Udemy
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
Development
Web Development Data Science Mobile Development Programming Languages Game Development Database Design & Development Software Testing Software Engineering Development Tools No-Code Development
Business
Entrepreneurship Communications Management Sales Business Strategy Operations Project Management Business Law Business Analytics & Intelligence Human Resources Industry E-Commerce Media Real Estate Other Business
Finance & Accounting
Accounting & Bookkeeping Compliance Cryptocurrency & Blockchain Economics Finance Finance Cert & Exam Prep Financial Modeling & Analysis Investing & Trading Money Management Tools Taxes Other Finance & Accounting
IT & Software
IT Certification Network & Security Hardware Operating Systems Other IT & Software
Office Productivity
Microsoft Apple Google SAP Oracle Other Office Productivity
Personal Development
Personal Transformation Personal Productivity Leadership Career Development Parenting & Relationships Happiness Esoteric Practices Religion & Spirituality Personal Brand Building Creativity Influence Self Esteem & Confidence Stress Management Memory & Study Skills Motivation Other Personal Development
Design
Web Design Graphic Design & Illustration Design Tools User Experience Design Game Design Design Thinking 3D & Animation Fashion Design Architectural Design Interior Design Other Design
Marketing
Digital Marketing Search Engine Optimization Social Media Marketing Branding Marketing Fundamentals Marketing Analytics & Automation Public Relations Advertising Video & Mobile Marketing Content Marketing Growth Hacking Affiliate Marketing Product Marketing Other Marketing
Lifestyle
Arts & Crafts Beauty & Makeup Esoteric Practices Food & Beverage Gaming Home Improvement Pet Care & Training Travel Other Lifestyle
Photography & Video
Digital Photography Photography Portrait Photography Photography Tools Commercial Photography Video Design Other Photography & Video
Health & Fitness
Fitness General Health Sports Nutrition Yoga Mental Health Dieting Self Defense Safety & First Aid Dance Meditation Other Health & Fitness
Music
Instruments Music Production Music Fundamentals Vocal Music Techniques Music Software Other Music
Teaching & Academics
Engineering Humanities Math Science Online Education Social Science Language Teacher Training Test Prep Other Teaching & Academics
AWS Certification Microsoft Certification AWS Certified Solutions Architect - Associate AWS Certified Cloud Practitioner CompTIA A+ Cisco CCNA Amazon AWS CompTIA Security+ Microsoft AZ-900
Graphic Design Photoshop Adobe Illustrator Drawing Digital Painting InDesign Character Design Canva Figure Drawing
Life Coach Training Neuro-Linguistic Programming Personal Development Personal Transformation Mindfulness Life Purpose Meditation CBT Emotional Intelligence
Web Development JavaScript React CSS Angular PHP Node.Js WordPress Vue JS
Google Flutter Android Development iOS Development React Native Swift Dart Programming Language Mobile Development Kotlin SwiftUI
Digital Marketing Google Ads (Adwords) Social Media Marketing Google Ads (AdWords) Certification Marketing Strategy Internet Marketing YouTube Marketing Email Marketing Retargeting
Microsoft Power BI SQL Tableau Business Analysis Data Modeling Business Intelligence MySQL Data Analysis Blockchain
Business Fundamentals Entrepreneurship Fundamentals Business Strategy Business Plan Startup Freelancing Online Business Blogging Home Business
Unity Game Development Fundamentals Unreal Engine C# 3D Game Development C++ 2D Game Development Unreal Engine Blueprints Blender
2021-03-08 11:33:58
30-Day Money-Back Guarantee
Development Data Science Machine Learning

DP-100: A-Z Machine Learning using Azure Machine Learning

Microsoft Azure DP-100: Designing and Implementing a Data Science Solution Exam Covered. Learn Azure Machine Learning
Bestseller
Rating: 4.5 out of 54.5 (3,556 ratings)
20,816 students
Created by Jitesh Khurkhuriya, Python, Data Science & Machine Learning A-Z Team
Last updated 4/2021
English
English [Auto], French [Auto], 
30-Day Money-Back Guarantee

