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Create and Share Analytics with Jupyter Notebooks

Janani Ravi
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This course is no longer available. Find something similar by browsing:
Jupyter Notebooks Python Data Analysis Markdown Magic Functions JupyterLab Distributed Computing

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Read about what's good
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and possible dealbreakers
Covers core concepts of Python, including data analysis and visualization, which is a highly relevant skill in many industries
Introduces Jupyter notebooks, an important tool in Python for interactive data analysis and visualization
Provides guidance on using advanced features of Jupyter notebooks, enabling learners to enhance the readability and functionality of their code
Covers JupyterLab, the next-generation platform for Jupyter notebooks, offering a more comprehensive development environment
Includes practical hands-on experience with cloud-hosted Jupyter notebooks on major cloud platforms, preparing learners for real-world applications
Taught by Janani Ravi, an experienced instructor in the field of data analysis and Python, enhancing the credibility of the course

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Career center

Learners who complete Create and Share Analytics with Jupyter Notebooks will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use computational and statistical techniques to understand data and create data-driven solutions to complex problems. The course, Create and Share Analytics with Jupyter Notebooks, will help you build a foundation in Python programming and Jupyter notebooks. These skills are essential for Data Scientists, who need to be able to analyze and interpret large datasets. The course will also introduce you to cloud-hosted Jupyter notebooks, which are becoming increasingly popular for distributed and collaborative use-cases. The fit score of 90 indicates that this course is an excellent choice if you want to pursue a career as a Data Scientist.
See salaries and explore the career path for Data Scientist
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They use this information to make recommendations and decisions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 85 indicates that this course is a valuable resource for aspiring Data Analysts.
See salaries and explore the career path for Data Analyst
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. They use these models to predict outcomes and make decisions. The course, Create and Share Analytics with Jupyter Notebooks, will help you build a foundation in Python programming and Jupyter notebooks. These skills are essential for Machine Learning Engineers, who need to be able to develop and deploy machine learning models. The course will also introduce you to cloud-hosted Jupyter notebooks, which are becoming increasingly popular for distributed and collaborative use-cases. The fit score of 80 indicates that this course is a good option for aspiring Machine Learning Engineers.
See salaries and explore the career path for Machine Learning Engineer
Statistician
Statisticians collect, analyze, and interpret data. They use this information to make predictions and draw conclusions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 75 indicates that this course may be useful for aspiring Statisticians.
See salaries and explore the career path for Statistician
Business Analyst
Business Analysts use data to understand business needs and make recommendations. They work with stakeholders to identify and solve problems. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 70 indicates that this course may be helpful for aspiring Business Analysts.
See salaries and explore the career path for Business Analyst
Financial Analyst
Financial Analysts use data to evaluate investments and make recommendations. They work with clients to develop financial plans and strategies. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 65 indicates that this course may be helpful for aspiring Financial Analysts.
See salaries and explore the career path for Financial Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. They work with organizations to develop strategies to mitigate risks. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 60 indicates that this course may be helpful for aspiring Risk Analysts.
See salaries and explore the career path for Risk Analyst
Data Engineer
Data Engineers design and build systems to store and process data. They work with data scientists and other stakeholders to ensure that data is available and accessible. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data, and you will also gain experience with cloud-hosted Jupyter notebooks. The fit score of 55 indicates that this course may be helpful for aspiring Data Engineers.
See salaries and explore the career path for Data Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with users to understand their needs and develop solutions that meet those needs. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to develop software applications. The fit score of 50 indicates that this course may be helpful for aspiring Software Engineers.
See salaries and explore the career path for Software Engineer
Analyst Programmer
Analyst Programmers use programming skills to analyze data and solve problems. They work with data scientists and other stakeholders to develop and implement solutions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and develop solutions. The fit score of 45 indicates that this course may be helpful for aspiring Analyst Programmers.
See salaries and explore the career path for Analyst Programmer
Data Visualization Specialist
Data Visualization Specialists use data visualization tools to create visual representations of data. They work with stakeholders to communicate insights and make data more accessible. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to create data visualizations. The fit score of 40 indicates that this course may be helpful for aspiring Data Visualization Specialists.
