Machine Learning is one of the hottest and top paying skills. It’s also one of the most interesting field to work on.
In this course of Machine Learning using Azure Machine Learning, we will make it even more exciting and fun to learn, create and deploy machine learning models. We will go through every concept in depth. This course not only teaches basic but also the advance techniques of Data processing, Feature Selection and Parameter Tuning which an experienced and seasoned Data Science expert typically deploys. Armed with these techniques, in a very short time, you will be able to match the results that an experienced data scientist can achieve.
This course will help you prepare for the entry to this hot career path of Machine Learning as well as the Azure DP-100: Azure Data Scientist Associate exam.
This course has more than 80 lectures and is over 14 hours in content. That simply means, we go through the details of Data Science and Machine Learning along with its implementation. Almost every topic has a hands-on lab that you can practice. I have dealt with almost all scenarios during my tenure with various governments across the world and Fortune 500 companies.
I am committed to and invested in your success. I have always provided answers to all the questions and not a single question remains unanswered for more than a few days. The course is also regularly updated with newer features.
Learning data science and then further deploying Machine Learning Models have been difficult in the past. To make it easier, I have explained the concepts using very simple and day-to-day examples. Azure ML is Microsoft’s way of democratizing Machine Learning. We will use this revolutionary tool to implement our models. Once learnt, you will be able to create and deploy machine learning models in less than an hour using Azure Machine Learning Studio.
Azure Machine Learning Studio is a great tool to learn to build advance models without writing a single line of code using simple drag and drop functionality. Azure Machine Learning (AzureML) is considered as a game changer in the domain of Data Science and Machine Learning.
This course has been designed keeping in mind entry level Data Scientists or no background in programming. This course will also help the data scientists to learn the AzureML tool. You can skip some of the initial lectures or run them at 2x speed, if you are already familiar with the concepts or basics of Machine Learning.
The course is very hands on and you will be able to develop your own advance models while learning,
- Advance Data Processing methods
- Statistical Analysis of the data using Azure Machine Learning Modules
- MICE or Multiple Imputation By Chained Equation
- SMOTE or Synthetic Minority Oversampling Technique
- PCA; Principal Component Analysis
- Two class and multiclass classifications
- Logistic Regression
- Decision Trees
- Linear Regression
- Support Vector Machine (SVM)
- Understanding how to evaluate and score models
- Detailed Explanation of input parameters to the models
- How to choose the best model using Hyperparameter Tuning
- Deploy your models as a webservice using Azure Machine Learning Studio
- Cluster Analysis
- K-Means Clustering
- Feature selection using Filter-based as well as Fisher LDA of AzureML Studio
- Recommendation system using one of the most powerful recommender of Azure Machine Learning
- All the slides and reference material for offline reading
You will learn and master, all of the above even if you do not have any prior knowledge of programming.
This course is a complete Machine Learning course with basics covered. We will not only build the models but also explain various parameters of all those models and where we can apply them.
In this course, we will start with some basic terms which are used very frequently in machine learning.
I will also explain
- What is Machine Learning and some real world examples.
- Azure Machine Learning Introduction
- Provide an overview of Azure Machine Learning Studio and high level architecture.
We would also look at
- Steps for building an ML model.
- Supervised and Unsupervised learning
- Understanding the data and pre-processing
- Different model types
- The AzureML Cheat Sheet.
- How to use Classification and Regression
- What is clustering or cluster analysis
KDNuggets one of the leading forums on Data Science calls Azure Machine Learning as the next big thing in Machine Learning. It further goes on to say, “people without data science background can also build data models through drag-and-drop gestures and simple data flow diagrams.”
Azure Machine Learning’s library has many pre-built models that you can re-use as well as deploy them.
This course will also be a great help in preparing for the Microsoft DP-100 Exam – Designing and Implementing a Data Science Solution on the Azure using Azure Machine Learning. It covers almost all the topics of Azure Machine Learning.
So see you inside the course.
Who this course is for:
- Developers who want to start a career in or wants to learn about the exciting domain of Data Science and Machine Learning
- Business Analysts who want to apply Data Science to solve business problems
- Functional Experts who can take help of Machine Learning and build/test their hypothesis quickly
- Anyone who wants to learn Machine Learning
- Students and non-technical professionals who want to start a career in Machine Learning
- Business Process Managers who want to automate their processes or decision making
- Marketing professionals who want to apply machine learning for better predictions of sales, conversion, churn
- Basic Math is good enough. This course does not require background in Data Science. Will be great if you have one.
- Free or paid subscription to Microsoft Azure is required. It may ask for Phone and/or Credit Card for verification
Last Updated 2/2021