What you'll learn

  • Prepare for and Pass the Azure DP-100 Exam
  • Master Data Science and Machine Learning Models using Azure ML.
  • Data Processing using Python and Pandas
  • AzureML SDK for Python for complete Machine Learning Lifecycle.
  • Azure Automated Machine Learning for faster and efficient Machine Learning model development and deployment
  • Understand the concepts and intuition of Machine Learning algorithms
  • Build Machine Learning models within minutes
  • Deploy production grade Machine Learning algorithms
  • Deploy Machine Learning webservices in the simplest manner
Curated for the Udemy for Business collection

Course content

31 sections • 243 lectures • 28h 56m total length

  • Preview05:07
  • The course slides as well as Data Files for all sections
    00:16
  • Important Message About Udemy Reviews
    03:17

  • What You Will Learn in This Section
    02:02
  • Why Machine Learning is the Future?
    09:42
  • What is Machine Learning?
    09:31
  • Understanding various aspects of data - Type, Variables, Category
    07:05
  • Common Machine Learning Terms - Probability, Mean, Mode, Median, Range
    07:41
  • Types of Machine Learning Models - Classification, Regression, Clustering etc
    10:02
  • Basics of Machine Learning
    5 questions

  • What You Will Learn in This Section?
    02:08
  • What is Azure ML and high level architecture.
    03:59
  • Creating a Free Azure ML Account
    03:24
  • Azure ML Studio Overview and walk-through
    05:00
  • Azure ML Experiment Workflow
    07:19
  • Azure ML Cheat Sheet for Model Selection
    06:01
  • Getting Started with AzureML
    4 questions

  • [Hands On] - Data Input-Output - Upload Data
    08:18
  • [Hands On] - Data Input-Output - Convert and Unpack
    08:53
  • [Hands On] - Data Input-Output - Import Data
    05:46
  • [Hands On] -Data Transform - Add Rows/Columns, Remove Duplicates, Select Columns
    11:34
  • [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata
    18:29
  • [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data
    16:56
  • Update to Lecture Sequence.
    00:04
  • Data Processing
    8 questions

  • Logistic Regression - What is Logistic Regression?
    06:45
  • [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model
    22:08
  • Logistic Regression - Understand Parameters and Their Impact
    11:19
  • Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score
    13:17
  • Logistic Regression - Model Selection and Impact Analysis
    05:50
  • [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model
    08:13
  • Decision Tree - What is Decision Tree?
    07:34
  • Decision Tree - Ensemble Learning - Bagging and Boosting
    07:05
  • Decision Tree - Parameters - Two Class Boosted Decision Tree
    05:34
  • [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction
    10:43
  • Decision Forest - Parameters Explained
    03:37
  • [Hands On] - Two Class Decision Forest - Adult Census Income Prediction
    14:43
  • [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data
    08:14
  • SVM - What is Support Vector Machine?
    04:01
  • [Hands On] - SVM - Adult Census Income Prediction
    05:32
  • Classification Quiz
    8 questions

  • [Hands On] - Tune Hyperparameter for Best Parameter Selection
    09:53
  • Hyperparameter Tuning
    2 questions

  • Azure ML Webservice - Prepare the experiment for webservice
    02:22
  • [Hands On] - Deploy Machine Learning Model As a Web Service
    03:28
  • [Hands On] - Use the Web Service - Example of Excel
    06:38
  • AzureML Web Service
    2 questions

  • What is Linear Regression?
    06:19
  • Regression Analysis - Common Metrics
    06:27
  • [Hands On] - Linear Regression model using OLS
    11:05
  • [Hands On] - Linear Regression - R Squared
    04:25
  • Gradient Descent
    10:48
  • Linear Regression: Online Gradient Descent
    02:12
  • [Hands On] - Experiment Online Gradient
    04:21
  • Decision Tree - What is Regression Tree?
    06:41
  • Decision Tree - What is Boosted Decision Tree Regression?
    02:00
  • [Hands On] - Decision Tree - Experiment Boosted Decision Tree
    07:00
  • Regression Analysis
    6 questions

