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Cleaning and Preparing Data in Microsoft Azure

Jared Rhodes

This course targets software developers and data scientists looking to understand the initial steps in a machine learning solution. The content will showcase methods and tools available using Microsoft Azure.

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This course targets software developers and data scientists looking to understand the initial steps in a machine learning solution. The content will showcase methods and tools available using Microsoft Azure.

No data science project of merit has ever started with great data ready to plug into an algorithm. In this course, Cleaning and Preparing Data in Microsoft Azure, you'll learn foundational knowledge of the steps required to utilize data in a machine learning project. First, you'll discover different types of data and languages. Next, you'll learn about managing large data sets and handling bad data. Finally, you'll explore how to utilize Azure Notebooks. When you're finished with this course, you'll have the skills and knowledge of preparing data needed for use in Microsoft Azure. Software required: Microsoft Azure.

This course is no longer available. Find something similar by browsing:
Data Preparation Data Cleaning Azure Notebooks Machine Learning Data Wrangling Azure Microsoft Azure

What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Examines techniques for properly preparing data for machine learning projects using Microsoft Azure tools, catering to software developers and data scientists
Develops skills in managing large data sets, handling bad data, and utilizing Azure Notebooks, all of which are key aspects of data preparation in machine learning
Teaches learners about different types of data and languages used in data science, providing a foundational understanding

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Reviews summary

Azure data prep: a solid foundation

According to students, this course provides a solid foundation in cleaning and preparing data specifically for Microsoft Azure. Learners frequently praised the clear explanations and the practical, hands-on labs using Azure Notebooks, which significantly helped in solidifying their understanding and applying concepts directly. The course is considered highly relevant for professionals looking to start with machine learning projects in Azure. However, some learners noted that while it's an excellent starting point, the pacing might be fast for absolute beginners and it lacks advanced depth for those with prior experience. A few also mentioned the potential for content to become slightly outdated due to Azure's rapid evolution.
Well-suited for beginners, but may lack advanced detail.
"I found some parts moved a bit quickly, especially if I was completely new to Azure's interface."
"The course covered the basics, but I felt it lacked depth for my prior experience in data manipulation."
"If I already knew basic data cleaning, this course didn't add much for me, I was hoping for more advanced techniques."
Features useful hands-on exercises with Azure Notebooks.
"I particularly appreciated the hands-on labs using Azure Notebooks; they really helped solidify the concepts."
"The hands-on components were incredibly useful, making it easy to follow along and apply what was taught directly in Azure."
"I found the practical exercises good, providing a solid environment to test my understanding."
Provides essential data preparation skills for Azure ML.
"This course was a fantastic introduction to data cleaning in Azure. The instructor explained complex topics..."
"As a software developer transitioning into data science, I gained a solid foundation from this course."
"I found this an excellent course for understanding the foundational steps of data wrangling within the Microsoft Azure ecosystem."
Azure's rapid evolution can make some content feel dated.
"Azure changes so fast that some parts felt slightly outdated even though it was recently published."
"The concepts are fine, but I wished for more up-to-date demos or alternative methods."
"I had to supplement my learning with current Azure documentation as the platform evolves, something to consider."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Cleaning and Preparing Data in Microsoft Azure with these activities:
Create a data cleaning and preparation plan
Helps develop a structured and methodic approach to data cleaning and preparation
Browse courses on Data Cleaning
Show steps
  • Identify data sources and types
  • Develop a data cleaning and preparation workflow
  • Test and validate data cleaning and preparation process
Follow tutorials on advanced data cleaning and preparation techniques
Enhances understanding of advanced techniques and industry best practices
Show steps
  • Identify and select relevant tutorials
  • Complete tutorials and practice techniques
Mentor junior data scientists in data cleaning and preparation
Reinforces knowledge through teaching and provides opportunities to share best practices
Show steps
  • Identify opportunities to mentor junior data scientists
  • Provide guidance and support on data cleaning and preparation tasks
Show all three activities

Career center

Learners who complete Cleaning and Preparing Data in Microsoft Azure will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use their expertise in machine learning and statistical analysis to develop and implement data-driven solutions for business problems. This course, Cleaning and Preparing Data in Microsoft Azure, helps build a foundation in data handling and wrangling techniques that are common for working with datasets in this role.
See salaries and explore the career path for Data Scientist
Data Engineer
Data Engineers design and build the infrastructure and tools that are used to store, process, and analyze data. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for analysis.
See salaries and explore the career path for Data Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models for a variety of applications. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for use in machine learning algorithms.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
Data Analysts apply their skills in statistics and data mining to sift through structured and unstructured data to help companies make data-driven decisions. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by building a foundation in data handling and wrangling techniques that are common for working with datasets in this role.
See salaries and explore the career path for Data Analyst
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for storage in a database.
See salaries and explore the career path for Database Administrator
Business Analyst
Business Analysts use data to identify and solve business problems. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for analysis.
See salaries and explore the career path for Business Analyst
Statistician
Statisticians use their expertise in statistics to collect, analyze, and interpret data. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for analysis.
See salaries and explore the career path for Statistician
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics and statistics to develop and implement solutions to problems in business and industry. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for analysis.
See salaries and explore the career path for Operations Research Analyst
Quantitative Analyst
Quantitative Analysts use their knowledge of mathematics and statistics to develop and implement financial models. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for analysis.
See salaries and explore the career path for Quantitative Analyst
Data Visualization Specialist
Data Visualization Specialists use their expertise in data visualization to create visual representations of data. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for visualization.
See salaries and explore the career path for Data Visualization Specialist
Data Architect
Data Architects design and build the architecture for data systems. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for storage and analysis.
See salaries and explore the career path for Data Architect
Software Engineer
Software Engineers apply their knowledge of programming languages and software development to design, develop, and maintain software applications. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for use in software applications.
See salaries and explore the career path for Software Engineer
Information Security Analyst
Information Security Analysts use their knowledge of information security to protect data from unauthorized access or use. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for secure storage.
See salaries and explore the career path for Information Security Analyst
Technical Writer
Technical Writers use their skills in writing and communication to create technical documentation. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for documentation.
See salaries and explore the career path for Technical Writer
Product Manager
Product Managers use their knowledge of product development to manage the development and launch of new products. This course, Cleaning and Preparing Data in Microsoft Azure, may be useful for this career path by providing an understanding of the process of cleaning and preparing data for use in product development.
See salaries and explore the career path for Product Manager

