eLearning Bundle - Machine Learning Basics with R and Python Online Course

eLearning Bundle - Machine Learning Basics with R and Python

by Certstaffix® Training

Length: 8 Course(s)      Price: $1000/person (US Dollars)      Bulk Pricing: 6+ Contact Us      Access Length: 6 Months      Category: Machine Learning


This eLearning bundle includes these 8 courses: Python Machine Learning in 7 Days, Getting Started with Machine Learning in R, R Machine Learning Solutions, Python Machine Learning - Part 1, Python Machine Learning Tips, Tricks, and Techniques, Python Machine Learning Solutions, Python Machine Learning Projects and Building Predictive Models with Machine Learning and Python.
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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
  • Any software needed for training is provided in an online lab environment.

  Detailed Training Topics

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MACHINE LEARNING BASICS WITH R/PYTHON

Python Machine Learning in 7 Days - 2 hours and 22 minutes

In this course, you will be introduced to a new machine learning aspect in each section followed by a practical assignment as a homework to help you in efficiently implement the learnings in a practical manner. With the systematic and fast-paced approach to this course, learn machine learning using Python in the most practical and structured way to develop machine learning projects in Python in a week.

Getting Started with Machine Learning in R - 1 hour and 48 minutes

Do you want to turn your data to predict outcomes that make real impact and have better insights?R provides a cutting-edge power you need to work with machine learning techniquesYou will learn to apply machine learning techniques in the popular statistical language R. This course will get you started with Machine Learning and R by understanding Machine Learning and installing R. The course will then take you through some different types of ML. You will work with a classic dataset using Machine Learning. You will learn Linear and Logistic Regression algorithms and analyze the dataset. The course will take you through algorithms like Random Forest and Naive Bayes for working on your data in R. You will then see some of the excellent graphical tools in R, and some discussion of the goals and techniques for presenting graphical data. Analysis of the data set is demonstrated from end to end, with example R code you can use. Then you’ll have a chance to do it yourself on another data set.By the end of the course you will learn how to gain insights from complex data and how to choose the correct algorithm for your specific needs.

R Machine Learning Solutions - 8 hours and 20 minutes

R is a statistical programming language that provides impressive tools to analyze data and create high-level graphics. This video course will take you from very basics of R to creating insightful machine learning models with R. You will start with setting up the environment and then perform data ETL in R.

Data exploration examples are provided that demonstrate how powerful data visualization and machine learning is in discovering hidden relationship. You will then dive into important machine learning topics, including data classification, regression, clustering, association rule mining, and dimensionality reduction.

Python Machine Learning - Part 1 - 3 hours and 22 minutes

Machine learning and predictive analytics are transforming the way that businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, and is becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data. Its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.This video gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science courseis invaluable. It coversa wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and features guidance and tips on everything from sentiment analysis to neural networks. With this video,you’ll soon be able to answer some of the most important questions facing you and your organization.

Python Machine Learning Tips, Tricks, and Techniques - 2 hours and 46 minutes

Machine learning allows us to interpret data structures and fit that data into models to identify patterns and make predictions. Python makes this easier with its huge set of libraries that can be easily used for machine learning. In this course, you will learn from a top Kaggle master to upgrade your Python skills with the latest advancements in Python.

It is essential to keep upgrading your machine learning skills as there are immense advancements taking place every day. In this course, you will get hands-on experience of solving real problems by implementing cutting-edge techniques to significantly boost your Python Machine Learning skills and, as a consequence, achieve optimized results in almost any project you are working on.

Each technique we cover is itself enough to improve your results. However; combining them together is where the real magic is. Throughout the course, you will work on real datasets to increase your expertise and keep adding new tools to your machine learning toolbox.

By the end of this course, you will know various tips, tricks, and techniques to upgrade your machine learning algorithms to reduce common problems, all the while building efficient machine learning models.

Python Machine Learning Solutions - 4 hours and 30 minutes

Machine learning is increasingly pervasive in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more.

With this course, you will learn how to perform various machine learning tasks in different environments. We’ll start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the course, you’ll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.

You’ll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modelling, data visualization techniques, recommendation engines, and more with the help of real-world examples.

Python Machine Learning Projects - 2 hours and 56 minutes

Machine learning gives you unimaginably powerful insights into data. Today, implementations of machine learning have been adopted throughout Industry and its concepts are numerous. This video is a unique blend of projects that teach you what Machine Learning is all about and how you can implement machine learning concepts in practice. Six different independent projects will help you master machine learning in Python. The video will cover concepts such as classification, regression, clustering, and more, all the while working with different kinds of databases. By the end of the course, you will have learned to apply various machine learning algorithms and will have mastered Python's packages and libraries to facilitate computation. You will be able to implement your own machine learning models after taking this course.

Building Predictive Models with Machine Learning and Python - 2 hours and 47 minutes

Machine Learning is no longer the inaccessible domain it used to be. There are over 100,000 Python libraries you can download in one line of code! This course will introduce you to tools with which you can build predictive models with Python, the core of a Data Scientist's toolkit. Through some really interesting examples, the course will take you through a variety of challenges: predicting the value of a house in Boston, the batting average of a baseball player, their survival chances had they been on the Titanic, or any other number of other interesting problems. Once you master the content of the course, you can level-up your knowledge of the Python Data Analytics and Machine Learning stack by exploring these recommended libraries. This course will guide you through the tools in the Python ecosystem that Data Scientists use to get results in a matter of hours - and with practice - in a matter of minutes. The best way to learn is through examples, and this course will guide you through all the steps needed to train and test your models by tackling several classifications and regression challenges. By the end of the course, you will be able to take the Python Machine Learning toolkit we cover and apply it to your own projects to deploy models in just a few lines of code.
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