- Understand why you should do ML in the cloud
- Understand when you should do ML in the cloud
- Analyze the customers of ML
Online
3 Months
Quick facts
particular | details | |||
---|---|---|---|---|
Collaborators
Microsoft Corporation
|
Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
|
Learning efforts
5-10 Hours Per Week
|
Course overview
The Machine Learning Engineer for Microsoft Azure online course is designed to deliver the knowledge of Azure Machine Learning over the cloud covering the use and benefits of Machine Learning in the cloud. The course teaches how to manage and choose computer resources to train Machine Learning models for quick and accurate predictive results.
The Machine Learning Engineer for Microsoft Azure syllabus explores training of Machine Learning Models in Azure including supervised model, unsupervised model and Reinforcement model. The program helps to learn using various types of tools in Microsoft Azure to train and deploy a machine learning model for pipeline automation. The nano degree course covers key concepts to analyze data and construct data sets suitable for machine learning.
The Machine Learning Engineer for Microsoft Azure nano degree program in collaboration with Microsoft focuses on Configuring cloud-based machine learning model with the help of Microsoft Azure services and tools, training a model on datasets using Automated Machine Learning and Analyzing the performance of the trained models. The Course covers in-depth knowledge of shipping machine learning models into production.
The highlights
- Support for all technical questions
- Practical tips and industry best practices
- Personalized feedback
- Unlimited submissions and feedback loops
- Additional suggested resources to improve
- Questions answered quickly by the technical mentor's team.
Program offerings
- Quizzes
- Online training
- 3 months course
- Mentor support
- Real world projects
Course and certificate fees
Machine Learning Engineer for Microsoft Azure Fee
Heads | Amount in INR |
Programme Fees (3-month access) | 58,257 |
Programme Fees (pay as you go) | 22,849/month |
certificate availability
certificate providing authority
Eligibility criteria
For enrolling in Machine Learning Engineer for Microsoft Azure certification course, the candidate should have experience with basic python programming skills and knowledge of fundamental statistics and algebra. The candidate should be familiar with basic machine learning concepts along with an understanding of Azure and Docker/Container services.
Certification Qualifying Details
Candidates should complete their in-course Assessments and Capstone Project to get a completion certificate in Machine Learning for Microsoft Azure.
What you will learn
After completing the Machine Learning Engineer by Microsoft Azure nano degree program, candidates will be able to :
- Train Machine Learning Models
- Deploy Machine Learning Models
- Configure Machine Learning Pipeline
- Identify problems in logs
Who it is for
Students having basic knowledge of Python Programming, Machine Learning, Docker/Container service who want to become Machine Learning Engineer, Data Administrator, Data Engineer, Data Scientist, can join Machine Learning Engineer for Microsoft Azure Program.
Admission details
Step 1. To know more about the Machine Learning Engineer for Microsoft Azure online Course, open the course website
(https://www.udacity.com/course/machine-learning-engineer-for-microsoft-azure-nanodegree--nd00333)
Step 2. Visit the checkout page by clicking on the ‘Enroll Now’ button
Step 3. Confirm order details and continue
Step 4. Fill in the payment details
Step 5. Complete the Application by paying fees.
Filling the form
Step 1. To Apply for the Machine Learning Engineer for Microsoft Azure nanodegree training, open the course website
(https://www.udacity.com/course/machine-learning-engineer-for-microsoft-azure-nanodegree--nd00333)
Step 2. Open your account by filling in login details
Step 3. Upload the self-attested copy of required documents
Step 4. Verify your email address and Phone number
Step 5. Finish the registration process.
The syllabus
Using Azure Machine Learning
Introduction to Azure ML
Workspaces and the Azure ML Studio
- Interpret the Azure ML Platform
- Explain how to manage and choose to compute resources
- Summarize the key components of Workspaces and Notebooks
Datastores and Datasets
- Analyze how to manage data
- Construct datasets
- Compose solutions to manage data drift and deal with sensitive data
Training Models in Azure ML
- Experiment with the Designer
- Develop and manage pipelines
- Organize and run hyperparameter experiments
The AzureML SDK
- Utilize data with the SDK
- Create pipelines
- Organize experiments
AutoML and Hyperparameter
- Design solutions with AutoML and the SDK
- Analyze model interpretation experiments
- Create portable ML models with ONNX
Machine Learning Operations
Enabling Security
- Create a Service Principal account for different types of roles
- Determine what the differences are in various forms of authentication
- Use a specific type of authentication when selecting deployment settings
Deploy a ML model
- Use a production environment for deployment
- Enable authentication in the deployment cluster
- Discover the differences between container-based deployment and Kubernetes.
ML Endpoints
- Use a proven tool to find what a baseline for performance is
- Gather information about an endpoint input to interact with it
- Find what potential issues can happen with an incorrect input
Pipeline Automation
- Create a pipeline to further automation when training models
- Enable a REST API for the pipeline, so other services can interact with it
Evaluation process
There is no any type of written examination for certification in Machine Learning for Microsoft Azure, however, candidates must submit their capstone project based on their learning.
How it helps
- Real-world projects from industry experts
- Technical mentor support
- Career services
- Student community support
- Flexible Learning
Instructors
Mr Noah Gift
Professor
Duke University, Durham
Mr Alfredo Deza
Instructor
Freelancer
Mr Erick Galinkin
Researcher
Freelancer
Mr Soham Chatterjee
Researcher
Freelancer
Other Bachelors, Other Masters
FAQs
Students and professionals having basic knowledge of python programming, machine learning along with docker/container services can join Machine Learning Engineer for Microsoft Azure.
The estimated duration of Machine Learning Engineer for Microsoft Azure nano degree is 3 Months at the rate of 5-10 hours per week.
Yes, you can join Machine Learning for Microsoft Azure courses online without any work experience.
After the completion of the Machine Learning for Microsoft Azure Certification course, candidates can apply for different job roles, such as Machine Learning Engineer, AI Specialist, Data Scientist, and many more.