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Self-paced course
Self-paced course
Machine Learning 1: Data Profiling
Machine Learning 1: Data Profiling
Rating 4.6
490 reviews
490 reviews
490 reviews
Course Description
This course is PART 1 of a 4-PART SERIES designed to help you build a fundamental understanding of machine learning:
QA & Data Profiling
Classification
Regression & Forecasting
Unsupervised Learning
In this course we’ll introduce the machine learning landscape and workflow, and review critical QA tips for cleaning and preparing raw data for analysis, including variable types, empty values, range & count calculations, table structures, and more.
We’ll cover univariate analysis with frequency tables, histograms, kernel densities, and profiling metrics, then dive into multivariate profiling tools like heat maps, violin & box plots, scatter plots, and correlation.
Throughout the course we’ll introduce case studies to solidify key concepts and tie them back to real world scenarios. You’ll clean up product inventory data for a local grocery, explore Olympic athlete demographics, visualize traffic accident frequency in New York City, and more.
NOTE: This is NOT a coding course, and doesn’t cover programming languages like Python or R. Our goal is to use familiar tools like Excel to demystify complex topics and explain exactly how they work.
If you’re ready to build the foundation for a successful career in data science, this is the course for you.
Course Description
This course is PART 1 of a 4-PART SERIES designed to help you build a fundamental understanding of machine learning:
QA & Data Profiling
Classification
Regression & Forecasting
Unsupervised Learning
In this course we’ll introduce the machine learning landscape and workflow, and review critical QA tips for cleaning and preparing raw data for analysis, including variable types, empty values, range & count calculations, table structures, and more.
We’ll cover univariate analysis with frequency tables, histograms, kernel densities, and profiling metrics, then dive into multivariate profiling tools like heat maps, violin & box plots, scatter plots, and correlation.
Throughout the course we’ll introduce case studies to solidify key concepts and tie them back to real world scenarios. You’ll clean up product inventory data for a local grocery, explore Olympic athlete demographics, visualize traffic accident frequency in New York City, and more.
NOTE: This is NOT a coding course, and doesn’t cover programming languages like Python or R. Our goal is to use familiar tools like Excel to demystify complex topics and explain exactly how they work.
If you’re ready to build the foundation for a successful career in data science, this is the course for you.
Course Content
5.25 video hours
Skills you'll learn in this course
Assess data quality with profiling metrics & visual summaries
Detect anomalies, outliers & missing patterns immediately
Generate automated data profiling reports in Python
Lay a solid foundation for informed algorithm selection
Meet your instructors
Josh MacCarty
Lead Machine Learning Instructor
Josh brings over a decade of applied Machine Learning experience to the Maven team, specializing in forecasting, predictive modeling, natural language processing, cluster analysis, and pricing optimization. He has a Bachelor's degree in Economics and was a Graduate Fellow for his Master's degree in Global Political Economy.
Student reviews
I am absolutely delighted with my experience at Maven Analytics! The outstanding courses, well-crafted guided projects, and thoughtfully designed learning paths have been pivotal in my data analysis journey. The Data Playground is a remarkable tool, allowing for hands-on application of the concepts learned. The comprehensive content and engaging format have significantly enhanced my skills in Data Profiling for Machine Learning. A heartfelt thank you to Maven Analytics for consistently delivering top-notch educational resources. I wholeheartedly recommend their courses for anyone looking to excel in the world of data analysis!
Andrew Hubbard
<p>I am absolutely delighted with my experience at Maven Analytics! The outstanding courses, well-crafted guided projects, and thoughtfully designed learning paths have been pivotal in my data analysis journey. The Data Playground is a remarkable tool, allowing for hands-on application of the concepts learned. The comprehensive content and engaging format have significantly enhanced my skills. A heartfelt thank you to Maven Analytics for consistently delivering top-notch educational resources. I wholeheartedly recommend their courses to anyone looking to excel in the world of data analysis!</p>
Andrew Hubbard
This course, ‘Machine Learning Part 1: Data Profiling’, provides a framework to learn about ML without simplifying the subject and without going too deep into certain details. I wouldn’t be able to accomplish that on my own, though all the information is out there on YouTube, LinkedIn, and other channels. But I would get overwhelmed, and after endless hours I would still have no idea about ML. I’m convinced that data literacy will become a basic core competency in our society worldwide. A basic understanding of Machine Learning is part of that competency and valuable even if one won’t apply it in a professional role. It means a lot to me that this topic is covered on your platform. Thank you, Maven Analytics, for creating this relevant, and accessible course series. Keep up the excellent work 👍🏼🔥.
Leandra
Included learning paths
Course credential
You’ll earn the course certification by completing this course and passing the assessment requirements
Machine Learning 1: Data Profiling
Machine Learning 1: Data Profiling
CPE Accreditation
CPE Credits:
0
Field of Study:
Information Technology
Delivery Method:
QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: May 25, 2023
Course Description
This course is PART 1 of a 4-PART SERIES designed to help you build a fundamental understanding of machine learning:
QA & Data Profiling
Classification
Regression & Forecasting
Unsupervised Learning
In this course we’ll introduce the machine learning landscape and workflow, and review critical QA tips for cleaning and preparing raw data for analysis, including variable types, empty values, range & count calculations, table structures, and more.
