eLearning Bundle - Data Mining with Python Online Course | Certstaffix® Training

eLearning Bundle - Data Mining with Python Online Course

Machine Learning TrainingeLearning Bundle - Data Mining with Python

by Certstaffix® Training

Length: 3 Course(s)      Price: $500/person (US Dollars)      Bulk Pricing: 6+ Contact Us      Access Length: 6 Months      Category: Machine Learning

This eLearning bundle consists of these 3 courses: R Data Mining Projects, Machine Learning with Go and Data Mining with Python: Implementing Classification and Regression
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  Online Machine Learning Classes: Learn at Your Own Pace

We will enroll you into a demo (Windows 10) eLearning session. Login information will be emailed to you.

Prefer a self-paced learning solution to fit your own schedule? Certstaffix® Training offers eLearning courses bundled together:

  • Learn at your own pace - Start and stop as it is convenient for you. Pick up where you left off.
  • Lecture utilizing video and recorded screen shots
  • 6 month subscription length

  Detailed Training Topics

Course Description: Print It | Download PDF | Email It
Machine Learning Training


R Data Mining Projects - 3 hours and 19 minutes

The R language is a powerful open source functional programming language. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis. It enables you to create high-level graphics and offers an interface to other languages. This means R is best suited to producing data and visual analytics through customization scripts and commands, instead of the typical statistical tools that provide tick boxes and drop-down menus for users. This video course explores data mining techniques, showing you how to apply different mining concepts to various statistical and data applications in a wide range of fields. We will teach you about R and its application to data mining, and give you relevant and useful information you can use to develop and improve your applications. It will help you complete complex data mining cases and guide you through handling issues you might encounter during projects.

Machine Learning with Go - 2 hours and 48 minutes

The mission of this course is to turn you into a productive, innovative data analyst who can leverage Go to build robust and valuable applications. To this end, the course clearly introduces the technical aspects of building predictive models in Go, but also helps you understand how machine learning workflows are applied in real-world scenarios.This course shows you how to be productive in machine learning while also producing applications that maintain a high level of integrity. It also gives you patterns to overcome challenges that are often encountered when trying to integrate machine learning in an engineering organization.You’ll begin by gaining a solid understanding of how to gather, organize, and parse real-work data from a variety of sources. Then you’ll develop a solid statistical toolkit that will allow you to quickly understand gain intuition about the content of a dataset. Finally, you’ll gain hands-on experience of implementing essential machine learning techniques (regression, classification, clustering, and so on) with the relevant Go packages.

Data Mining with Python: Implementing Classification and Regression - 2 hours and 3 minutes

Python is a dynamic programming language used in a wide range of domains by programmers who find it simple yet powerful. In today’s world, everyone wants to gain insights from the deluge of data coming their way. Data mining provides a way of finding these insights, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. Python has become the language of choice for data scientists for data analysis, visualization, and machine learning.

In this course, you will discover the key concepts of data mining and learn how to apply different data mining techniques to find the valuable insights hidden in real-world data. You will also tackle some notorious data mining problems to get a concrete understanding of these techniques.

We begin by introducing you to the important data mining concepts and the Python libraries used for data mining. You will understand the process of cleaning data and the steps involved in filtering out noise and ensuring that the data available can be used for accurate analysis. You will also build your first intelligent application that makes predictions from data. Then you will learn about the classification and regression techniques such as logistic regression, k-NN classifier, and SVM, and implement them in real-world scenarios such as predicting house prices and the number of TV show viewers.

By the end of this course, you will be able to apply the concepts of classification and regression using Python and implement them in a real-world setting.
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