Learning SQL Server Machine Learning Services
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Learning SQL Server Machine Learning Services

Learn the basics of SQL Server Integration Services (SSIS) - with Practical Activities.
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0.0 (0 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
9 students enrolled
Created by Samire Banballa
Published 8/2020
English
Current price: $69.99 Original price: $99.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 2 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • You will know the different stages in Lifecycle of a Data Science Project
  • You will know how to perform a simple installation of SQL Server along with Machine Learning Services
Course content
Expand 29 lectures 02:10:53
+ Learning SQL Server Machine Learning
29 lectures 02:10:53
Make the most of the exercise files
02:31
What is Machine Learning Services (MLS)
03:39
Enable script execution in SQL Server
04:42
R data types
04:36
Variables in R
06:10
Import a data set from SQL Server
02:35
Query data into an R data frame
04:50
Output data to a result set
05:24
Select values from a data frame
06:36
Create a data frame from vectors
04:59
Challenge- Import data
00:50
Solution- Import data
04:49
Sample a data set
06:21
Parameterize a stored procedure
05:23
Challenge- Write a stored procedure
00:40
Solution- Write a stored procedure
06:01
View installed packages
04:19
Produce graphs and plots
06:50
Create a bar plot
04:53
Challenge- Create a pie chart
01:03
Solution- Create a pie chart
13:47
Install MLS on a standalone server
05:41
Add development tools to a client
04:56
Install and configure RStudio
03:51
Next steps
01:20
Requirements
  • Basic SQL Server Knowledge
Description

Data Science, Big Data, Machine Learning and Artificial Intelligence, are the areas of technology that have been significantly evolved over the last few years. These technologies, are already heavily used by many organizations, in order to efficiently solve complex problems. Among other, they are used for predicting patterns based on large data sets and thus transform raw data into meaningful knowledge.

Examples where Data Science and Machine Learning are used, include: email SPAM and malware filtering, product recommendations on eCommerce websites, online fraud detection, early prediction of diseases and much more.

To this end, knowing Data Science and Machine Learning, is surely a competitive advantage in the job market, since as we evolve as a society and economy, these technologies are being used even more, for helping Business, Healthcare and many other sectors in our everyday lives.

Since all these technologies rely on large sets of data, also known as "Big Data", combining these technologies with a powerful Data Platform such as SQL Server, can further enhance the process of learning from data.

SQL Server, via its Machine Learning Services offering, helps you to easily implement Data Science and Machine Learning projects, directly against your data, either structured, or unstructured, or both.

Via my course "Introduction to Data Science and SQL Server Machine Learning", you will get introduced to Data Science and SQL Server Machine Learning Services. Among other, you will learn what Data Science is and what is the Data Science Lifecycle. Moreover, you will learn about SQL Server and its Machine Learning Services offering and see live demonstrations of installing the required services for getting started, as well as of how you can run Python and R code from within SQL Server.

Then, we will talk about SQL Server's development tools, which can be used for implementing Data Science projects on the platform and finally we will perform a simple Data Science project in SQL Server, where we will create, train and score a model, for predicting values based on the data input.


Who this course is for:
  • People who are interested in getting started with Data Science and Machine Learning