We may earn an affiliate commission when you visit our partners.
Jupyter Notebook, Numpy, and Pandas
Mat Leonard,
Parnian Barekatain,
Eddy Shyu,
Brok Bucholtz,
Elizabeth Otto Hamel,
Cindy Lin,
Cezanne Camacho,
Arpan Chakraborty,
Luis Serrano,
and
Juan Delgado
Mat Leonard,
Parnian Barekatain,
Eddy Shyu,
Brok Bucholtz,
Elizabeth Otto Hamel,
Cindy Lin,
Cezanne Camacho,
Arpan Chakraborty,
Luis Serrano,
and
Juan Delgado
Register for this course and see more details by visiting:
OpenCourser.com/course/rz9asi/jupyter
What's inside
Syllabus
Learn how to use Jupyter Notebooks to create documents combining code, text, images, and more.
Learn the basics of NumPy and how to use it to create and manipulate arrays.
Learn the basics of Pandas Series and DataFrames and how to use them to load and process data.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
This course introduces Jupyter Notebooks and the basics of NumPy and Pandas for data analysis
The instructors for this course are recognized for their work in data analysis
Save this course
Save Jupyter Notebook, Numpy, and Pandas to your list so you can find it easily later:
Save
Save
Activities
Coming soon
We're preparing activities for
Jupyter Notebook, Numpy, and Pandas.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Jupyter Notebook, Numpy, and Pandas will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use their expertise in data analysis, machine learning, and artificial intelligence to solve complex business problems. They develop and implement data-driven solutions that can improve decision-making, predict outcomes, and optimize processes. Jupyter Notebook, Numpy, and Pandas are essential tools for Data Scientists as they allow them to efficiently work with large datasets, train machine learning models, and visualize insights. This course provides a strong foundation in these tools, enabling learners to build a successful career as a Data Scientist.
Data Analyst
Data Analyst
Data Analysts use their knowledge of data, statistics, and programming to extract meaningful insights from data. These insights can be used to improve business decisions and optimize operations. Jupyter Notebook, Numpy, and Pandas are essential tools for Data Analysts as they allow them to efficiently handle, manipulate, and analyze large datasets. This course provides a solid foundation in these tools, equipping learners with the skills needed to succeed in this growing field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. They work closely with Data Scientists and other stakeholders to develop data-driven solutions that address business problems. Jupyter Notebook, Numpy, and Pandas are essential tools for Machine Learning Engineers as they allow them to efficiently work with large datasets, preprocess data, and evaluate model performance. This course provides a solid foundation in these tools, equipping learners with the skills needed to succeed in this rapidly growing field.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their knowledge of mathematics, statistics, and programming to analyze financial data and make investment decisions. They develop and implement trading strategies, risk management models, and other quantitative solutions. Jupyter Notebook, Numpy, and Pandas are essential tools for Quantitative Analysts as they allow them to efficiently handle, manipulate, and analyze large financial datasets. This course provides a solid foundation in these tools, giving learners a competitive advantage in this highly competitive field.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers design and develop data visualizations that communicate insights effectively. They work closely with Data Analysts, Data Scientists, and other stakeholders to create visualizations that can inform decision-making, identify trends, and uncover hidden patterns. Jupyter Notebook, Numpy, and Pandas are essential tools for Data Visualization Engineers as they allow them to efficiently work with large datasets, preprocess data, and create interactive visualizations. This course provides a solid foundation in these tools, equipping learners with the skills needed to succeed in this emerging field.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business processes, data analysis, and technology to identify and solve business problems. They work closely with stakeholders to gather requirements, analyze data, and develop solutions that improve efficiency, productivity, and customer satisfaction. Jupyter Notebook, Numpy, and Pandas are essential tools for Business Analysts as they allow them to efficiently work with large datasets, identify trends, and make data-driven recommendations. This course provides a solid foundation in these tools, equipping learners with the skills needed to succeed in this in-demand field.
Statistician
Statistician
Statisticians use their knowledge of data analysis, probability, and statistics to solve problems in various fields. They design and conduct surveys, analyze data, and develop statistical models to draw meaningful conclusions. Jupyter Notebook, Numpy, and Pandas are essential tools for Statisticians as they allow them to efficiently work with large datasets, perform statistical analyses, and visualize results. This course provides a solid foundation in these tools, giving learners a competitive advantage in this growing field.
