About this Course
Data Scientist is the central role in developing machine learning models. This role is responsible for solving the business problem that initiated the project. While the Data Engineer will prepare the data to be used for the models, the Data Scientist determines what data is needed for model training, creates model features from the data, determines what machine learning model to use, trains and evaluates the model, and often has involvement in model deployment. Often the data scientist needs to evaluate multiple models to determine which performs the best.
Gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure’s premier data science service, Azure Machine Learning service, to automate the data science pipeline. This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.
This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.
Module 1: Doing Data Science on Azure
The student will learn about the data science process and the role of the data scientist. This is then applied to understand how Azure services can support and augment the data science process.
- Introduce the Data Science Process
- Overview of Azure Data Science Options
- Introduce Azure Notebooks
Module 2: Doing Data Science with Azure Machine Learning service
The student will learn how to use Azure Machine Learning service to automate the data science process end to end.
- Introduce Azure Machine Learning (AML) service
- Register and deploy ML models with AML service
Module 3: Automate Machine Learning with Azure Machine Learning service
In this module, the student will learn about the machine learning pipeline and how the Azure Machine Learning service’s AutoML and HyperDrive can automate some of the laborious parts of it.
- Automate Machine Learning Model Selection
- Automate Hyperparameter Tuning with HyperDrive
Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning service
In this module, the student will learn how to automatically manage and monitor machine learning models in the Azure Machine Learning service.
- Manage and Monitor Machine Learning Models
- Azure Fundamentals
- Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
- How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn.
Venue: LIVE Online
Live Online Training
Get the same training you expect in the classroom without leaving your office or home. These are NOT recorded classes. They are LIVE sessions with an expert instructor. We use the latest in video conferencing technologies and audio so you can confidently participate in any class just like being right there in person. We guarantee the effectiveness of our online training delivery approach that we will give you your money back if you are not totally satisfied. Ask us for a demo.
Online class requirements:
- Moderate to fast Internet
- A phone or computer headset is required in order to hear the instructor/moderator). You can use Computer Audio (VoIP) or you can dial in from a regular phone. For convenience, we recommend a hands-free headset or phone.
- Training software must be installed on your computer (trial versions are acceptable)
- RECOMMENDED: Dual Monitors or computers. For optimal online learning experience, we recommend participants have dual monitors or two computers. Your online classroom credentials allow you to join multiple times from multiple computers. Participants should use one monitor or computer to view the instructor’s shared screen and another monitor or computer to work with the software.
What happens when you enroll in an online class
When you register for an online class, you will receive a welcome email followed by login access to the Citrix GoToTraining virtual classroom. A workbook (printed copy or eBook) will be sent to you prior to the start of class.
Online Training Advantages
Convenience: You don’t have to travel and can attend from your home, office or anywhere with an internet connection. Our online classes are conducted using GoToTraining, a more robust version of the popular GoToMeeting screen sharing and conferencing platform. To accommodate multiple time zones, courses are typically scheduled from 10am – 5pm Eastern with a one-hour lunch break at 12:30 – 1:30 pm Eastern and a 10-minute break in the morning and afternoon. When conducting custom online course for your group, class times can be modified to accommodate your timezone.
Interactive Learning: Our online training is fully interactive. You can speak and chat with the instructor and classmates at any time. Various interactive techniques are used in every class. Our small class sizes (typically 4 – 8 students), allow our instructors to focus on individual performance and issues and to work closely with you to meet your unique needs. Classes are designed to be a hands-on learning experience, providing opportunities for you to try your new skills while the instructor is available for review, questions, and feedback. You have the option to give the instructor permission to view your computer to provide one-on-one assistance when needed.