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Ryan Ahmed
In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. This guided project is the first of a series of multiple guided projects (learning path) that is designed for anyone who wants to master data analysis with pandas.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/3c00rq/mastering
What's inside
Syllabus
Project Overview
In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. This guided project is the first of a series of multiple guided projects (learning path) that is designed for anyone who wants to master data analysis with pandas.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Guides learners through real-world, end-to-end tasks
Aimed at learners who have no prior data analysis knowledge or experience
Provides a solid foundation in data analysis and manipulation using Pandas
This course is the first in a comprehensive series covering all aspects of data analysis with Pandas
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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 Mastering Data Analysis with Pandas with these
activities:
Course Material Compilation
Show steps
Ensure you have all necessary course materials for effective learning.
Show steps
-
Download and print the course syllabus and schedule.
-
Create a dedicated folder for the course materials.
-
Organize and file all relevant assignments, notes, and resources.
Review 'Data Manipulation with Pandas'
Show steps
Familiarize yourself with a valuable resource for data analysis and manipulation in advance of the course.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
-
Read the first three chapters of the book.
-
Summarize the key concepts and techniques introduced in the book.
-
Try out the examples provided in the book.
Python Refresher
Show steps
Brush up on your Python basics for a stronger foundation.
Browse courses on
Python
Show steps
-
Review your Python notes or textbooks.
-
Complete a few online coding challenges or exercises.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Pandas Tutorial Practice
Show steps
Reinforce your understanding of Pandas through hands-on practice.
Browse courses on
Pandas
Show steps
-
Visit the Pandas documentation website and work through their tutorial.
-
Complete at least 10 exercises on the Pandas practice platform.
Study Group
Show steps
Collaborate with peers to enhance your learning and understanding of Pandas.
Show steps
-
Form a study group with other students in the course.
-
Meet regularly to discuss concepts, share tips, and work on assignments together.
-
Review each other's work and provide feedback.
Pandas Guided Projects
Show steps
Deepen your knowledge by following guided projects specific to Pandas.
Browse courses on
Pandas
Show steps
-
Find a platform or online resource that offers guided projects for Pandas.
-
Choose a project that aligns with your interests and skill level.
-
Follow the instructions and complete the project.
Data Science Meetup
Show steps
Connect with other professionals in the field and expand your network.
Show steps
-
Find a local Data Science Meetup group and attend an event.
-
Introduce yourself and network with other attendees.
-
Attend a talk or workshop related to Pandas or data analysis.
Data Analysis Project
Show steps
Apply your acquired skills to a practical project.
Browse courses on
Pandas
Show steps
-
Identify a dataset that interests you.
-
Use Pandas to clean, manipulate, and analyze the data.
-
Create visualizations and summarize your findings.
Kaggle Competition
Show steps
Test and expand your skills in a competitive environment.
Browse courses on
Pandas
Show steps
-
Identify a Kaggle competition related to Pandas.
-
Join the competition and download the dataset.
-
Develop a solution using Pandas and other relevant techniques.
Course Material Compilation
Show steps
Ensure you have all necessary course materials for effective learning.
Show steps
Show steps
Show steps
- Download and print the course syllabus and schedule.
- Create a dedicated folder for the course materials.
- Organize and file all relevant assignments, notes, and resources.
Review 'Data Manipulation with Pandas'
Show steps
Familiarize yourself with a valuable resource for data analysis and manipulation in advance of the course.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
Show steps
Show steps
- Read the first three chapters of the book.
- Summarize the key concepts and techniques introduced in the book.
- Try out the examples provided in the book.
Python Refresher
Show steps
Brush up on your Python basics for a stronger foundation.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review your Python notes or textbooks.
- Complete a few online coding challenges or exercises.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Pandas Tutorial Practice
Show steps
Reinforce your understanding of Pandas through hands-on practice.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Visit the Pandas documentation website and work through their tutorial.
- Complete at least 10 exercises on the Pandas practice platform.
Study Group
Show steps
Collaborate with peers to enhance your learning and understanding of Pandas.
Show steps
Show steps
Show steps
- Form a study group with other students in the course.
- Meet regularly to discuss concepts, share tips, and work on assignments together.
- Review each other's work and provide feedback.
