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Mike West
Pandas has become the gold standard for data wrangling in applied machine learning. This course will teach you the basics of data wrangling in Python using Pandas, including basic syntax, functions, and dataframe manipulation.
Read more
Pandas has become the gold standard for data wrangling in applied machine learning. This course will teach you the basics of data wrangling in Python using Pandas, including basic syntax, functions, and dataframe manipulation.
Read more
Pandas has become the gold standard for data wrangling in applied machine learning. This course will teach you the basics of data wrangling in Python using Pandas, including basic syntax, functions, and dataframe manipulation.
At the core of applied machine learning is a thorough knowledge of data wrangling. In this course, Data Wrangling with Pandas for Machine Learning Engineers, you will learn how to massage data into a modellable state. First, you will discover what data wrangling is and its importance to the machine learning process. Next, you will explore the Pandas DataFrame and see how data is manipulated within the DataFrame. Finally, you will learn how to build an accurate model with the cleansed dataset. When you are finished with this course, you will have a foundational knowledge of data wrangling that will help you as you move forward to becoming a machine learning engineer.
Register for this course and see more details by visiting:
OpenCourser.com/course/ttpdut/data
What's inside
Syllabus
Course Overview
Getting Started in Data Wrangling
Pandas DataFrame Basics
Pandas Data Structures
Read more
Syllabus
Course Overview
Getting Started in Data Wrangling
Pandas DataFrame Basics
Pandas Data Structures
Read more
Modeling the Cleansed Data
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a thorough foundation in data wrangling for aspiring ML Engineers, a core skill in the field
Taught by industry-renowned instructor Mike West, ensuring learners access to cutting-edge knowledge and insights
Emphasizes practical application, focusing on preparing learners to use data wrangling in real-world ML projects
Course materials include hands-on exercises, solidifying learners' understanding and proficiency in data wrangling
Develops expertise in using the Pandas library, an industry-standard tool for data manipulation
Prerequisites are not explicitly stated, potentially leaving learners with knowledge gaps if they lack prior experience in data wrangling or Python
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Save Data Wrangling with Pandas for Machine Learning Engineers to your list so you can find it easily later:
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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 Data Wrangling with Pandas for Machine Learning Engineers with these
activities:
Practice Python Basics (Lists, Dictionaries, Conditional Statements)
Show steps
Refreshes core coding concepts like data structures, control flow, and conditional statements to ensure a sturdy foundation for the course.
Browse courses on
Python Basics
Show steps
-
Review materials on Python lists, dictionaries, conditional statements, control flow
-
Complete practice problems on these concepts
-
Build a small Python program using these concepts
Create a Pandas Cheat Sheet Summary
Show steps
Strengthens understanding of Pandas by creating a personalized cheat sheet or summary of key concepts, functions, and syntax.
Browse courses on
Pandas
Show steps
-
Review course materials and identify key Pandas concepts
-
Create a custom summary document or cheat sheet
-
Keep the summary as concise and organized as possible
Follow a Pandas Tutorial
Show steps
Introduces the core functions and operations of Pandas, allowing students to gain hands-on experience with data manipulation techniques.
Browse courses on
Pandas
Show steps
-
Identify an online Pandas tutorial
-
Follow the tutorial thoroughly, completing all exercises
-
Experiment with applying the learned concepts in a Jupyter notebook
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Pandas User Group or Community
Show steps
Facilitates knowledge sharing and problem-solving through discussions with other Pandas users, fostering a collaborative learning environment.
Browse courses on
Pandas
Show steps
-
Identify Pandas user groups or communities online
-
Join the group and participate in discussions
-
Ask questions and share experiences with other members
Pandas Data Cleaning Challenges
Show steps
Enhances data cleaning skills by providing practical challenges and exercises that test Pandas knowledge in a focused manner.
Browse courses on
Pandas
Show steps
-
Find online Pandas data cleaning challenges
-
Attempt to solve these challenges using Pandas functions and operations
-
Compare your solutions to provided references or discuss in forums
Share a Pandas Data Manipulation Example
Show steps
Encourages active learning by having students demonstrate their understanding of Pandas by creating and sharing practical examples.
Browse courses on
Pandas
Show steps
-
Choose a specific Pandas data manipulation task
-
Develop a Python script or Jupyter notebook showcasing the solution
-
Write a blog post or create a presentation on the example
Develop a Data Cleaning Pipeline
Show steps
Provides an opportunity to apply Pandas for practical data cleaning tasks, enhancing understanding of data manipulation and preparation.
Browse courses on
Pandas
Show steps
-
Identify a dataset
-
Design a data cleaning pipeline using Pandas
-
Implement the pipeline and perform data cleaning
-
Evaluate the cleaned data
Participate in a Kaggle Competition Using Pandas
Show steps
Provides a real-world application of Pandas skills by participating in a data science competition, enhancing problem-solving and analytical abilities.
