Machine Learning Basics - SQL Server 2017, R, Python & T-SQL
3.9 (4 ratings)
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Machine Learning Basics - SQL Server 2017, R, Python & T-SQL

SQL Server, R, Python, TSQL, Data Analysis, Machine Learning Services, Data Science, Data Visualization, Statistics
3.9 (4 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
131 students enrolled
Created by Siddharth Mehta
Last updated 6/2017
English
Current price: $10 Original price: $200 Discount: 95% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 5 hours on-demand video
  • 6 Articles
  • 25 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Perform descriptive and inferential statistical analysis on data
  • SQL Server 2017 Machine Learning Services
  • Visual Studio 2017 Data Science Applications
  • Basics and Intermediate level R and Python with T-SQL in SQL Server Machine Learning Services
  • Number of different advanced Statistical Visualizations in R and Python
View Curriculum
Requirements
  • No prior knowledge of Machine Learning / SQL Server 2017 Machine Learning Services is required
  • Working knowledge of any version of SQL Server is required
  • No prior knowledge of R / Python is required
Description

Top 4 Reasons to take this course:

1) You can learn SQL Server 2017 Machine Learning Services, Microsoft R Open, Python, as well as Statistical Data Science from scratch as well as ask questions directly to a Published Author, Microsoft MVP, and a Senior Technology Architect with more than 14 years of experience who actively practices Business Intelligence, Data Mining, Analytics and Machine Learning in real-world client projects internationally.

2) In a single course, without any prior query development experience - You can learn two programming languages - R and Python and learn how to use it with T-SQL and SQL Server 2017. Also you get to compare the functional equivalent of both languages with reference manuals available in this course.

3) More than 70+ R and Python programming examples are explained in the course using SSMS and Visual Studio 2017 Data Science Applications. These examples range from basics to advanced complex visualizations.

4) Downloadable Course Content:

  • SQL Server Machine Learning Services Reference Guides, Comparison Manuals, CheatSheets
  • Code examples discussed throughout the course
  • Link to a Free EBook.  

Course Description

Machine Learning Basics with SQL Server 2017, R and Python is a  course in which a student having no experience / awareness of Machine Learning / R / Python / SQL Server 2017 Machine Learning Services would be trained step by step to a level where the student is confident to independently work independently with each of them.

Course includes practical hands-on queries with explanation and analysis, and theoretical coverage of key concepts. This is a fast track course to learn practical query development on 2 programming languages i.e. R and Python with T-SQL in the scope of SQL Server, using the latest version of SQL Server - 2017. No prior experience of working with R / Python is required. Even installation of SQL Server 2017 Machine Learning Services, R, Python, and Visual Studio 2017 Data Science Applications is covered in the course.

PS: This course does not teach development of machine learning models and/or algorithms. This course teaches fundamental theory and data science using R and Python in SQL Server Machine Learning Services so that a student can pursue Machine Learning confidently and comfortably.

Who is the target audience?
  • Anyone who wants to build a statistical foundation before pursuing machine learning should enroll in this course
  • Anyone who wants to methodically migrate from database development or business intelligence towards predictive analytics should enroll in this course
  • Anyone aspiring to pursue basics of becoming a data scientist should pursue this course
  • Anyone interested in data science should enroll in this course
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Curriculum For This Course
46 Lectures
04:58:36
+
Instructor Introduction and Course Objectives
2 Lectures 10:08

Instructor Introduction - Siddharth Mehta

Preview 01:43

Course Objectives and Course Pre-requisites

Preview 08:25
+
Introduction to Machine Learning
6 Lectures 55:49

Learn use of Machine Learning Services and its influence on your day to day work.

Preview 06:32

Fundamentals of Machine Learning and Statistics

Fundamentals of Machine Learning & Statistics
18:28

Understand how to learn Descriptive Statistics, Inferential Statistics and Hypothesis Testing

Introduction to Statistical Methods
19:10

Links to essential reference material for learning fundamental statistics for machine learning.

Developing Statistical Literacy
00:36

Learn details of SQL Server 2017 Machine Learning Services Architecture with Architecture Diagram

Machine Learning Services Architecture
05:03

Download Machine Learning Tools and Resources

Machine Learning Resources
06:00
+
Installation and Configuration
5 Lectures 18:38

Learn SQL Server 2017, R, Python and Machine Learning Services Installation

SQL Server 2017 Installation
05:43

Learn SQL Server Management Studio and Visual Studio 2017 Data Science Applications installation.

SSMS and Visual Studio 2017 Installation
03:30

Learn how to test installation of R and Python in SQL Server 2017 Machine Learning Services.

Acceptance Testing of R & Python in SQL Server 2017
06:42

Introduction to R and Python reference documentation, which compares R vs Python functionality side by side.