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Cleaning and Preparing Data in Microsoft Azure.
Cover image
Reinforcement Learning, second edition
Save
Provides a comprehensive overview of reinforcement learning, covering topics such as Markov decision processes, value iteration, and policy iteration. It valuable resource for students and researchers looking to learn more about reinforcement learning.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
Hands-On Artificial Intelligence for Banking
Save
Provides a comprehensive overview of machine learning, covering topics such as data preparation, model training, and evaluation. It valuable resource for students and researchers looking to learn more about machine learning.
Hands-On Artificial Intelligence for Banking: A...
Paperback
$$
Hands-On Artificial Intelligence for Banking: A...
Kindle Edition
$$
Cover image
Deep Learning
Save
Provides a comprehensive overview of deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for students and researchers looking to learn more about deep learning.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Speech and Language Processing. An Introduction to...
Save
Provides a comprehensive overview of speech and language processing, covering topics such as speech recognition, natural language understanding, and machine translation. It valuable resource for students and researchers looking to learn more about speech and language processing.
Speech and Language Processing An Introduction to...
Paperback
$$
Cover image
Probabilistic Graphical Models
Save
Provides a comprehensive overview of probabilistic graphical models, covering topics such as Bayesian networks, Markov networks, and conditional random fields. It valuable resource for students and researchers looking to learn more about probabilistic graphical models.
Probabilistic Graphical Models: Principles and...
Hardcover
$$$$
Probabilistic Graphical Models: Principles and...
Kindle Edition
$$$
Cover image
Natural Language Processing with Python
Save
Provides a comprehensive overview of natural language processing with Python, covering topics such as text classification, text clustering, and machine translation. It valuable resource for students and researchers looking to learn more about natural language processing.
Natural Language Processing with Python: Analyzing...
Paperback
$$$
Natural Language Processing with Python: Analyzing...
Kindle Edition
$$
Cover image
R for Data Science
Save
Provides a comprehensive overview of data manipulation with R, covering topics such as data cleaning, transformation, and visualization. It valuable resource for data scientists and software developers looking to learn more about data manipulation.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
Learning OpenCV 3
Save
Provides a comprehensive overview of computer vision with OpenCV, covering topics such as image processing, feature detection, and object recognition. It valuable resource for students and researchers looking to learn more about computer vision.
Learning OpenCV 3: Computer Vision in C++ with the...
Paperback
$$$
Learning OpenCV 3: Computer Vision in C++ with the...
Kindle Edition
$$$
Cover image
Data Quality
Save
Provides a practical guide to data cleaning, covering topics such as data validation, imputation, and transformation. It valuable reference for data scientists and software developers looking to improve the quality of their data.
Data Quality For The Information Age (Artech House...
Hardcover
$$$
Data Quality Management and Technology
Hardcover
$$
Data Quality: The Field Guide by Thomas Redman PhD...
Paperback Bunko
$$$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a practical introduction to machine learning with Python, covering topics such as data preparation, model training, and evaluation. It valuable resource for software developers and data scientists looking to learn more about machine learning.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Machine Learning Q and AI
Save
Provides a gentle introduction to machine learning, covering topics such as data preparation, model training, and evaluation. It valuable resource for beginners looking to learn more about machine learning.
Machine Learning Q and AI: 30 Essential Questions...
Paperback
$$
Machine Learning Q and AI: 30 Essential Questions...
Kindle Edition
$$

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Course image
Time
67 hours
Level
Introductory
Via
Pluralsight
Instructor
Jared Rhodes
Language
English
Cleaning and Preparing Data in Microsoft Azure belongs to the following collections:
  1. Implementing the Data Science Workflow in Microsoft Azure
  2. Microsoft Azure Data Scientist (DP-100)
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Examines techniques for properly preparing data for machine learning projects using Microsoft Azure tools, catering to software developers and data scientists
Develops skills in managing large data sets, handling bad data, and utilizing Azure Notebooks, all of which are key aspects of data preparation in machine learning
Teaches learners about different types of data and languages used in data science, providing a foundational understanding
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