Browse courses on
Pandas
Show steps
-
Identify a Kaggle competition that uses Pandas
-
Team up with other students or participate individually
-
Apply Pandas to solve the competition's data challenges
Practice Python Basics (Lists, Dictionaries, Conditional Statements)
Show steps
Refreshes core coding concepts like data structures, control flow, and conditional statements to ensure a sturdy foundation for the course.
Browse courses on
Python Basics
Show steps
Show steps
Show steps
- Review materials on Python lists, dictionaries, conditional statements, control flow
- Complete practice problems on these concepts
- Build a small Python program using these concepts
Create a Pandas Cheat Sheet Summary
Show steps
Strengthens understanding of Pandas by creating a personalized cheat sheet or summary of key concepts, functions, and syntax.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Review course materials and identify key Pandas concepts
- Create a custom summary document or cheat sheet
- Keep the summary as concise and organized as possible
Follow a Pandas Tutorial
Show steps
Introduces the core functions and operations of Pandas, allowing students to gain hands-on experience with data manipulation techniques.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify an online Pandas tutorial
- Follow the tutorial thoroughly, completing all exercises
- Experiment with applying the learned concepts in a Jupyter notebook
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a Pandas User Group or Community
Show steps
Facilitates knowledge sharing and problem-solving through discussions with other Pandas users, fostering a collaborative learning environment.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify Pandas user groups or communities online
- Join the group and participate in discussions
- Ask questions and share experiences with other members
Pandas Data Cleaning Challenges
Show steps
Enhances data cleaning skills by providing practical challenges and exercises that test Pandas knowledge in a focused manner.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Find online Pandas data cleaning challenges
- Attempt to solve these challenges using Pandas functions and operations
- Compare your solutions to provided references or discuss in forums
Share a Pandas Data Manipulation Example
Show steps
Encourages active learning by having students demonstrate their understanding of Pandas by creating and sharing practical examples.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Choose a specific Pandas data manipulation task
- Develop a Python script or Jupyter notebook showcasing the solution
- Write a blog post or create a presentation on the example
Develop a Data Cleaning Pipeline
Show steps
Provides an opportunity to apply Pandas for practical data cleaning tasks, enhancing understanding of data manipulation and preparation.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify a dataset
- Design a data cleaning pipeline using Pandas
- Implement the pipeline and perform data cleaning
- Evaluate the cleaned data
Participate in a Kaggle Competition Using Pandas
Show steps
Provides a real-world application of Pandas skills by participating in a data science competition, enhancing problem-solving and analytical abilities.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify a Kaggle competition that uses Pandas
- Team up with other students or participate individually
- Apply Pandas to solve the competition's data challenges
Career center
Learners who complete Data Wrangling with Pandas for Machine Learning Engineers will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. They use data to create models that can predict outcomes or make decisions. This course provides a solid foundation in data wrangling, which is essential for Machine Learning Engineers to clean and prepare data for modeling. The course modules on 'Pandas DataFrame Basics' and 'Pandas Data Structures' are especially relevant.
AI Engineer
AI Engineer
AI Engineers design, develop, and maintain AI systems. This course helps build a foundation in data wrangling with Pandas, which is a key skill for AI Engineers who need to clean and prepare data for AI model development. The modules on 'Pandas Data Structures' and 'Modeling the Cleansed Data' are particularly relevant to this role.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course teaches the basics of data wrangling with Pandas, which is a key skill for Data Scientists who need to clean and prepare data for analysis and modeling. The modules on 'Getting Started in Data Wrangling' and 'Pandas DataFrame Basics' are particularly relevant to this role.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure that support data-driven applications. This course provides a foundation in data wrangling with Pandas, which is a key skill for Data Engineers who need to clean and prepare data for storage and processing. The modules on 'Pandas DataFrame Basics' and 'Modeling the Cleansed Data' are particularly relevant to this role.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts use data visualization tools and techniques to communicate data insights to stakeholders. This course helps build a foundation in data wrangling with Pandas, which is a key skill for Data Visualization Analysts who need to clean and prepare data for visualization. The modules on 'Pandas DataFrame Basics' and 'Modeling the Cleansed Data' are particularly relevant to this role.
Data Analyst
Data Analyst
A Data Analyst processes and analyzes data from a variety of sources to provide key decision-makers with useful insights. This course can help build a foundation in data wrangling, which is crucial for Data Analysts who need to prepare data for analysis. Particularly, the modules on 'Pandas Data Structures' and 'Modeling the Cleansed Data' are directly relevant to this role.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze financial data and make investment recommendations. This course provides a foundation in data wrangling with Pandas, which can be useful for Quantitative Analysts who need to clean and prepare data for analysis. The modules on 'Getting Started in Data Wrangling' and 'Pandas Data Structures' are particularly relevant to this role.
