Power BI Marketplace will be explained and how to use them will be clarified.
At the end of this training, you will able to write R code in Power BI report and Power Query, create custom visual with the help of JSON codes and R scripts,
The training includes but not limited to topics below:
1.1: Introduction to R
R is a statistical language that has been used for many years for the aim of machine learning, statistical analytics, data wrangling, data visualization and so forth. There is a possibility to embed R codes inside Power BI to create more smart applications. In this module, we will go through the basics of R language and introduce some of the main R functions and commands such as statistical summary, package concepts, read data from SQL Server, Azure and so forth, visualization command, loop, and so forth. You will see some demos and introduction about:
- Introduction to R Language: What is R?
- RStudio; The First Experience
- Install Rstudio
- RStudio Environment
- R basic Command
- Data Structure such as Data Frame, Vector, and Lists
- Import Data from the local machine, SQL Server, Azure Data Lake and so forth.
- Check the Statistical Summary of data
- Check the Structure Summary of Data
- Use existing Package and how to Install New Packages
- Create Basic Chart such as Histogram and Box Plot for better Understanding data
- And some other useful commands
1.2: Introduction to Machine Learning
In this section, some introduction to Machine learning will be provided. The audience will learn what Artificial Intelligence is, what is Machine Learning, who is Data Scientists, who is data Analyst, and What is Deep learning. Also, some explanations on what descriptive and predictive analytics are will be provided. In this module audience will learn:
- What is Descriptive Analytics
- What is Predictive Analytics
- What is Forecasting
- What Languages exist for Machine Learning and what is the main difference
1.3: Use R in Power BI Report for Visualization
Power BI consists of different components such as Power BI visualization, Power Query, Power BI services and so forth. Power BI visualization has lots of interesting and useful chart to visual data and creates business reports. However, customer need can be varied; each customer may need different visual that not available in Power BI visualization pan. In this module
- How to set up R in Power BI visualization will be explained
- How to use R visual in Power BI will be shown
- R editor in Power BI will be explained, and all feature such as setting, how to debug code in RStudio, and how to run will be explained.
- How to draw some basic charts like Histogram, Boxplot, table (gride) will be shown.
- The audience will see how to use the ggplot2 package for drawing the more complex visualization
- They will learn how to create a table chart with four, and five dimensions
- The audience will learn how to create different bar chart, polar chart by writing simple R codes
- How to create a colorful chart in Power BI using R will be explained
1.4: Use R in Power Query
Power Query is one of the main important components in Power BI that is used for data cleaning and wrangling. Power Query is a comprehensive component for extracting data from different locations, clean the data and load it (ETL). The main language behind the scene of Power Query is M. In this module, you will see how we can use R scripts in Power query for storing data in local machine or other devices, creating loops, normalizing the data, and Machine Learning.
The content that you will learn in this module includes but not limited to;
- How to access the R editor and how to use it
- How to store the dataset from Power Query in a local machine
- How to access the R editor in Power query and how to run the R scripts
- How to use R to apply a loop on a dataset/column
- How to expand the regular expression language
- How to access the R codes in Power query advanced editor
1.5: Predictive Analytics in Power BI
Some explanation on what predictive analytics is will be provided. The main algorithms for classification and regression will be introduced. The main concepts of some algorithms for classification and regression such as Decision tree, KNN, linear and non-linear regression will be explained.
The content that you will learn in this module includes but not limited to;
- What is predictive analytics and what algorithms we use for predictive analytics
- Main concepts for the decision tree, SVM, regression, and KNN will be provided
- How to use decision tree algorithms (with related R codes) for the aim of classification in Power Query will be explained
- How to use regression algorithm for predicting a value in power Query will be shown
- How to parametrize the algorithm in Power Query for future use will be explained
1.6: Descriptive Analytics in Power BI
In this module, a brief explanation of what is descriptive analytics, what is clustering, what is market basket analytics will be provided. Audience will learn
- Basic concepts for clustering and market basket analytics
- How to write R scripts and what function has been used
- How to do Clustering in Power BI visualization and Power Query
1.7: Time series with R in Power BI
Forecasting is a popular and useful trend in many industries. Time series is an algorithm that has been used for forecasting the trend, pattern and future value for their sales, profit and so forth. In this module below item will be presented
- What is Time series and what are the main concepts behind it
- How to write R scripts for time series decomposition, forecasting using exponential smoothing and so forth.
- How to do forecasting in Power BI report and Power Query
1.8: Pre-build Advanced Analytics Visualization
Microsoft provides lots of interesting advanced analytics chart in the marketplace for Power BI users. This charts able end user to use them for analytics without writing any R scripts.
- How to access the Power BI advanced analytics visualization in Marketplace
- What is decision tree visualization and how to use it
- What is time series visualizations?
- How to use clustering and correlation analytics visualization
1.9: Create Custom Visual with R and JSON Scripts
There is a possibility to expand the visualization in Power BI with creating custom visual. These visuals have some difference from what we have in section 1-3. These custom visuals can be shared with others easily without disclosing the code behind them. These visualizations can be put in a list of visual for other people in the company. In this section.
- How to create custom visual with R
- How to use the Power BI template for it
- How to create a proper setting and so forth
Our Power BI in-person training will be held in high-quality venues with the recommendation for hotel bookings for attendees. There will be special group rating fee as well as early bird and past attendees discount. for the schedule of our in-person training follow this link:
We run online training with GoToWebinar and GoToTraining applications. These applications provide a highly reliable communication channel between instructor and attendees. For the schedule of our online training follow this link:
Use the letter written for your boss to convince him/her to pay for your Power BI Training course
Check Schedule of upcoming events here
Check cancellation policies and rates here
What others say about the training and trainer
Kenny McMillan, Sports Physiologist / Data Analyst, Frankfurt, Germany:
I attended RADACADs “Advanced Analytics” course recently in Frankfurt in May 2017. Being a regular user of Power BI (with a science background ) the course was extremely helpful in showing me how to incorporate R data visualizations into Power BI dashboards and for introducing me to machine learning using the Microsoft ML Studio. Leila is an excellent and extremely knowledgeable instructor and explained complex data analytical concepts and methodologies in an easy-to-understand manner. I thoroughly recommend this course to anyone who wants to expand their data analytical skills and knowledge.
Martin Catherall (Microsoft Data Platform MVP):
As part of SQL Saturday Auckland 2016 I attended an “Analytics with Power BI and R.” pre-con with Leila. Leila took the class’s knowledge from rudimentary to competent in a day. We first looked at R, the language and the software. Once these skills were obtained we started to look at Power BI and the integration that it has with R. We worked through a few examples and Leila answered all of the class’s questions and offered to provide supplementary material for some of the more advanced questions. I left the class feeling that my R and Power BI knowledge was at a competent level and ready to dive into some of the more advanced material that Leila provided.
Cancellation up to 5 weeks before the event: full 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.
Transfer fee to another event date* (up to 2 weeks before the event): 25% of the standard price of the event to transfer
Transfer fee to another event date* (from 2 weeks to 1 day before the event): 40% of the standard price of the event to transfer
Transfer fee at the day of event*: 60% of the standard price of the event to transfer
*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 fee will be refunded for no show.