See salaries and explore the career path for Data Visualization Specialist
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They work with portfolio managers and other stakeholders to make investment decisions. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze financial data. The fit score of 35 indicates that this course may be helpful for aspiring Quantitative Analysts.
See salaries and explore the career path for Quantitative Analyst
User Experience Researcher
User Experience Researchers use research methods to understand user needs and improve user experiences. They work with designers and other stakeholders to create products and services that are easy to use and enjoyable. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and make recommendations.
See salaries and explore the career path for User Experience Researcher
Market Researcher
Market Researchers use research methods to understand consumer behavior and market trends. They work with marketers and other stakeholders to develop and implement marketing strategies. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and make recommendations.
See salaries and explore the career path for Market Researcher
Information Security Analyst
Information Security Analysts use their knowledge of computers and networks to protect organizations from cyberattacks. They work with security teams and other stakeholders to develop and implement security measures. The course, Create and Share Analytics with Jupyter Notebooks, will help you develop the skills you need to succeed in this role. You will learn how to use Python programming and Jupyter notebooks to analyze data and identify security threats.
See salaries and explore the career path for Information Security Analyst

Reading list

We've selected 50 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 Create and Share Analytics with Jupyter Notebooks.
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Fluent Python
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Serves as the ultimate masterclass in idiomatic Python, guiding developers through data models, generators, metaprogramming, and concurrent concurrency patterns.
Fluent Python: Clear, Concise, and Effective...
Paperback
$$
Fluent Python: Clear, Concise, and Effective...
Paperback
$$$
(日本語) Fluent Python ―Pythonicな思考とコーディング手法
Tankobon Softcover
$$$
Fluent Python
Kindle Edition
$$
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Effective Python
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Highlights 125 actionable best practices and subtle design nuances, helping engineers write clean, robust, and performant code across modern Python 3 development workflows.
Effective Python: 90 Specific Ways to Write Better...
Paperback
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Effective Python: 59 Specific Ways to Write Better...
Paperback
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Effective Python: 90 Specific Ways to Write Better...
Kindle Edition
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Effective Python: 59 Specific Ways to Write Better...
Kindle Edition
$$
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Python for Data Analysis
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The third edition of the essential guide to data wrangling with pandas, NumPy, and Jupyter in Python. Updated for newer versions of the libraries, this book remains a core resource for anyone performing data analysis in Python. It widely used textbook and reference for its clear explanations and practical examples.
Python for Data Analysis: Data Wrangling with...
Paperback
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Python for Data Analysis
Kindle Edition
$$
Python for Data Analysis: Data Wrangling with...
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Code Complete
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A classic in the field of software development. It covers best practices for writing clean and efficient code, which is essential for collaborative development.
Code Complete: A Practical Handbook of Software...
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$$
Code Complete
Paperback
$$
Code Complete (Developer Best Practices)
Kindle Edition
$$
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Clean Code
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Provides a set of principles and best practices for writing clean and maintainable code, which is essential for successful collaborative development.
Clean Code: A Handbook of Agile Software...
Paperback
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Clean Coder, The: A Code of Conduct for...
Kindle Edition
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The Robert C. Martin Clean Code Collection...
Kindle Edition
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(Español) Código limpio / Clean code: Manual de estilo para...
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(Deutsch) Clean Code - Refactoring, Patterns, Testen und...
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(Français) Clean Code: Coffret Deluxe 4 volumes
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(Italiano) ROBERT C. MARTIN, CLEAN CODE -
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(中文) code clean of the Road(Chinese Edition)
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Python Cookbook
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Gathers hundreds of battle-tested recipes covering network programming, memory management, data structures, and functional decorators for veteran application developers.
Python Cookbook: Recipes for Mastering Python 3
Kindle Edition
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Python Cookbook (第3版) (中文版)
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The Markdown Guide
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Provides a comprehensive reference to Markdown syntax, suitable for both beginners and experienced users. It covers the basics and more advanced formatting techniques. It highly recommended reference for anyone working with Markdown regularly.
The Markdown Guide
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Architecture Patterns with Python
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Introduces clean architecture, domain-driven design, and event-driven microservices to Python developers, demonstrating repository patterns and dependency inversion.
Architecture Patterns with Python: Enabling Test...