We’ll cover univariate analysis with frequency tables, histograms, kernel densities, and profiling metrics, then dive into multivariate profiling tools like heat maps, violin & box plots, scatter plots, and correlation.
Throughout the course we’ll introduce case studies to solidify key concepts and tie them back to real world scenarios. You’ll clean up product inventory data for a local grocery, explore Olympic athlete demographics, visualize traffic accident frequency in New York City, and more.
NOTE: This is NOT a coding course, and doesn’t cover programming languages like Python or R. Our goal is to use familiar tools like Excel to demystify complex topics and explain exactly how they work.
If you’re ready to build the foundation for a successful career in data science, this is the course for you.
Course Description
This course is PART 1 of a 4-PART SERIES designed to help you build a fundamental understanding of machine learning:
QA & Data Profiling
Classification
Regression & Forecasting
Unsupervised Learning
In this course we’ll introduce the machine learning landscape and workflow, and review critical QA tips for cleaning and preparing raw data for analysis, including variable types, empty values, range & count calculations, table structures, and more.
We’ll cover univariate analysis with frequency tables, histograms, kernel densities, and profiling metrics, then dive into multivariate profiling tools like heat maps, violin & box plots, scatter plots, and correlation.
Throughout the course we’ll introduce case studies to solidify key concepts and tie them back to real world scenarios. You’ll clean up product inventory data for a local grocery, explore Olympic athlete demographics, visualize traffic accident frequency in New York City, and more.
NOTE: This is NOT a coding course, and doesn’t cover programming languages like Python or R. Our goal is to use familiar tools like Excel to demystify complex topics and explain exactly how they work.
If you’re ready to build the foundation for a successful career in data science, this is the course for you.
Curriculum
1
Getting Started
1
Getting Started
1
Getting Started
2
ML Intro & Landscape
2
ML Intro & Landscape
2
ML Intro & Landscape
3
Preliminary Data QA
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
3
Preliminary Data QA
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
3
Preliminary Data QA
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
4
Univariate Profiling
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
4
Univariate Profiling
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
4
Univariate Profiling
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
5
Multivariate Profiling
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
5
Multivariate Profiling
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
5
Multivariate Profiling
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6 MIN
6
Course Feedback & Next Steps
6
Course Feedback & Next Steps
6
Course Feedback & Next Steps
Meet your instructors
Josh MacCarty
Lead Machine Learning Instructor
Josh brings over a decade of applied Machine Learning experience to the Maven team, specializing in forecasting, predictive modeling, natural language processing, cluster analysis, and pricing optimization. He has a Bachelor's degree in Economics and was a Graduate Fellow for his Master's degree in Global Political Economy.
Student reviews
I am absolutely delighted with my experience at Maven Analytics! The outstanding courses, well-crafted guided projects, and thoughtfully designed learning paths have been pivotal in my data analysis journey. The Data Playground is a remarkable tool, allowing for hands-on application of the concepts learned. The comprehensive content and engaging format have significantly enhanced my skills in Data Profiling for Machine Learning. A heartfelt thank you to Maven Analytics for consistently delivering top-notch educational resources. I wholeheartedly recommend their courses for anyone looking to excel in the world of data analysis!
Andrew Hubbard
<p>I am absolutely delighted with my experience at Maven Analytics! The outstanding courses, well-crafted guided projects, and thoughtfully designed learning paths have been pivotal in my data analysis journey. The Data Playground is a remarkable tool, allowing for hands-on application of the concepts learned. The comprehensive content and engaging format have significantly enhanced my skills. A heartfelt thank you to Maven Analytics for consistently delivering top-notch educational resources. I wholeheartedly recommend their courses to anyone looking to excel in the world of data analysis!</p>
Andrew Hubbard
This course, ‘Machine Learning Part 1: Data Profiling’, provides a framework to learn about ML without simplifying the subject and without going too deep into certain details. I wouldn’t be able to accomplish that on my own, though all the information is out there on YouTube, LinkedIn, and other channels. But I would get overwhelmed, and after endless hours I would still have no idea about ML. I’m convinced that data literacy will become a basic core competency in our society worldwide. A basic understanding of Machine Learning is part of that competency and valuable even if one won’t apply it in a professional role. It means a lot to me that this topic is covered on your platform. Thank you, Maven Analytics, for creating this relevant, and accessible course series. Keep up the excellent work 👍🏼🔥.
Leandra
Included learning paths
Course credential
You’ll earn the course certification by completing this course and passing the assessment requirements
Machine Learning 1: Data Profiling
Machine Learning 1: Data Profiling
CPE Accreditation
CPE Credits:
0
Field of Study:
Information Technology
Delivery Method:
QAS Self Study
Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.
For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.
*Last Updated: May 25, 2023
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