  • What is Cluster Analysis?
    11:52
  • [Hands On] - Cluster Analysis Experiment 1
    13:15
  • [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate
    08:04
  • Clustering or Cluster Analysis
    4 questions

  • Section Introduction
    02:49
  • How to Summarize Data?
    06:28
  • [Hands On] - Summarize Data - Experiment
    03:11
  • Outliers Treatment - Clip Values
    06:51
  • [Hands On] - Outliers Treatment - Clip Values
    07:51
  • Clean Missing Data with MICE
    07:18
  • [Hands On] - Clean Missing Data with MICE
    06:43
  • SMOTE - Create New Synthetic Observations
    08:33
  • [Hands On] - SMOTE
    05:50
  • Data Normalization - Scale and Reduce
    03:10
  • [Hands On] - Data Normalization
    02:32
  • PCA - What is PCA and Curse of Dimensionality?
    06:24
  • [Hands On] - Principal Component Analysis
    03:24
  • Join Data - Join Multiple Datasets based on common keys
    06:03
  • [Hands On] - Join Data - Experiment
    02:42

Requirements

  • 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

Description

This course will help you and your team to build skills required to pass the most in demand and challenging, Azure DP-100 Certification exam. It will earn you one of the most in-demand certificate of Microsoft Certified: Azure Data Scientist Associate.

DP-100 is designed for Data Scientists. This exam tests your knowledge of Data Science and Machine learning to implement machine learning models on Azure. So you must know right from Machine Learning fundamentals, Python, planning and creating suitable environments in Azure, creating machine learning models as well as deploying them in production.

Why should you go for DP-100 Certification?

  • One of the very few certifications in the field of Data Science and Machine Learning.

  • You can successfully demonstrate your knowledge and abilities in the field of Data Science and Machine Learning.

  • You will improve your job prospects substantially in the field of Data Science and Machine Learning.

Key points about this course

  • Covers the most current syllabus as on 8th December, 2020.

  • 100% syllabus of DP-100 Exam is covered.

  • Very detailed and comprehensive coverage with more than 200 lectures and 25 Hours of content

  • Crash courses on Python and Azure Fundamentals for those who are new to the world of Data Science

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 using Azure Machine Learning Service as well as the Azure Machine Learning Studio. 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.

----- Exam Syllabus for DP-100 Exam -----

1. Set up an Azure Machine Learning Workspace (30-35%)

Create an Azure Machine Learning workspace

  • Create an Azure Machine Learning workspaceConfigure workspace settings

  • Manage a workspace by using Azure Machine Learning studio

Manage data objects in an Azure Machine Learning workspace

  • Register and maintain datastores

  • Create and manage datasets

Manage experiment compute contexts

  • Create a compute instance

  • Determine appropriate compute specifications for a training workload

  • Create compute targets for experiments and training


Run Experiments and Train Models (25-30%)

Create models by using Azure Machine Learning Designer

  • Create a training pipeline by using Azure Machine Learning designer

  • Ingest data in a designer pipeline

  • Use designer modules to define a pipeline data flow

  • Use custom code modules in designer

Run training scripts in an Azure Machine Learning workspace

  • Create and run an experiment by using the Azure Machine Learning SDK

  • Configure run settings for a script

  • Consume data from a dataset in an experiment by using the Azure Machine Learning SDK

Generate metrics from an experiment run

  • Log metrics from an experiment run

  • Retrieve and view experiment outputs

  • Use logs to troubleshoot experiment run errors

Automate the model training process

  • Create a pipeline by using the SDK

  • Pass data between steps in a pipeline

  • Run a pipeline

  • Monitor pipeline runs


Optimize and Manage Models (20-25%)