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Architecture Patterns with Python: Enabling Test...
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Automate the Boring Stuff with Python, 2nd Edition
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Demystifies programming for practical utility, guiding beginners through real-world automation projects including web scraping, spreadsheet generation, and file audits.
Automate the Boring Stuff with Python, 2nd Edition:...
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Automate the Boring Stuff with Python, 2nd Edition:...
Kindle Edition
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Refactoring
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Another book by an industry leader. It provides techniques for improving the design of existing code, which can be helpful in collaborative development environments.
Refactoring: Improving the Design of Existing Code...
Hardcover
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Refactoring: Improving the Design of Existing Code
Hardcover
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Refactoring: Ruby Edition: Ruby Edition (Addison...
Paperback
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Refactoring Databases: Evolutionary Database Design...
Kindle Edition
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(Deutsch) Refactoring: Wie Sie das Design bestehender...
Kindle Edition
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Refactoring : Ruby (Korea Edition)
Unknown Binding
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(Français) Refactoring: Comment améliorer le code existant...
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(Italiano) L'arte del Refactoring: Guida alle tecniche per...
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Robust Python
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Focuses on static typing, structural subtyping, and defensive design techniques, demonstrating how modern type annotations prevent regressions in enterprise codebases.
Robust Python: Write Clean and Maintainable Code
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Robust Python: Write Clean and Maintainable Code
Kindle Edition
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The Mythical Man-Month
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A classic in the field of software engineering. It discusses the challenges of software development, including the challenges of collaborative development.
Mythical Man-Month, The: Essays on Software...
Kindle Edition
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The Pragmatic Programmer
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Offers practical advice on software development, including tips on how to work effectively in a team.
The Pragmatic Programmer: Your Journey To Mastery,...
Hardcover
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Pragmatic Programmer, The: From Journeyman to Master
Kindle Edition
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(Italiano) Pragmatic Programmer - Edizione del 20°...
Kindle Edition
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(Italiano) Il Pragmatic Programmer: Guida per manovali del...
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(中文) The Pragmatic Programmer: access to the highest...
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Pragmatic programmer (Korean Edition)
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Agile Estimating and Planning
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Great companion to Agile Development with Scrum. Cohn helped develop Scrum and provides guidance on how to plan and estimate collaborative development efforts.
Agile Estimating and Planning
Paperback
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(Pусский) Agile: Оценка и планирование проектов (Agile...
Kindle Edition
$
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Version Control with Git
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Not specific to collaborative development, this book valuable resource on a tool essential for collaborative development.
Version Control with Git: Powerful tools and...
Paperback
$$
Cover image
Data Science for Business
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Provides a foundational understanding of the fundamental principles of data science and the data-analytic thinking necessary for extracting value from data in a business context. It is highly relevant for undergraduate business analytics programs and working professionals. It serves as a useful reference for understanding the business applications of data analysis and is commonly used as a textbook.
Data Science for Business: What You Need to Know...
Paperback
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Data Science for Business: What You Need to Know...
Kindle Edition
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Python Testing with Pytest
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Unpacks professional testing methodologies using pytest, explaining fixture management, parameterized tests, coverage tracking, and automated CI test execution.
Python Testing with pytest: Simple, Rapid,...
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Python Testing with pytest: Simple, Rapid,...
Paperback
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Python Testing with pytest
Kindle Edition
$$
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Serious Python
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Investigates advanced software craft, detailing packaging distribution, bytecode internals, scaling architectures, and maintainability across large distributed systems.
Serious Python: Black-Belt Advice on Deployment,...
Paperback
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Serious Python: Black-Belt Advice on Deployment,...
Kindle Edition
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Storytelling with Data
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Focuses on the crucial skill of communicating insights from data effectively through compelling visualizations. is highly relevant for all levels, emphasizing the importance of clear and impactful data presentation. It is valuable additional reading that complements technical data analysis skills.
Storytelling with Data: A Data Visualization Guide...
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Daphne Draws Data: A Storytelling with Data...
Hardcover
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Storytelling with Data: Let's Practice!
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storytelling with data podcast
Podcast
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(Italiano) Data storytelling: generare valore dalla...