R vs Python Reference Manuals
02:31

Download SQL Server 2017 Tools and Resources

Resources
00:12
+
Basics of Microsoft R Services in SQL Server 2017
8 Lectures 55:19

Learn fundamentals of R in SQL Server 2017 Machine Learning Services

R Fundamentals
10:07

Learn different types of data structure in R with SQL Server 2017 Machine Learning Services

Introduction to Data Structures in R
04:15

Learn Vectors data structure in R with SQL Server 2017 Machine Learning Services

Vectors
07:49

Learn Matrix data structure in R with SQL Server 2017 Machine Learning Services

Matrix
10:10

Learn Arrays data structure in R with SQL Server 2017 Machine Learning Services

Arrays
05:32

Learn Data Frames data structure in R with SQL Server 2017 Machine Learning Services

Data Frames
08:29

Learn Lists data structure in R with SQL Server 2017 Machine Learning Services

Lists
03:33

Learn to loop data structure in R with SQL Server 2017 Machine Learning Services

Looping Data Structures
05:24
+
Data Ingestion and Analytics in SQL Server 2017 with R
11 Lectures 01:27:56

Learn to load machine learning datasets in R with SQL Server 2017 Machine Learning Services

Loading Machine Learning Datasets
05:24

Learn installation and loading of packages in R with SQL Server 2017 Machine Learning Services

Installing and Loading Packages
04:39

Learn to read data from excel in R with SQL Server 2017 Machine Learning Services

Loading Excel Data
04:48

Learn to read data from web in R with SQL Server 2017 Machine Learning Services

Web Scraping
08:11

Learn to query R data structure in a method similar to T-SQL querying with SQL Server 2017 Machine Learning Services

Querying Data with R - The SQL Way
08:13

Learn how to find help in R with SQL Server 2017 Machine Learning Services and Visual Studio 2017

R Documentation
03:59

Learn how to query data in SQL Server from a R client with SQL Server 2017 Machine Learning Services and Visual Studio 2017

Querying SQL Server from Data Science Applications
06:51

Learn how to use statistical functions in R for Statistical Data Analysis with SQL Server 2017 Machine Learning Services and Visual Studio 2017

Statistical Profiling with R
10:19

Learn how to create distribution plots, kernel density plots and correlation plots in R with SQL Server 2017 Machine Learning Services and Visual Studio 2017

Distribution, Kernel Density, and Correlation
19:08

Learn how to draw visualizations in R for exploratory data analysis with GGPlot2, SQL Server 2017 Machine Learning Services and Visual Studio 2017

Ggplot2 - Exploratory Data Analysis for Machine Learning
16:06

Download R Resources

R Resources
00:18
+
Basics of Python in SQL Server 2017
6 Lectures 41:17

Learn Basics of Python in SQL Server 2017 Machine Learning Services

Python Basics
07:30

Learn Basics of Data Structures in Python in SQL Server 2017 Machine Learning Services

Python Data Structures
06:34

Learn about Arrays in Python with SQL Server 2017 Machine Learning Services

Arrays
11:38

Learn about Series in Python with SQL Server 2017 Machine Learning Services

Series
03:04

Learn about Data Frames in Python with SQL Server 2017 Machine Learning Services

Data Frames
07:17

Learn to query data structures in Python similar to T-SQL querying method in SQL Server Machine Learning Services

Querying Data with Python - The SQL Way
05:14
+
Data Ingestion and Analytics in SQL Server with Python
6 Lectures 28:40

Learn to read and load Machine Learning Datasets in Python with SQL Server Machine Learning Services

Loading Machine Learning Datasets
03:25

Learn to read data from excel in Python with SQL Server Machine Learning Services

Loading Excel Data
02:34

Learn to read data from web in Python with SQL Server Machine Learning Services

Web scraping
08:26

Learn to read data from SQL Server in Python with SQL Server Machine Learning Services

Reading SQL Server Data from Python with RevoScalePy
04:47

Learn to draw statistical visualization in Python with Seaborn package, SQL Server Machine Learning Services and Visual Studio 2017

Statistical analysis with Seaborn and Matplotlib
07:18

Download Python Books and list of important python libraries for machine learning.

Python Resources
02:10
+
Summary
2 Lectures 03:55

Course Summary

Summary
02:41

Discount coupons of my other courses

Bonus Lecture - Discount Coupons
01:14
About the Instructor
Siddharth Mehta
4.1 Average rating
453 Reviews
5,246 Students
7 Courses
Published Author, Microsoft MVP Alumni, Sr. Tech Arch

My name is Siddharth Mehta. I work in the role of a Senior Technology Architect with a multinational IT firm. I have career experience of more than 14 years in the IT industry working with multinational IT companies and Fortune 500 clients. 

Industry Experience

-|- International experience of working across geographies (US, UK, Singapore) for multi-national clients in Banking, Logistics, Government, Media Entertainment, Products, Life Sciences and other domains

-|- I usually work as a lead architect for a portfolio of applications in web, mobile, BI, Analytics, Data warehousing, Reporting, Collaboration, CMS, NoSQL and other categories.

-|- In my present role, I remain responsible for Arch Design, Tech Stack selection, Infra design, 3rd party products evaluation and procurement, and Performance engineering. My primary specialty is Microsoft SQL Server and Microsoft Business Intelligence. I usually work with MS BI integration with cross technologies like Elasticsearch / Lucene, MongoDB, Sharepoint 2013 and 2010, jQuery based framework like Highcharts and GoJS, jQueryMobile, Bootstrap, iOS xCode framework, and many others.

Authoring Achievements

-|- I have authored more than 200 articles and tutorials collectively for online publications like mssqltips, sqlserverperformance, sqlservercental, techrepublic and others.

-|- I have authored / co-authored as well as reviewed books for print-media publication houses like Manning publication, Packt publication.

-|- I have also authored a whitepaper for MSDN Library titled: Bulk report generation using SSIS and SSRS 2008 R2.

Certifications

-|- TOGAF 9 Part I & II certified architect
-|- CITA-F certified architect
-|- HCAHD (Hortonworks Hadoop certified)
-|- MCSD.Net, and MCTS in SQL Server maintenance as well as Developing BI apps using SQL Server
-|- Certified Sr. Technology Architect as well as Digital Architect

Academics

Master of Science with major in Computer Applications and Information Technology