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30-Day Money-Back Guarantee

This course includes:

  • 2.5 hours on-demand video
  • 13 articles
  • 7 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Data Science RapidMiner

Data Science : Master Machine Learning Without Coding

Learn Fundamentals Of Data Science & Machine Learning With Rapidminer (No Coding). Dataset & Solutions Included.
Rating: 4.3 out of 54.3 (517 ratings)
4,251 students
Created by Ram Prasad
Last updated 10/2018
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Build predictive models using machine learning algorithms without writing a line of software code
Curated for the Udemy for Business collection

Course content

14 sections • 63 lectures • 2h 37m total length

  • Preview00:32
  • Preview00:37
  • Preview03:00
  • Preview01:07
  • Preview03:20

  • Preview02:40

  • Rapidminer Development Environment Introduction
    03:04
  • Operators, Extensions, Repository, Parameters, Help
    05:10
  • Let's Build Our First Basic Process - Introduction
    01:00
  • Let's Build Our First Basic Process - Hands On
    07:23
  • End of Rapidminer Basics
    00:25

  • Before We Start
    00:55
  • Downloading the Data for your First Regression Machine Learning Model
    00:12
  • What Is This Dataset?
    00:53
  • Importing Data
    02:28
  • Partitioning the Data
    04:55
  • Building Multiple Linear Regression Machine Learning Model
    01:41
  • Output Results of Multiple Linear Regression Machine Learning Model
    00:54
  • Validating Performance of Multiple Linear Regression Machine Learning Model
    04:06
  • Saving your Work
    00:15
  • Conclusion - First Simple Regression Machine Learning Model
    00:26

  • Downloading the Second Dataset With Issues
    00:09
  • What Is This Dataset?
    00:35
  • Importing Data and Identifying Issues
    04:24
  • Eliminating Fields That Are Not Useful
    01:47
  • Identifying and Removing Outliers
    06:22
  • Convert Nominal Data Fields to Numerical Data Fields
    05:04
  • Building Multiple Linear Regression Machine Learning Model on Cleaned Data
    04:00

  • Let's Test Your Knowledge
    3 questions

  • Downloading the Data for your First Classification Machine Learning Model
    00:07
  • What Is This Data?
    00:48
  • Importing The Data and Identifying The Issues
    04:12
  • Convert Data From One Type To Another
    04:11
  • Handling Missing Values In A Field
    02:39
  • Set Label Role Using Operator
    01:40
  • Eliminate Fields That Are Not Useful
    01:18
  • Partition Data and Build Classification Machine Learning Model
    05:12
  • Output Results of Classification Machine Learning Model
    01:05
  • Validating Performance of Classification Machine Learning Model
    08:50
  • Additional Reading
    01:50
  • Optimizing the Performance of our Classification Machine Learning Model
    07:22
  • Additional Reading
    00:30
  • Conclusion - Classification Machine Learning Algorithm
    01:26

  • Let's Test Your Knowledge
    3 questions

  • What is Clustering and How is it different from Regression or Classification?
    01:15
  • Download Data for your Clustering Model Example
    00:07
  • Story behind the data
    01:44
  • What is K-Means Clustering?
    02:56
  • Let's Build our Clustering Algorithm to segment patient data
    04:39
  • Download Data for New Patients
    00:12
  • Let's Build our Clustering Algorithm to segment patient data - Continued
    03:36
  • Conclusion
    00:28

  • Let's Test Your Knowledge
    3 questions

Requirements

  • Able to use a Windows computer and install software on it
  • High school math

Description

Learn To Master Data Science And Machine Learning Without Coding And Earn a 6-Figure Income 

 

Why Data Science and Machine Learning are the Hottest and Most In-Demand Technology Jobs.

 

Data Scientist was recently dubbed “The Sexiest Job of the 21st Century” by Harvard Business Review, and for good reason! 

 

If you’re looking for a fast and effective way to earn a 6-figure income without spending thousands of dollars in training, keep reading to learn about this revolutionary Udemy course. 

 

Glassdoor reports that Data Scientist was named the “Best Job in America for 2016,” which was based on the huge amount of career opportunities and 6-figure average salary.  Business media from Forbes to The New York Times also frequently report about the increasing demand for data scientists.

 

Why is this great news for you? 

The sudden increase in demand for Data Scientists has created an incredible skills gap in the job market.  According to a McKinsey Report, by the end of 2018 the demand for them is expected to be 60% higher than the available talent! 

Machine Learning is the Key to Your High-Earning Future

Leading companies understand that Machine Learning is the future, and are investing millions of dollars into Machine Learning Research. 


Machine Learning is the subset of Artificial Intelligence (AI) that enables computers to learn and perform tasks they haven’t been explicitly programmed to do.

 

Data Scientists and Machine Learning Engineers who are skilled in Machine Learning are even higher in demand across the entire employment spectrum.  Many diverse industries are searching for innovation in the field, and their need for Machine Learning experts and engineers is rapidly increasing.

 

Traditional Machine Learning requires students to know software programming, which enables them to write machine learning algorithms.  But in this groundbreaking Udemy course, you’ll learn Machine Learning without any coding whatsoever.  As a result, it’s much easier and faster to learn! 

 

There’s literally no other course on Udemy that teaches Machine Learning without the need for programming knowledge or coding, using free open source software!

 

A Rare Opportunity to Quickly Learn Data Science and Machine Learning at an Affordable Cost… No Previous Knowledge of Programming Required!

 

Happily, now you can shorten your learning curve and be on your way toward earning a 6-figure income with this groundbreaking Udemy training.

 

Master Machine Learning & Data Science Quickly!

One of the most common problems learners have when jumping into Machine Learning and Data Science is the steep learning curve, and when you add to this the complexity of learning programming languages like Python or R you can get demotivated and lose interest fast.

A Different & More Effective Approach To Learning Data Science

In this groundbreaking course, you will learn the basic concepts of machine learning using a visual tool. Where you can just drag drop machine learning algorithms and all other functionality hiding the ugliness of code, making it much easier to grasp the fundamental concepts.

We’ll Build Several Machine Learning Algorithms Together.

I’ll “hand-hold” you as we build from scratch several different types of machine learning algorithms used in the real world, across several industries and I will explain where and how they are used.

Learn Both The Theory & Application Of Machine:

The course will teach you those fundamental concepts of machine learning by implementing practical exercises which are based on real world examples. You will learn the theory, but get hands on practice building these machine learning algorithms.


You’ll also get access to:

·         The datasets used in all the exercises.

·         The solution files of the completed exercises.

·         Cheat sheets to help you remember the fundamental concepts.

 

Join the class now!

Who this course is for:

  • Software Programmers or Data Analysts Trying To Switch To A Data Science Career
  • Business Analysts With No Programming Background Yet Want To Learn Machine Learning
  • Students Trying to Understand the Basics of Machine Learning
  • Anyone Who Wants To Understand the Fundamentals Behind Machine Learning

Instructor

Ram Prasad
Data Scientist & Certified RapidMiner Analyst
Ram Prasad
  • 4.3 Instructor Rating
  • 743 Reviews
  • 5,165 Students
  • 2 Courses

Ram develops analytics solutions and predictive models that help long haul trucking companies make critical business decisions in operations, safety and productivity. Ram has 10 years of prior experience in software engineering and has been building data solutions for the last 5 years. He holds a patent (pending) for a text mining application for wireless communication devices in trucks. He is a frequent speaker at Big Data, Data Science conferences and is engaged with the local data science community in Atlanta, Georgia. Ram is a certified RapidMiner Analyst.


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