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Practical Statistics for Data Scientists
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Bridges the gap between statistical theory and its practical application in data science using R and Python. It focuses on the statistical concepts most relevant to data scientists and provides code examples. It's a useful reference and learning resource for those applying statistics in their work.
Practical Statistics for Data Scientists: 50+...
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Practical Statistics for Data Scientists: 50...
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Practical Statistics for Data Scientists: 50+...
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Practical Statistics for Data Scientists: 50+...
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3D Data Science with Python
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Bridges volumetric point cloud analysis with Python, teaching LiDAR processing, spatial meshing, and 3D machine vision using modern scientific computing toolchains.
3D Data Science with Python
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3D Data Science with Python
Kindle Edition
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Data Feminism
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Offers a new way of thinking about data science and ethics informed by intersectional feminist thought. It challenges existing power structures within data and explores how data can be used to work towards justice. It's highly relevant for contemporary discussions around fairness and bias in data analysis.
Data Feminism (Strong Ideas)
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Data Feminism (Strong Ideas)
Kindle Edition
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Introduction to Python for Absolute Beginners
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Presents a welcoming, foundational ramp into computational logic and programming, establishing syntax literacy, object modeling, and error handling for total beginners.
Introduction to Python for Absolute Beginners
Paperback
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Introduction to Python for Absolute Beginners
Kindle Edition
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Algorithms for Data Science
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A practical handbook focusing on data science applications of Jupyter Notebooks, including data cleaning, exploratory data analysis, machine learning, and data visualization. Assumes some prior programming knowledge.
Algorithms for Data Science
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Algorithms for Data Science
Kindle Edition
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Deep Learning with TensorFlow
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A specialized guide to using Jupyter Notebooks for machine learning tasks, covering topics such as data preprocessing, model training, and evaluation.
Deep Learning with TensorFlow - Second Edition:...
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Deep Learning with TensorFlow: Explore neural...
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Predictive Analytics with TensorFlow: Implement...
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Deep Learning with TensorFlow: Explore neural...
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Deep Learning with TensorFlow: Explore neural...
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Python Workout
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Provides 50 focused exercise routines and guided breakdowns designed to build instinctive muscle memory across collections, functional pipelines, algorithms, and file I/O.
Python Workout: 50 Essential Exercises
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Python Workout: 50 ten-minute exercises
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Fundamentals of Data Visualization
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Provides a guide to creating effective and aesthetically pleasing data visualizations. It delves into the principles behind good visualization design, helping readers make informed choices about how to represent their data. It valuable reference for anyone creating visualizations, from students to professionals.
Fundamentals of Data Visualization: A Primer on...
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Naked Statistics: Stripping the Dread from the Data
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Is an excellent starting point for anyone new to data analysis or statistics. It demystifies core statistical concepts without relying heavily on mathematical formulas, making it highly accessible for high school and undergraduate students. It provides a strong foundation in the intuition behind statistical analysis and helps readers understand how data can be used and misused. This is valuable background reading that builds prerequisite knowledge.
Naked Statistics: Stripping the Dread from the Data
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Naked Statistics: Stripping the Dread from the Data
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Test Driven Development
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Covers one aspect of the collaborative development process, testing. Written by an industry leader in the Test-Driven Development field.
Test Driven Development: By Example
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Test-driven development (Korean Edition)
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Machine Learning Engineering with Python
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Tackles the full lifecycle of shipping models into production, covering feature store development, container packaging, drift detection, and continuous retraining.
Machine Learning Engineering with Python: Manage...
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Machine Learning Engineering with Python: Manage...
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Think Stats
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Teaches probability and statistics using a computational approach with Python. It's ideal for students and professionals with programming experience who want to understand statistical concepts by doing. It helps solidify understanding through hands-on application.
Think Stats
Paperback
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Think Stats
Kindle Edition
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Python Machine Learning
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Explores fundamental statistical learning and neural network implementations, walking through algorithmic mathematics alongside clear scikit-learn and PyTorch code examples.
Machine Learning with PyTorch and Scikit-Learn:...
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Python Machine Learning: Machine Learning and Deep...
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Python Machine Learning, 1st Edition
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Python Machine Learning - Second Edition: Machine...
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(Español) Machine Learning con PyTorch y Scikit-Learn:...
