Machine Learning No-Code Approach: Using Azure ML Studio
What you'll learn
- Examine the foundations of Supervised Machine Learning
- Use Azure ML Studio to create Predictive Models without code
- Evaluate different algorithms to find the one that works best
- Deploy models live to be used with new data
- Build a real estate model to predict house prices
- Experiment with the traditional Titanic Dataset to predict survival chances
- Be able to work with computer files and folders
- Be able to use a spreadsheet application like Microsoft Excel or Google Sheets
- A free or paid subscription to Microsoft Azure
Machine Learning is the most in demand technical skill in today's business environment. Most of the time though it is reserved for professionals that know how to code.
But Microsoft Azure Machine Learning Studio changed that. It brings a drag-n-drop easy to use environment to anyone’s fingertips. Microsoft is known for its easy-of-use tools and Azure ML Studio is no different.
However, as easy as Azure ML Studio is, if you don’t know Machine Learning, at least the basics, you won’t be able to do much with the tool. This is one of the goals of this course: To give you the foundational understanding about Machine Learning. You will get the base knowledge required to not only talk proficiently about ML, but also to put it into action and execute on business needs.
We will go through all the steps necessary to put together a Supervised Learning prediction model, whether you need Classification (for discrete values like “Approved” or “Nor Approved”) or Regression (for continuous values like “Salary” or “Price”).
The course will only require you to have basic knowledge of math including the basic operations and how to calculate average. Some exposure to Microsoft Excel would be good as during deployment of the live model, we will be using Excel to perform demonstrations.
This course has been designed keeping in mind technologists with no coding background as we use a “no-code approach”. It is very hands-on, and you will be able to develop your own models while learning. We will cover:
- Basics of the main three main types of Machine Learning Algorithms
- Supervised Learning in depth
- Classification by using the Titanic Dataset
- Understanding and selecting the features from the dataset
- Changing the metadata of features to work better with ML Algorithms
- Splitting the data
- Selecting the Algorithm
- Training, scoring, and evaluating the model
- Regression by using the Melbourne Real Estate Dataset
- Cleaning missing data
- Stratifying the data
- Tuning hyperparameters
- Deploying the models to a Excel
- Providing web service details to developers in case you want to integrate with external systems
- Azure ML Cheat Sheet
The course also includes 4 assignments with solutions that will give you an extra chance to practice your newly acquired Machine Learning skills.
In the end you will be able to use your own datasets to help your company with data prediction or, if you just want to impress the boss, you will be able to show the new tool you have just added to your toolbelt.
If you are not a coder and thought there would be no place for you to ride the Machine Learning wave, think again. You can not only be part of it, but you can master it and become a Machine Learning hero with Azure ML Studio.
Enroll today and I will see you inside!
Who this course is for:
- Technology Professionals
- Curious about Machine Learning
- Not a Coder
My name is Aderson Oliveira and I love to teach technology. I have always enjoyed guiding people through hard to understand technical topics, but that became more evident back in 2018 when I started teaching coding in a post-secondary environment.
I love the "Aha!" moments that I help to create with my students when they finally get it.
I have been working as a developer for the past 20 years and in the last 10 years I have been working as a consultant, running my own service helpdesk business. I have mostly focused on Microsoft related technologies like Azure, C#, SQL Server and .NET Core Framework.
I have been teaching online since 2010 and more recently in the past 4 years I have been focusing on AI and Machine Learning.
I enjoy learning and I'm here on Udemy to share what I know with anyone interested to join the learning journey with me.