Who should take this course?

This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.


Microsoft Azure AI Fundamentals (AI-900) is recommended, or the equivalent experience.

  • Creating cloud resources in Microsoft Azure.
  • Using Python to explore and visualize data.
  • Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
  • Working with containers

The Training Covers These Topics:

1 – Design a data ingestion strategy for machine learning projects

  • Identify your data source and format
  • Choose how to serve data to machine learning workflows
  • Design a data ingestion solution

2 – Design a machine learning model training solution

  • Identify machine learning tasks
  • Choose a service to train a machine learning model
  • Decide between compute options

3 – Design a model deployment solution

  • Understand how model will be consumed
  • Decide on real-time or batch deployment

4 – Explore Azure Machine Learning workspace resources and assets

  • Create an Azure Machine Learning workspace
  • Identify Azure Machine Learning resources
  • Identify Azure Machine Learning assets
  • Train models in the workspace

5 – Explore developer tools for workspace interaction

  • Explore the studio
  • Explore the Python SDK
  • Explore the CLI

6 – Make data available in Azure Machine Learning

  • Understand URIs
  • Create a datastore
  • Create a data asset

7 – Work with compute targets in Azure Machine Learning

  • Create and use a compute instance
  • Create and use a compute cluster

8 – Work with environments in Azure Machine Learning

  • Understand environments
  • Explore and use curated environments
  • Create and use custom environments

9 – Find the best classification model with Automated Machine Learning

  • Preprocess data and configure featurization
  • Run an Automated Machine Learning experiment
  • Evaluate and compare models

10 – Track model training in Jupyter notebooks with MLflow

  • Configure MLflow for model tracking in notebooks
  • Train and track models in notebooks

11 – Run a training script as a command job in Azure Machine Learning

  • Convert a notebook to a script
  • Run a script as a command job
  • Use parameters in a command job

12 – Track model training with MLflow in jobs

  • Track metrics with MLflow
  • View metrics and evaluate models

13 – Run pipelines in Azure Machine Learning

  • Create components
  • Create a pipeline
  • Run a pipeline job

14 – Perform hyperparameter tuning with Azure Machine Learning

  • Define a search space
  • Configure a sampling method
  • Configure early termination
  • Use a sweep job for hyperparameter tuning

15 – Deploy a model to a managed online endpoint

  • Explore managed online endpoints
  • Deploy your MLflow model to a managed online endpoint
  • Deploy a model to a managed online endpoint
  • Test managed online endpoints

16 – Deploy a model to a batch endpoint

  • Understand and create batch endpoints
  • Deploy your MLflow model to a batch endpoint
  • Deploy a custom model to a batch endpoint
  • Invoke and troubleshoot batch endpoints

What People Are Saying About Us

Vanessa Boston

Really good progression on Excel Levels 1-3. Was able to take a decent survey of the capability of Excel and work on target areas like V-LookUp which were of special importance to me. You can save the Manuals Work Books for reviewing and recreating lessons as practice

Ashley Lackey

Carolyn did a great job at teaching the class and making all of the information feel manageable and easy to understand. Although the class was small and quiet she stayed engaging and thorough the entire time. I would definitely recommend this class to others!

Marissa Hogan

Carolyn was a phenomenal teacher! I learned many new things from the Excel 3 course that I took; I can’t wait to take other courses that Data Creative offers.

Mariya Petrovska

I absolutely loved the trainings I have taken with Data Creative. The instructors are very professional, easy to follow, knowledgeable and friendly. The groups are relatively small, so you get personal attention. I highly recommend them for everyone that wants to learn new skills or improve their performance.

Tony Wilson

Awesome training at a very good pace. Trainers were very open to example scenarios and unique questions. Highly recommend!

John Andrew Kenyon

Today I was took the excel level 2 class with Data Creative. The instructor was very professional and knowledgeable. He presented everything available to the lesson and more. I will definitely be taking the 3rd lesson through Data Creative.

Alejandra Cabrera

I completed the level 1 and level 2 PowerPoint training with Damian and I learned so much! I’ve been using PowerPoint for a while and had no idea that there was so much you could do with it. Damian was very easy to follow, friendly, and willing to answer any and all questions. I would definitely recommend this course for anyone looking to fine tune their skills in PowerPoint.

Antoinette Medina

Excellent communication and class setup. Classes are well structured, not too fast-paced. Nice materials, easy to review and follow even if you do not have two screens!

Robert Chalmers

Trish was an excellent facilitator and very personable. The class, Excel Level 4, was easy to follow and she encourage us all day to ask questions! She supplied us with a lot of useful information and “extras”. I learned what I was hoping to learn and had fun doing it.

Jody Old

I took the Excel Level 1, 2, 3, and the Power Point class. I have worked with Excel for over 20 years and I am blown away on how much I thought I knew, but really didn’t know. I would recommend Data Creative to anyone who would want to learn more about what different programs can do. I will be looking forward to any other class my place of employment will want me to take through this company