Jupyter is a web application used to create and share documents. These documents include codes, images, and text. The open-source platform allows you to create different notebooks for your codes with your explanations, data, and results. With Jupyter, you are able to share your notebooks as an attachment to collaborate with others and improve your results.

Why is it important to learn about Jupyter?

It's important to learn about Jupyter to facilitate your data sharing and improve your results. Being able to share your explanations, data, code, and images with others all in one easy to use attachment will save you time and keep your data up to date with the modifications made by others. It's also important to learn to use Jupyter to create tutorials for educational purposes. This allows you to present your findings in a way for everyone to understand and lets others try out your code and simulate modifications to learn and improve from one another.

How can online courses help me learn about Jupyter?

Online courses will help you learn about Jupyter by offering the flexibility you need to learn on your own time all while having experts available to answer questions and who will guide you through each module in the course. You'll broaden your knowledge of data science topics such as Python, SQL, and deep learning. These courses will give you detailed lectures, Guided Projects, and assignments that will test your knowledge to measure your understanding of the material. Discover the foundations of applied data science, computer programming, and machine learning, or uncover advanced studies such as understanding deepfakes with Keras. You will be able to follow along video tutorials to learn to use the platform and create projects that simulate true tests.

What skills or experience do I need to already have, before starting to learn about Jupyter?

To learn about Jupyter, you should have prior knowledge in coding and data analysis. Having this prior knowledge will allow you to understand how to create the notebooks and analyze the results. It will also help you create simulations and be able to learn from other's shared data. Before starting to learn about Jupyter you should also have knowledge in coding programs and languages to understand the language and be able to translate the results to test modifications or run other simulations.

What are the benefits of taking an online Jupyter course?

Online Jupyter courses offer a convenient and flexible way to enhance your knowledge or learn new Jupyter skills. Choose from a wide range of Jupyter courses offered by top universities and industry leaders tailored to various skill levels.

What Jupyter courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Jupyter, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top Jupyter Courses - Learn Jupyter Online

Explore the Jupyter Course Catalog

Status: New
Status: Free Trial
University of Colorado Boulder
BiteSize Python for Intermediate Learners
Skills you'll gain: Matplotlib, Object Oriented Programming (OOP), Plotly, Seaborn, Data Visualization Software, Object Oriented Design, Pandas (Python Package), NumPy, Statistical Visualization, Interactive Data Visualization, Software Documentation, Scatter Plots, Box Plots, Data Structures, Maintainability, Programming Principles, Software Design, Data Import/Export, Data Manipulation, Data Cleansing
4.6
Rating, 4.6 out of 5 stars
6 reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
Universidad Austral
NLP System Architecture and Dev-Ops
Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Application Lifecycle Management, Systems Architecture, Application Development, Algorithms, Software Architecture, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Machine Learning Algorithms, Software Development Life Cycle, Machine Learning
Beginner · Course · 1 - 4 Weeks
The University of Chicago
Global Warming II: Create Your Own Models in Python
Skills you'll gain: Python Programming, Mathematical Modeling, NumPy, Environmental Science, Jupyter, Scientific Visualization, Matplotlib, Simulations, Numerical Analysis, Differential Equations
4.1
Rating, 4.1 out of 5 stars
55 reviews
Mixed · Course · 1 - 3 Months
Status: Free Trial
Universidad Nacional Autónoma de México
Python: de usuario a explorador de datos
Skills you'll gain: Matplotlib, Extract, Transform, Load, Pandas (Python Package), NumPy, Exploratory Data Analysis, Time Series Analysis and Forecasting, Data Visualization Software, Data Science, Package and Software Management, Graphing, Data Analysis, Data Import/Export, Python Programming, Data Manipulation
Beginner · Course · 1 - 3 Months
Status: Free Trial
Databricks
Introduction to Computational Statistics for Data Scientists
Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Classification And Regression Tree (CART), Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Statistical Machine Learning, Probability Distribution, Data Science, Markov Model, Statistics, NumPy, Simulations, Mathematical Software, Statistical Inference
4
Rating, 4 out of 5 stars
109 reviews
Beginner · Specialization · 1 - 3 Months
Status: New
Simplilearn
Data Analytics with Python
Skills you'll gain: Matplotlib, NumPy, Python Programming, Data Presentation, Pandas (Python Package), Data Analysis, Data Visualization Software, Scripting, Analytics, Numerical Analysis, Data Manipulation, Real Time Data, Data Processing, Programming Principles, Scripting Languages, Data Cleansing
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
IBM
AI Workflow: Data Analysis and Hypothesis Testing
Skills you'll gain: Data Visualization, Exploratory Data Analysis, Data Presentation, Statistical Hypothesis Testing, Dashboard, Data Analysis, Data Science, Probability & Statistics, Statistical Analysis, Jupyter, Matplotlib, Data Cleansing, Pandas (Python Package), Statistical Inference, Statistics, Data Manipulation
4.3
Rating, 4.3 out of 5 stars
123 reviews
Advanced · Course · 1 - 4 Weeks
Packt
Practical Quantum Computing with IBM Qiskit for Beginners
Skills you'll gain: IBM Cloud, Cryptography, Algorithms, Python Programming, Linear Algebra, Programming Principles, Computer Science, Theoretical Computer Science, Emerging Technologies, Test Case, Jupyter, Physics, Simulations, Software Installation, Debugging, Development Environment
Beginner · Course · 3 - 6 Months
Status: Free
Coursera Project Network
Visualizing Filters of a CNN using TensorFlow
Skills you'll gain: Tensorflow, Applied Machine Learning, Python Programming, Jupyter, Artificial Neural Networks, Deep Learning, Computer Vision, Scientific Visualization
4.4
Rating, 4.4 out of 5 stars
78 reviews
Intermediate · Guided Project · Less Than 2 Hours
Coursera Project Network
Data Science Coding Challenge: Loan Default Prediction
Skills you'll gain: Applied Machine Learning, Jupyter, Data Processing, Predictive Modeling, Machine Learning, Predictive Analytics, Data Manipulation, Data Science, Python Programming
4.7
Rating, 4.7 out of 5 stars
91 reviews
Intermediate · Guided Project · Less Than 2 Hours
Coursera Project Network
PySpark Foundations: Process, analyze, and summarize data
Skills you'll gain: PySpark, Data Visualization Software, Data Analysis, Exploratory Data Analysis, Data Cleansing, Data Processing, Data Manipulation, Big Data, Jupyter, Pandas (Python Package), People Analytics
Intermediate · Guided Project · Less Than 2 Hours
Status: Free Trial
University of Illinois Urbana-Champaign
Machine Learning for Accounting with Python
Skills you'll gain: Machine Learning Algorithms, Unsupervised Learning, Scikit Learn (Machine Learning Library), Machine Learning, Text Mining, Applied Machine Learning, Time Series Analysis and Forecasting, Data Processing, Supervised Learning, Predictive Modeling, Python Programming, Regression Analysis, Feature Engineering, Jupyter, Pandas (Python Package), Natural Language Processing, Statistical Analysis, Performance Metric
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
43 reviews
Intermediate · Course · 1 - 3 Months