Business Analyst
Business Analyst
Business Analysts identify and analyze business needs and opportunities. They use data to make recommendations that can improve business outcomes. This course provides a foundation in data wrangling with Pandas, which can be useful for Business Analysts who need to clean and prepare data for analysis. The modules on 'Getting Started in Data Wrangling' and 'Pandas Data Structures' are particularly relevant to this role.
Data and Analytics Consultant
Data and Analytics Consultant
Data and Analytics Consultants help organizations improve their data and analytics capabilities. This course provides a foundation in data wrangling with Pandas, which can be useful for Data and Analytics Consultants who need to understand the data wrangling process and its importance to data-driven decision-making. The modules on 'Getting Started in Data Wrangling' and 'Pandas DataFrame Basics' are particularly relevant to this role.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. This course provides a foundation in data wrangling with Pandas, which can be useful for Statisticians who need to clean and prepare data for analysis. The module on 'Pandas DataFrame Basics' is particularly relevant to this role.
Machine Learning Manager
Machine Learning Manager
Machine Learning Managers lead and manage teams of machine learning engineers and scientists. This course provides a foundation in data wrangling with Pandas, which can be useful for Machine Learning Managers who need to understand the data wrangling process and its importance to the machine learning lifecycle. The modules on 'Getting Started in Data Wrangling' and 'Pandas Data Structures' are particularly relevant to this role.
Data Architect
Data Architect
Data Architects design and manage data systems and infrastructure. This course helps build a foundation in data wrangling with Pandas, which can be useful for Data Architects who need to clean and prepare data for storage and processing. The modules on 'Getting Started in Data Wrangling' and 'Pandas DataFrame Basics' are particularly relevant to this role.
Data Science Manager
Data Science Manager
Data Science Managers lead and manage teams of data scientists and engineers. This course provides a foundation in data wrangling with Pandas, which can be useful for Data Science Managers who need to understand the data wrangling process and its importance to the machine learning lifecycle. The modules on 'Getting Started in Data Wrangling' and 'Pandas Data Structures' are particularly relevant to this role.
Product Manager for AI/ML
Product Manager for AI/ML
Product Managers for AI/ML lead the development and management of AI/ML products. This course provides a foundation in data wrangling with Pandas, which can be useful for Product Managers who need to understand the data wrangling process and its importance to the development of AI/ML products. The module on 'Modeling the Cleansed Data' is particularly relevant to this role.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course helps build a foundation in data wrangling with Pandas, which can be useful for Software Engineers who work on data-driven applications. The modules on 'Getting Started in Data Wrangling' and 'Pandas DataFrame Basics' are particularly relevant to this role.
For more career information including salaries, visit:
OpenCourser.com/course/ttpdut/data
Reading list
We've selected nine 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
Data Wrangling with Pandas for Machine Learning Engineers.
Is an in-depth guide to the Pandas library for data manipulation and analysis in Python. It's a comprehensive reference for both beginners and experienced users, covering topics from data structures and indexing to data munging and advanced techniques.
Comprehensive guide to data analysis in Python, covering topics from data wrangling with Pandas and NumPy to data visualization and machine learning with Jupyter notebooks.
Provides a comprehensive introduction to data science, covering topics from data wrangling and analysis to machine learning and natural language processing. It's a great book for beginners who want to learn the basics of data science.
Comprehensive guide to machine learning with Python, covering topics from data wrangling and preprocessing to model training and evaluation. It's a great book for beginners who want to learn the basics of machine learning.
Comprehensive guide to machine learning with Python, covering topics from data wrangling and preprocessing to model training and evaluation. It's a great book for beginners who want to learn the basics of machine learning.
Comprehensive guide to machine learning with Python, covering topics from data wrangling and preprocessing to model training and evaluation. It's a great book for beginners who want to learn the basics of machine learning.
Comprehensive guide to machine learning with R, covering topics from data wrangling and preprocessing to model training and evaluation. It's a great book for beginners who want to learn the basics of machine learning.
Comprehensive guide to deep learning with Python, covering topics from neural networks and convolutional neural networks to recurrent neural networks and natural language processing. It's a great book for beginners who want to learn the basics of deep learning.
Comprehensive guide to natural language processing with Python, covering topics from tokenization and stemming to parsing and machine translation. It's a great book for beginners who want to learn the basics of natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ttpdut/data
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Time
60 hours
Level
Introductory
Via
Pluralsight
Instructor
Mike West
Language
English
Good to know
Provides a thorough foundation in data wrangling for aspiring ML Engineers, a core skill in the field
Taught by industry-renowned instructor Mike West, ensuring learners access to cutting-edge knowledge and insights
Emphasizes practical application, focusing on preparing learners to use data wrangling in real-world ML projects
Course materials include hands-on exercises, solidifying learners' understanding and proficiency in data wrangling
Develops expertise in using the Pandas library, an industry-standard tool for data manipulation
Prerequisites are not explicitly stated, potentially leaving learners with knowledge gaps if they lack prior experience in data wrangling or Python
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