What Is Programming? And How To Get Started
January 28, 2025
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This course is part of Microsoft Azure Data Scientist Associate (DP-100) Exam Prep Professional Certificate
Instructor: Microsoft
31,321 already enrolled
Included with
(280 reviews)
Recommended experience
Intermediate level
Knowledge of basic mathematical concepts is important and some experience with Python is also beneficial.
(280 reviews)
Recommended experience
Intermediate level
Knowledge of basic mathematical concepts is important and some experience with Python is also beneficial.
How to plan and create a working environment for data science workloads on Azure
How to run data experiments and train predictive models
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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.
7 videos14 readings9 assignments1 discussion prompt
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.
7 videos7 readings8 assignments
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.
8 videos4 readings6 assignments1 discussion prompt
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Reviewed on Dec 3, 2023
Condense but solid course on ML basics. AND first time I was guided in a cloud provider for ML use cases without having to shed tears from frustration. Very good to gain first familiarity with Azure.
Reviewed on Feb 20, 2022
Great course with lots of insights. Definetly worth it!
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.
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