Actuary
Actuary
Actuaries use their knowledge of mathematics, statistics, and finance to assess and manage risk. They develop and implement insurance policies, pension plans, and other financial products. Jupyter Notebook, Numpy, and Pandas are essential tools for Actuaries as they allow them to efficiently work with large datasets, model financial risk, and make informed decisions. This course provides a solid foundation in these tools, giving learners a competitive advantage in this specialized field.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of finance, accounting, and economics to analyze financial data and make investment recommendations. They develop and implement financial models, conduct due diligence, and provide insights to clients. Jupyter Notebook, Numpy, and Pandas are essential tools for Financial Analysts as they allow them to efficiently work with large financial datasets, perform financial analysis, and visualize results. This course provides a solid foundation in these tools, giving learners a competitive advantage in this competitive field.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work closely with stakeholders to gather requirements, design solutions, and implement code. Jupyter Notebook, Numpy, and Pandas are essential tools for Software Engineers who work with data-intensive applications. This course provides a solid foundation in these tools, giving learners a competitive advantage in this rapidly growing field.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. They work closely with Data Scientists, Data Analysts, and other stakeholders to ensure that data is available, reliable, and accessible. Jupyter Notebook, Numpy, and Pandas are essential tools for Data Engineers as they allow them to efficiently work with large datasets, perform data transformations, and create data pipelines. This course provides a solid foundation in these tools, giving learners a competitive advantage in this emerging field.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. They work closely with other IT professionals to ensure that data is stored, managed, and accessed efficiently. Jupyter Notebook, Numpy, and Pandas are essential tools for Database Administrators who work with large datasets. This course provides a solid foundation in these tools, giving learners a competitive advantage in this in-demand field.
Market Researcher
Market Researcher
Market Researchers conduct research to understand consumer behavior, market trends, and competitive landscapes. They collect and analyze data to provide insights that help businesses make informed decisions. Jupyter Notebook, Numpy, and Pandas are essential tools for Market Researchers as they allow them to efficiently work with large datasets, identify trends, and visualize results.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics, statistics, and computer science to solve complex problems in business and industry. They develop and implement mathematical models to optimize operations, improve efficiency, and reduce costs. Jupyter Notebook, Numpy, and Pandas are essential tools for Operations Research Analysts as they allow them to efficiently work with large datasets, build models, and visualize results. This course provides a solid foundation in these tools, giving learners a competitive advantage in this specialized field.
Risk Manager
Risk Manager
Risk Managers identify, assess, and manage risks to an organization. They work closely with other stakeholders to develop and implement risk management strategies. Jupyter Notebook, Numpy, and Pandas are essential tools for Risk Managers as they allow them to efficiently work with large datasets, analyze risk factors, and visualize results. This course provides a solid foundation in these tools, giving learners a competitive advantage in this in-demand field.
For more career information including salaries, visit:
OpenCourser.com/course/rz9asi/jupyter
Reading list
We've selected 13 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
Jupyter Notebook, Numpy, and Pandas.
Provides a comprehensive overview of data science using Python, covering topics such as data manipulation, visualization, machine learning, and deep learning. It valuable reference for anyone who wants to learn more about data science and how to use Python to solve real-world problems.
Provides a comprehensive overview of Pandas, covering topics such as data structures, data manipulation, and data analysis. It valuable resource for anyone who wants to learn more about Pandas and how to use it for data science.
Provides a hands-on introduction to data science, covering topics such as data collection, data cleaning, data analysis, and machine learning. It valuable resource for anyone who wants to learn more about data science and how to use Python to solve real-world problems.
Provides a comprehensive overview of machine learning using Python, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about machine learning and how to use Python to solve real-world problems.
Provides a comprehensive overview of deep learning using Python, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn more about deep learning and how to use Python to solve real-world problems.
Provides a practical introduction to data science for business professionals, covering topics such as data collection, data analysis, and data visualization. It valuable resource for anyone who wants to learn more about data science and how to use it to improve business decision-making.
Provides a gentle introduction to data analytics, covering topics such as data collection, data cleaning, data analysis, and data visualization. It valuable resource for anyone who wants to learn more about data analytics and how to use it to solve real-world problems.
Provides a gentle introduction to machine learning, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about machine learning and how to use it to solve real-world problems.
Provides a hands-on introduction to deep learning using Fastai and PyTorch, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn more about deep learning and how to use it to solve real-world problems.
Provides a comprehensive overview of machine learning using Scikit-Learn, Keras, and TensorFlow, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about machine learning and how to use Python to solve real-world problems.
Save
Provides a comprehensive overview of data science using R, covering topics such as data manipulation, data analysis, and data visualization. It valuable resource for anyone who wants to learn more about data science and how to use R to solve real-world problems.
Provides a comprehensive overview of machine learning using R, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about machine learning and how to use R to solve real-world problems.
Provides a comprehensive overview of deep learning using R, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn more about deep learning and how to use R to solve real-world problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rz9asi/jupyter
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Time
180 hours
Level
Advanced
Via
Udacity
Instructors
Mat Leonard
Parnian Barekatain
Eddy Shyu
Brok Bucholtz
Elizabeth Otto Hamel
Cindy Lin
Cezanne Camacho
Arpan Chakraborty
Luis Serrano
Juan Delgado
Language
English
Good to know
This course introduces Jupyter Notebooks and the basics of NumPy and Pandas for data analysis
The instructors for this course are recognized for their work in data analysis
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser