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Data Science Training - Module 3: Advanced Data Science with Microsoft Serv...

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Course Title: Data Science and Advanced Analytics with Microsoft Technologies


From 1 to 7 days (Lecture + Labs): depends on the modules you enroll.

Delivery method:

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 Microsoft Advanced Analytics field on the planet from one to seven 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 some basic concepts for Machine Learning, Predictive and Descriptive analytics. You learn how to write R codes for the aim of data wrangling, data modeling, data visualization, and machine learning. Moreover, you will learn how to use custom AI tools like Azure Machine learning for creating your desire model, deploy it and use it as web service in other applications and scenarios like the Internet of Things (IoT). You will learn about how to use R in a dashboard, how to R in the cloud and on-premises storage. You will learn how to use pre-build AI tools like Bot and cognitive services to create smart report and applications. 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 scientist, data analyst, business intelligence developer, or data architect, 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 3: Advanced Data Science with Microsoft Services – 2 days course

This training is designed for data science, data analysis and who want to do machine learning by writing R or Python code. This course will start with some explanation of different machine learning algorithms and approaches. Then, some discussion on basic statistical analysis will be provided such as probability, factor analysis, hypothesis testing and so forth. Then the process of machine learning from business understanding, data cleaning, feature selection, model selection, split data for testing and training, evaluating the created model and finally developing and visual the trained model and analyzing the result will be presented.

For predict analysis algorithms such as decision tree, boosted decision tree, decision forest will be explained. The concept and how they work will be explained. Then how to set parameters for each of them will be illustrated. Also, the process of data preparation for each of these algorithms will be discussed. Finally, the related code for writing this algorithm in the cloud will be explained. The same process will be done for the descriptive algorithms such as clustering.

In this two days training, the audience will learn some deep concepts for machine learning, data analysis, main algorithms for predictive, descriptive and statistical analysis using R, R in Power BI and SQL Server.

The training includes but not limited to topics below:

3.1: Machine Learning Basics

The main concepts, life cycle and best practice of doing machine learning with Microsoft product will be explained.

  • The main Predictive, descriptive and Prescriptive analysis will be explained
  • What are the main stages of machine learning cycle will be illustrated
    • Business understanding
    • Data cleaning and feature selection
    • Model Selection
    • Data training and testing
    • Evaluating measures
    • Writing codes

3.2: Predictive Analytics

In this section, the audience will learn some of the algorithms such as Decision tree, Decision Forest, regression and SVM for the aim of predictive analytics. The main concepts of these algorithms will be explained, and the related R or Python code will be shown. How to analysis the trained model and set up the parameters also will be discussed. Finally, how to evaluate the result will be explained.

  • What is classification and how to evaluate a classification result using confusion Matrix
  • Decision Tree, Decision Forest, and Boosted decision tree
  • SVM and KNN
  • How to do classification using decision tree in SQL Server 2016
  • How to classify by decision forest in Power BI
  • The main code for SVM and KNN and how to compare the results by writing R codes

3.3: Descriptive Analytics

Descriptive analytics is an unsupervised learning approach. In this part, the audience will be familiar with some of the main algorithms for descriptive analytics from text mining, clustering and, Market basket analytics.

  • The main concepts for clustering and k-mean clustering will be explained. Also, the process of identifying the number of clusters will be explained
  • The main process for text mining for the aim of sentiment analytics, keyword extraction, and language detection
  • How to do clustering in Power BI and how to use Power BI visual to analysis cluster
  • What is market basket analysis and what is support, confidence and lift measure
  • How to do Market basket analysis with R and rules package and how to show the result in Power BI visualization tools
  • Text mining concepts and main concepts

3.4: Forecasting

Forecasting is one of the main approaches for time series. The main concepts of the time series will be explained and how to decompose time series, how to use exponential smoothing and ARIMA for forecasting the time series data. Audience will learn

  • What is the forecasting
  • How to decompose time series data
  • What is Exponential smoothing and how to do it in RStudio and Power BI
  • What is ARIMA and how to do it in Power BI

In-Person Training;

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:

Online Training;

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.

Who Attended RADACAD Training Courses

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 Show:
No fee will be refunded for no show.





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