Use Automated ML to create optimal models

  • Use the Automated ML interface in Azure Machine Learning studio

  • Use Automated ML from the Azure Machine Learning SDK

  • Select pre-processing options

  • Determine algorithms to be searched

  • Define a primary metric

  • Get data for an Automated ML run

  • Retrieve the best model

Use Hyperdrive to tune hyperparameters

  • Select a sampling method

  • Define the search space

  • Define the primary metric

  • Define early termination options

  • Find the model that has optimal hyperparameter values

Use model explainers to interpret models

  • Select a model interpreter

  • Generate feature importance data

Manage models

  • Register a trained model

  • Monitor model usage

  • Monitor data drift


Deploy and Consume Models (20-25%)

Create production compute targets

  • Consider security for deployed services

  • Evaluate compute options for deployment

Deploy a model as a service

  • Configure deployment settings

  • Consume a deployed service

  • Troubleshoot deployment container issues

Create a pipeline for batch inferencing

  • Publish a batch inferencing pipeline

  • Run a batch inferencing pipeline and obtain outputs

Publish a designer pipeline as a web service

  • Create a target compute resource

  • Configure an Inference pipeline

  • Consume a deployed endpoint


Some feedback from previous students,

  1. "The instructor explained every concept smoothly and clearly. I'm an acountant without tech background nor excellent statistical knowledge. I do really appreciate these helpful on-hand labs and lectures. Passed the DP-100 in Dec 2020. This course really help."


  2. "Cleared DP-100 today with the help of this course. I would say this is the one of the best course to get in depth knowledge about Azure machine learning and clear the DP-100 with ease. Thank you Jitesh and team for this wonderful tutorial which helped me clear the certification."


  3. "The instructor explained math concept clearly. These math concepts are necessary as fundation of machine learning, and also are very helpful for studying DP-100 exam concepts. Passed DP-100."


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.

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.

So, hit the enroll button and I will see you inside the course.

Best-

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
  • Existing Data Scientists who want to earn DP-100 Certification
  • Anyone who wants to learn 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
  • Students and non-technical professionals who want to start a career in Machine Learning
  • Data Engineers or Software Engineers who want to learn Data Science and Machine Learning

Instructors

Jitesh Khurkhuriya
Data Scientist and Digital Transformation Consultant
Jitesh Khurkhuriya
  • 4.5 Instructor Rating
  • 5,617 Reviews
  • 31,825 Students
  • 6 Courses

Jitesh has over 20 years of technology experience and worked as programmer, Product Head as well as the Data Scientist.  

Jitesh has worked with various fortune 500 companies and governments across the world.

As the Data Scientist and Anti-Fraud Expert, he was the member of the high-profile team to suggest tax reforms and amendments in VAT, Customs and Income Tax based on fraud pattern analysis, countrywide data mining and analysis, business process security analysis. This not only contributed to a revolutionary change in the tax processes but also reduced the tax and customs frauds. 

As a seasoned leader in Digital Transformation, Jitesh has developed and executed strategies that generated high top and bottom line revenue streams.

Python, Data Science & Machine Learning A-Z Team
Helping you succeed in Data Science and Machine Learning.
Python, Data Science & Machine Learning A-Z Team
  • 4.5 Instructor Rating
  • 5,353 Reviews
  • 30,482 Students
  • 4 Courses

Hi,

We are Jitesh's Python, Data Science and Machine Learning Assistant team. We are on a mission to help you understand the Data Science and Machine Learning in the simplest possible way. Jitesh has over 20 years of Technology experience and more than a decade of Data Science and Machine Learning experience with various Fortune 500 companies as well as few governments across the globe.

We help create various courses in the Data Science domain and one of the leading training providers.

You will hear from us socially and during the Q&A.

See you in the class and enjoy learning Data Science and Machine Learning.

Sincerely,

Data Science Learning Academy Team


  • Udemy for Business
  • Teach on Udemy
  • Get the app
  • About us
  • Contact us
  • Careers
  • Blog
  • Help and Support
  • Affiliate
  • Impressum Kontakt
  • Terms
  • Privacy policy
  • Cookie settings
  • Sitemap
  • Featured courses
Udemy
© 2021 Udemy, Inc.