Pandas Guided Projects
Show steps
Deepen your knowledge by following guided projects specific to Pandas.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Find a platform or online resource that offers guided projects for Pandas.
- Choose a project that aligns with your interests and skill level.
- Follow the instructions and complete the project.
Data Science Meetup
Show steps
Connect with other professionals in the field and expand your network.
Show steps
Show steps
Show steps
- Find a local Data Science Meetup group and attend an event.
- Introduce yourself and network with other attendees.
- Attend a talk or workshop related to Pandas or data analysis.
Data Analysis Project
Show steps
Apply your acquired skills to a practical project.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify a dataset that interests you.
- Use Pandas to clean, manipulate, and analyze the data.
- Create visualizations and summarize your findings.
Kaggle Competition
Show steps
Test and expand your skills in a competitive environment.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify a Kaggle competition related to Pandas.
- Join the competition and download the dataset.
- Develop a solution using Pandas and other relevant techniques.
Career center
Learners who complete Mastering Data Analysis with Pandas will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts focus on collecting, processing, and analyzing large datasets to extract valuable insights for businesses. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network can provide a strong foundation for individuals seeking to become Data Analysts. The course covers essential concepts of data analysis using Pandas, a powerful Python library for data manipulation. By learning how to read, clean, and analyze data with Pandas, learners can develop the skills needed to succeed as Data Analysts.
Data Scientist
Data Scientist
Data Scientists utilize statistical and analytical methods to extract insights from data and solve complex business problems. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network can be a valuable asset for individuals aspiring to become Data Scientists. The course provides a thorough understanding of data analysis techniques and methodologies, including data cleaning, data exploration, and data visualization with Pandas. These skills are essential for Data Scientists who work with large datasets and need to derive meaningful insights.
Business Analyst
Business Analyst
Business Analysts bridge the gap between business and technology by analyzing data and providing insights to support decision-making. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network can be beneficial for individuals pursuing a career as a Business Analyst. The course covers essential data analysis concepts and techniques, including data visualization, data mining, and forecasting. These skills empower Business Analysts to extract valuable insights from data and communicate them effectively to stakeholders.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts (Quants) apply mathematical and statistical models to analyze and predict financial markets. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network can provide a solid foundation for individuals aiming to become Quantitative Analysts. The course covers fundamental concepts of data analysis, statistical modeling, and data visualization with Pandas. By developing these skills, learners can gain a competitive edge in the field of quantitative finance.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models to solve real-world problems. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be helpful for individuals seeking to transition into Machine Learning Engineering. The course provides a foundational understanding of data analysis techniques and methodologies, including data cleaning, feature engineering, and data visualization with Pandas. These skills are essential for Machine Learning Engineers who work with large datasets and need to prepare data for modeling.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure to support data-driven applications. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals interested in pursuing a career as a Data Engineer. The course covers essential concepts of data analysis, data cleaning, and data transformation with Pandas. These skills can be beneficial for Data Engineers who need to work with large datasets and ensure data quality and consistency.
Data Architect
Data Architect
Data Architects design and implement data management solutions to meet business needs. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network can be helpful for individuals aspiring to become Data Architects. The course provides a fundamental understanding of data analysis techniques and methodologies, including data modeling, data integration, and data governance with Pandas. These skills can be beneficial for Data Architects who need to design and manage complex data systems.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand market trends and consumer behavior. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network can be beneficial for individuals seeking a career in Market Research. The course provides a strong foundation in data analysis techniques and methodologies, including data visualization, data mining, and data interpretation with Pandas. These skills are essential for Market Researchers who need to extract insights from data and develop effective marketing strategies.