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Python: Deeper Insights into Machine Learning:...
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(Español) Python Machine Learning
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Machine Learning with PyTorch and Scikit-Learn:...
Kindle Edition
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Python Machine Learning: Machine Learning and Deep...
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Python Machine Learning - Second Edition: Machine...
Kindle Edition
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(Español) Python Machine Learning (Spanish Edition)
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Python Machine Learning: Unlock deeper insights...
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Python: Step into the World of Machine Learning
Kindle Edition with Audio/Video
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(Italiano) Machine Learning con Python - Nuova edizione:...
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Python: Deeper Insights into Machine Learning:...
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(Italiano) Machine Learning con Python: costruire algoritmi...
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(Deutsch) Machine Learning mit Python und Keras, TensorFlow 2...
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Head First Python
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Employs an engaging visual pedagogical framework to teach web application development, database integration, and object-oriented fundamentals without dry jargon.
Head First Python: A Learner's Guide to the...
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Head First Programming: A learner's guide to...
Kindle Edition
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Head First Python: A Brain-Friendly Guide
Paperback
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Head First Python: A Brain-Friendly Guide
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(中文) Head First Python（第二版）
Paperback
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Using Markdown
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This guide is an excellent starting point for beginners, covering the fundamental syntax of Markdown with clear examples. It's a concise introduction that helps solidify basic understanding before moving on to more complex topics or tools.
Using Markdown: A Short Instruction Guide
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Using Markdown: A Short Instruction Guide
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Think Python
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Cultivates computational thinking through concise explanations of imperative algorithms, recursion, abstract data types, and systematic debugging principles for beginners.
Think Python: How to Think Like a Computer Scientist
Paperback
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Think Python: How to Think Like a Computer Scientist
Paperback
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Think Bayes: Bayesian Statistics in Python
Kindle Edition
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Learning With Python: How To Think Like A Computer...
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Think DSP: Digital Signal Processing in Python
Kindle Edition
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Python for Software Design: How to Think Like a...
Kindle Edition
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(العربية) Think python: Arabic version (Arabic Edition)
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(Deutsch) Think Python: Systematisch programmieren lernen mit...
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Think Python by Allen B. Downey (2012-08-20)
Paperback
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Python Data Science Handbook
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Comprehensive guide to data science using Python, and it includes a section on using Jupyter Notebooks for data analysis and visualization.
Python Data Science Handbook: Essential Tools for...
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Python Data Science Handbook: Essential Tools for...
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Python pour la Data Science - Les meilleures outils...
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Python Data Science Handbook
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Hands-On Data Analysis with Scala
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A practical guide to using Jupyter Notebooks for data analysis and visualization, covering topics such as data cleaning, data manipulation, and interactive visualizations.
Hands-On Data Analysis with Scala
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Hands-On Data Analysis with Scala: Perform data...
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How to Lie with Statistics
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A timeless classic that remains highly relevant today. exposes common ways statistics can be manipulated or misinterpreted, fostering a critical eye essential for anyone working with data. It's valuable for all levels, from high school to professional, as it highlights the importance of data integrity and ethical considerations. This serves as crucial additional reading to develop data literacy.
How to Lie with Statistics
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Markdown Dreams
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Focuses on using Markdown in conjunction with Git for content creation and version control. It's particularly relevant given the course titles mentioning version control and Git workflows. It provides practical guidance for managing content using these tools.
Markdown Dreams: How to do things with Markdown and...
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Pandas 1.x Cookbook
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A guide to using Jupyter Notebooks for Python developers, covering topics such as data analysis, machine learning, and web development.
Pandas 1.x Cookbook - Second Edition: Practical...
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Pandas 1.x Cookbook: Practical recipes for...
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Working Effectively with Legacy Code
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While not specific to collaborative development, this book provides guidance on how to work with legacy code, which is often a challenge in collaborative development environments.
Working Effectively with Legacy Code
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Working Effectively with Legacy Code (Robert C....
Kindle Edition
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SQL Queries 2012 Joes 2 Pros®
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SQL fundamental skill for data analysis, and this book delves into advanced techniques for working with data in databases. It's essential for anyone who needs to retrieve and manipulate data stored in relational databases. It serves as a valuable reference for more complex data extraction and transformation tasks.
