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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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/yo39xx/cleaning
What's inside
Syllabus
Course Overview
Transforming Data into Usable Datasets
Wrangling Data
Good to know
Good to know
Know what's good ,
what to watch for , 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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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
Show steps
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
Show steps
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
Show steps
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
Create a data cleaning and preparation plan
Show steps
Helps develop a structured and methodic approach to data cleaning and preparation
Browse courses on
Data Cleaning
Show steps
Show steps
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
Show steps
Enhances understanding of advanced techniques and industry best practices
Show steps
Show steps
Show steps
- Identify and select relevant tutorials
- Complete tutorials and practice techniques
Mentor junior data scientists in data cleaning and preparation
Show steps
Reinforces knowledge through teaching and provides opportunities to share best practices
Show steps
Show steps
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 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.
Data Engineer
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.
Machine Learning 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.
Statistician
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.
Data Architect
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.
Database Administrator
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.
Data Analyst
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.
Business Analyst
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.
Operations Research Analyst
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.
Data Visualization Specialist
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.
Quantitative 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.
Software Engineer
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.
Information Security Analyst
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.
Technical Writer
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.
Product Manager
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.
For more career information including salaries, visit:
OpenCourser.com/course/yo39xx/cleaning
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/yo39xx/cleaning
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Time
67 hours
Level
Introductory
Via
Pluralsight
Instructor
Jared Rhodes
Language
English
Good to know
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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