Risk Analyst
Risk Analyst
Risk Analysts assess and manage risks in various domains such as finance, insurance, and healthcare. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals interested in becoming Risk Analysts. The course provides a foundational understanding of data analysis techniques and methodologies, including data modeling, data simulation, and data visualization with Pandas. These skills can be beneficial for Risk Analysts who need to analyze and mitigate risks effectively.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to optimize business processes and systems. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be helpful for individuals seeking a career as an Operations Research Analyst. The course provides a foundational understanding of data analysis techniques and methodologies, including linear programming, simulation, and data visualization with Pandas. These skills can be beneficial for Operations Research Analysts who need to analyze and improve business operations.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to analyze biological and medical data. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals interested in pursuing a career as a Biostatistician. The course provides a foundational understanding of data analysis techniques and methodologies, including statistical modeling, data visualization, and data interpretation with Pandas. These skills can be beneficial for Biostatisticians who need to analyze and interpret health-related data.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations and assess financial performance. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals seeking a career as a Financial Analyst. The course provides a foundational understanding of data analysis techniques and methodologies, including financial modeling, data visualization, and data interpretation with Pandas. These skills can be beneficial for Financial Analysts who need to analyze and interpret financial data effectively.
Insurance Analyst
Insurance Analyst
Insurance Analysts assess and manage risks in the insurance industry. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals interested in pursuing a career as an Insurance Analyst. The course provides a foundational understanding of data analysis techniques and methodologies, including data modeling, data simulation, and data visualization with Pandas. These skills can be beneficial for Insurance Analysts who need to analyze and mitigate risks effectively.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess and manage risks in the insurance and finance industries. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals interested in becoming Actuaries. The course provides a foundational understanding of data analysis techniques and methodologies, including statistical modeling, data simulation, and data visualization with Pandas. These skills can be beneficial for Actuaries who need to analyze and mitigate risks effectively.
Data Journalist
Data Journalist
Data Journalists use data to tell stories and provide insights to the public. The 'Mastering Data Analysis with Pandas' course from Coursera Project Network may be useful for individuals interested in pursuing a career as a Data Journalist. The course provides a foundational understanding of data analysis techniques and methodologies, including data visualization, data mining, and data interpretation with Pandas. These skills can be beneficial for Data Journalists who need to analyze and interpret data effectively and communicate their findings clearly to the public.
For more career information including salaries, visit:
OpenCourser.com/course/3c00rq/mastering
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
Mastering Data Analysis with Pandas.
Save
Provides a comprehensive overview of data manipulation with Pandas. It covers topics such as data cleaning, transformation, and aggregation. It's a good resource for learners who want to learn more about the advanced features of Pandas.
Comprehensive guide to data manipulation with Pandas. It covers all the basics of data manipulation, as well as more advanced topics such as data cleaning, merging, and reshaping.
Save
Provides a comprehensive overview of data analysis with Python. It covers topics such as data cleaning, manipulation, visualization, and machine learning. It's a good resource for learners who want to learn more about data analysis and how to use Python for data analysis.
Great companion to the course, providing a comprehensive overview of Python for data analysis. It covers the basics of Python, as well as more advanced topics such as data manipulation, visualization, and machine learning.
Comprehensive guide to machine learning using Scikit-Learn, Keras, and TensorFlow. It covers all the basics of machine learning, as well as more advanced topics such as supervised learning, unsupervised learning, and deep learning.
Provides a comprehensive overview of machine learning with Python. It covers topics such as supervised learning, unsupervised learning, and deep learning. It's a good resource for learners who want to learn more about machine learning and how to use Python for machine learning.
Save
Provides a comprehensive overview of the art of data science. It covers topics such as data ethics, data privacy, and data bias. It's a good resource for learners who want to learn more about the ethical and social implications of data science.
Provides a comprehensive overview of deep learning with Python. It covers topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It's a good resource for learners who want to learn more about deep learning and how to use Python for deep learning.
Provides a comprehensive overview of natural language processing with Python. It covers topics such as tokenization, stemming, lemmatization, and parsing. It's a good resource for learners who want to learn more about natural language processing and how to use Python for natural language processing.
Provides a comprehensive overview of data visualization with Python. It covers topics such as data visualization basics, interactive visualization, and geospatial visualization. It's a good resource for learners who want to learn more about data visualization and how to use Python for data visualization.
Comprehensive guide to data science using Python. It covers all the basics of data science, as well as more advanced topics such as machine learning, deep learning, and natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3c00rq/mastering
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
Guides learners through real-world, end-to-end tasks
Aimed at learners who have no prior data analysis knowledge or experience
Provides a solid foundation in data analysis and manipulation using Pandas
This course is the first in a comprehensive series covering all aspects of data analysis with Pandas
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