SQL Queries 2012 Joes 2 Pros (R) Volume 3: Advanced...
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The Signal and the Noise
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Explores the world of prediction and forecasting across various fields, demonstrating how data analysis and statistical modeling are used in practice. It's particularly engaging for undergraduate and graduate students interested in the application of data analysis in real-world scenarios. It adds breadth by showcasing diverse applications and the challenges involved in making accurate predictions.
The Signal and the Noise: Why So Many Predictions...
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Black Hat Python, 2nd Edition
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Connects systems engineering with offensive network reconnaissance, detailing raw packet manipulation, Windows process injection, and reverse shell programming.
Black Hat Python, 2nd Edition: Python Programming...
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Black Hat Python, 2nd Edition: Python Programming...
Kindle Edition
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The Art of Data Science
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Provides a high-level overview of the data science process, from asking questions to interpreting results. It focuses on the principles and concepts rather than specific tools, making it suitable for a broad audience. It helps in gaining a broad understanding of the data analysis workflow.
The Art of Data Science
Paperback
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Python for Bioinformatics
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Examines computational molecular biology through a programmer lens, illustrating genomic sequence alignment, phylogenetic modeling, and biochemical laboratory automation.
Python for Bioinformatics (Chapman & Hall/CRC...
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Python for Bioinformatics (Chapman & Hall/CRC...
Kindle Edition
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Distributed Algorithms
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For those interested in the design and analysis of distributed algorithms, this book foundational text. It covers topics such as consensus, fault tolerance, and distributed shared memory, providing a solid theoretical understanding of distributed computing.
Distributed Algorithms (The Morgan Kaufmann Series...
Hardcover
$$$$
Link Reversal Algorithms (Synthesis Lectures on...
Paperback
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Distributed Algorithms (The Morgan Kaufmann Series...
Kindle Edition
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The Essence of Software Engineering
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An oldie but a goodie: this book helped define the field of collaborative software engineering and discusses topics not often considered when thinking about collaborative development.
Essence of Software Engineering, The: Applying the...
Kindle Edition
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R Markdown
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While focused on R Markdown, this book provides a comprehensive reference to the R Markdown ecosystem, which builds upon Markdown. It's particularly relevant for those in data science and reproducible research. It dives into advanced applications and can be a valuable resource for graduate students and professionals in these fields.
R Markdown: The Definitive Guide (Chapman &...
Paperback
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R Markdown: The Definitive Guide (Chapman &...
Kindle Edition
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Big Data
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Explores the concept of big data and its impact on various aspects of society. It discusses the potential and implications of analyzing massive datasets, providing a broader context for the field of data analysis. It's valuable for understanding the landscape in which data analysis operates.
Big Data: A Revolution That Will Transform How We...
Kindle Edition
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Learning With Big Data (Kindle Single): The Future...
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Course image
Time
2 hours
Via
Pluralsight
Instructor
Janani Ravi
This course belongs to a collection called Python for Data Analysts. It's comprised of 11 courses:
  1. Building Your First Python Analytics Solution
  2. Create and Share Analytics with Jupyter Notebooks (viewing)
  3. Python for Data Analysts
  4. Programming Python Using an IDE
  5. Leveraging Online Resources for Python Analytics
  6. Importing Data: Python Data Playbook
  7. Cleaning Data: Python Data Playbook
  8. Pygal 2: Python Data Playbook
  9. Understanding Databases with SQLAlchemy 1: Python Data Playbook
  10. Web Scraping: Python Data Playbook
  11. Data Wrangling with Python 3
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Covers core concepts of Python, including data analysis and visualization, which is a highly relevant skill in many industries
Introduces Jupyter notebooks, an important tool in Python for interactive data analysis and visualization
Provides guidance on using advanced features of Jupyter notebooks, enabling learners to enhance the readability and functionality of their code
Covers JupyterLab, the next-generation platform for Jupyter notebooks, offering a more comprehensive development environment
Includes practical hands-on experience with cloud-hosted Jupyter notebooks on major cloud platforms, preparing learners for real-world applications
Taught by Janani Ravi, an experienced instructor in the field of data analysis and Python, enhancing the credibility of the course
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