About this Course

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This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms. You'll  explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning. 
Next, this course introduces the machine learning tools available in Microsoft Azure. We'll review standardized approaches to data analytics and you'll receive specific guidance on Microsoft's Team Data Science Approach. As you go through the course, we'll introduce you to Microsoft's pre-trained and managed machine learning offered as REST API's in their suite of cognitive services. We'll implement solutions using the computer vision API and the facial recognition API, and we'll do sentiment analysis by calling the natural language service.   

Using the Azure Machine Learning Service you'll create and use an Azure Machine Learning Worksace.Then you'll train your own model, and you'll deploy and test your model in the cloud. Throughout the course you will perform hands-on exercises to practice your new AI skills. By the end of this course, you will be able to create, implement and deploy machine learning models.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

General knowledge of Azure

Approx. 16 hours to complete

English

Subtitles: English

What you will learn

Define Artificial Intelligence and Machine Language

Describe AI tools and roles, and the Microsoft Team Data Science Process

Work with Azure APIs, including those for vision, language, and search

Create, train, test and deploy your AI model in the cloud

Skills you will gain

Python ProgrammingAzure AI modelsMicrosoft Team Data Sciences ProcessAzure Machine Learning ServiceAzure Machine Learning Workspace

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

General knowledge of Azure

Approx. 16 hours to complete

English

Subtitles: English

Syllabus - What you will learn from this course

Week

1

Week 1

4 hours to complete

Introduction to Artificial Intelligence

This module introduces Artificial Intelligence and Machine learning. Next, we talk about machine learning types and tasks. This leads into a discussion of machine learning algorithms. Finally we explore python as a popular language for machine learning solutions and share some scientific ecosystem packages which will help you implement machine learning. By the end of this unit you will be able to implement machine learning models in at least one of the available python machine learning libraries.

4 hours to complete

10 videos (Total 47 min), 6 readings, 4 quizzes

10 videos

module 1 intro43s

Definition of AI and Machine Learning4m

Machine Learning Alogrithms5m

Python Basics1m

Python Collections6m

Python Variables2m

Python Scientific Ecosystem and ML Libraries5m

Linear Regression with Scikit Learn8m

Logistic Regression with Scikit Learn9m

Module conclusion1m

6 readings

Exercise: Sign up for a free Azure account or login to your existing one.30m

Definition of AI10m

Comparison of machine learning algorithms10m

Links to learn more about python10m

Exercise Python Basics notebook30m

Exercise: Scikit-learn models for regression and classification40m

4 practice exercises

Practice: Python Collections2m

AI and ML Definitions6m

Deep Learning3m

Module 1: Introduction to Artificial Intelligence30m

Week

2

Week 2

3 hours to complete

Standardized AI Processes and Azure Resources

This module introduces machine learning tools available in Microsoft Azure. It then looks at standardized approaches developed to help data analytics projects to be successful. Finally, it gives you specific guidance on Microsoft's Team Data Science Approach to include roles and tasks involved with the process. The exercise at the end of this unit points you to Microsoft's documentation to implement this process in their DevOps solution if you don't have your own.

3 hours to complete

9 videos (Total 44 min), 2 readings, 3 quizzes

9 videos

module 2 intro39s

AI Tools2m

aiprocesses2m

TDSP Stages7m

TDSP General Manager Tasks4m

TDSP Task Lead Tasks5m

TDSP Project Lead Tasks5m

TDSPData Scientist Tasks14m

Module 2 Conclusion49s

2 readings

Microsoft Team Data Science Process10m

Exercise: TDSP in Azure Devops1h

3 practice exercises

Practice: TDSP6m

ML Studio3m

Module 2: Standardized AI Processes and Azure Resources30m

Week

3

Week 3

3 hours to complete

Azure Cognitive APIs

This module introduces you to Microsoft's pretrained and managed machine learning offered as REST API's in their suite of cognitive services. We specifically implement solutions using the computer vision api, the facial recognition api, and do sentiment analysis by calling the natural language service.

3 hours to complete

7 videos (Total 28 min), 3 readings, 3 quizzes

7 videos

Module 3 Introduction54s

Cognitive Services Overview1m

Azure Computer Vision API12m

face api2m

Other Cognitive Services API's2m

Sentiment analysis6m

Module 3 Conclusion1m

3 readings

Exercise: Computer Vision Notebook30m

Exercise: Face API Notebook30m

Exercise: Sentiment Analysis Notebook30m

3 practice exercises

Search API3m

Translation3m

Module 3: Azure Cognitive APIs30m

Week

4

Week 4

3 hours to complete

Azure Machine Learning Service: Model Training

This module introduces you to the capabilities of the Azure Machine Learning Service. We explore how to create and then reference an ML workspace. We then talk about how to train a machine learning model using the Azure ML service. We talk about the purpose and role of experiments, runs, and models. Finally, we talk about

3 hours to complete

7 videos (Total 37 min), 3 readings, 5 quizzes

7 videos

Module 4 Introduction52s

Azure ML Service1m

Ways to create an ML Workspace14m

Setting up Experiments2m

Train and register a model5m

Train a model using Azure ML11m

Module 4 Conclusion1m

3 readings

Microsoft Azure Machine Learning Documentation10m

Exercise: Workspace Notebook30m

Exercise: Model Training Notebook1h

5 practice exercises

Azure ML Process3m

Practice: Azure ML Workspace6m

Practice: Train3m

Train Process Step3m

Module 4: Azure Machine Learning Service30m

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?

You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Is financial aid available?

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Developing AI Applications on Azure