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There are 3 modules in this course
Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models.
This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production.
From the most basic classical machine learning models, to exploratory data analysis and customizing architectures, you’ll be guided by easy -to-digest conceptual content and interactive Jupyter notebooks.
If you already have some idea what machine learning is about or you have a strong mathematical background this course is perfect for you. These modules teach some machine learning concepts, but move fast so they can get to the power of using tools like scikit-learn, TensorFlow, and PyTorch. This learning path is also the best one for you if you're looking for just enough familiarity to understand machine learning examples for products like Azure ML or Azure Databricks. It's also a good place to start if you plan to move beyond classic machine learning and get an education in deep learning and neural networks, which we only introduce here.
This program consists of 5 courses to help prepare you to take the Exam DP-100: Designing and Implementing a Data Science Solution on Azure. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at cloud scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure . Each course teaches you the concepts and skills that are measured by the exam.
Data exploration and analysis is at the core of data science. Data scientists require skills in languages like Python to explore, visualize, and manipulate data. In this module, you will learn how to use Python to explore, visualize, and manipulate data. You will also learn how regression can be used to create a machine learning model that predicts numeric values. You will use the scikit-learn framework in Python to train and evaluate a regression model.
Exam DP-100: Designing and Implementing a Data Science Solution on Azure certification•5 minutes
Lesson introduction•2 minutes
Lesson summary•1 minute
Lesson introduction•1 minute
What is regression?•6 minutes
Lesson summary•1 minute
14 readings•Total 177 minutes
Course syllabus•15 minutes
Exam DP-100: Skills Measured•15 minutes
How to be successful in this course•15 minutes
Explore data with NumPy and Pandas•10 minutes
Exercise - Explore data with NumPy and Pandas•10 minutes
Visualize data•10 minutes
Exercise - Visualize data with Matplotlib•10 minutes
Examine real world data•10 minutes
Exercise - Examine real world data•12 minutes
Exercise - Train and evaluate a regression model•30 minutes
Discover new regression models•10 minutes
Exercise - Experiment with more powerful regression models•10 minutes
Improve models with hyperparameters•10 minutes
Exercise - Optimize and save models•10 minutes
9 assignments•Total 68 minutes
Test prep •21 minutes
Exercise Quiz•2 minutes
Exercise Quiz•3 minutes
Exercise Quiz•3 minutes
Knowledge check •15 minutes
Exercise quiz•3 minutes
Exercise quiz•3 minutes
Exercise Quiz•3 minutes
Knowledge check •15 minutes
1 discussion prompt•Total 30 minutes
Meet and Greet•30 minutes
Train and evaluate classification and clustering models
Module 2•3 hours to complete
Module details
Classification is a kind of machine learning used to categorize items into classes. In this module, you will learn how classification can be used to create a machine learning model that predicts categories, or classes. You will use the scikit-learn framework in Python to train and evaluate a classification model. You will also learn how clustering can be used to create unsupervised machine learning models that group data observations into clusters. You will use the scikit-learn framework in Python to train a clustering model.
What's included
7 videos7 readings8 assignments
Show info about module content
7 videos•Total 9 minutes
Lesson introduction•1 minute
What is classification?•3 minutes
Evaluate classification models•2 minutes
Lesson summary•1 minute
Lesson introduction•1 minute
What is clustering•1 minute
Lesson summary•0 minutes
7 readings•Total 110 minutes
Exercise - Train and evaluate a classification model•30 minutes
Exercise - Perform classification with alternative metrics•10 minutes
Exercise - Train and evaluate multiclass classification models•10 minutes
Exercise - Train and evaluate a clustering model•30 minutes
Evaluate different types of clustering•10 minutes
Exercise - Train and evaluate advanced clustering models•10 minutes
8 assignments•Total 66 minutes
Test prep •21 minutes
Exercise quiz•3 minutes
Exercise Quiz•3 minutes
Exercise Quiz•3 minutes
Knowledge check•15 minutes
Exercise quiz•3 minutes
Exercise quiz•3 minutes
Knowledge check •15 minutes
Train and evaluate deep learning models
Module 3•3 hours to complete
Module details
In this module, you will learn about the fundamental principles of deep learning, and how to create deep neural network models using PyTorch or Tensorflow. You will also explore the use of convolutional neural networks to create image classification models.
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Learner reviews
4.5
331 reviews
5 stars
67.67%
4 stars
24.47%
3 stars
3.02%
2 stars
2.11%
1 star
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Showing 3 of 331
S
SA
5·
Reviewed on Feb 7, 2023
This course is very easy to understand and have a great value for new data science professionals. To the point explanations and engaging content by team Microsoft.
G
GM
4·
Reviewed on Jul 31, 2025
some answers are wrong in 4th course. Rest of the course was very comprehensive and a must do before dp100.
J
JK
5·
Reviewed on Feb 20, 2022
Great course with lots of insights. Definetly worth it!
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What will I get if I subscribe to this Certificate?
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