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Abhishek Jha
In this 1.5-hour long project-based course, you will learn how to create a Facebook Prophet Machine learning Model and use it to Forecast the Price of Bitcoin for the future 30 days.
Read more
In this 1.5-hour long project-based course, you will learn how to create a Facebook Prophet Machine learning Model and use it to Forecast the Price of Bitcoin for the future 30 days.
Read more
In this 1.5-hour long project-based course, you will learn how to create a Facebook Prophet Machine learning Model and use it to Forecast the Price of Bitcoin for the future 30 days.
We will begin by importing all the necessary libraries including Facebook Prophet. Then we will import our dataset and analyze it. Then we will start creating visualizations in Plotly express in order to understand the historical performance of Bitcoin. We will then prepare our data for Facebook Prophet and create a Facebook Prophet Machine learning Model. We will then fit our prepared data to the Facebook Prophet Model and command it to make a Forecast for the future 30 days. We will then Visualize the Forecast using the Prophet’s internal visualization tools and then download the Forecast data.
In the final section, we will go to Google Sheets and learn to extract Financial data of Bitcoin using Google Finance. We will then import the Forecast data into Google Sheets and compare it against the actual data and evaluate the performance of the Model.
Please note that although this project deals with Bitcoin and teaches to make Price predictions, it is for educational purposes only and should not be taken for a piece of Financial advice since Cryptocurrencies like Bitcoin are extremely volatile and speculative.
Basic knowledge of Python programming language is recommended but even those with no prior programming experience will be able to complete this project. You will need a Google account to complete this project.
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/jlpc0r/bitcoin
What's inside
Syllabus
Project Overview
By the end of this project, you will be able to create a Facebook Prophet Machine learning Model and use it to predict the future price of Bitcoin. The same skills can also be applied to any other time-series data like Stock Prices or any other Cryptocurrencies. We will begin by importing all the necessary libraries including Facebook Prophet. Then we will import our dataset and analyze it. Then we will start creating visualizations in Plotly express in order to understand the historical performance of Bitcoin. We will then prepare our data for Facebook Prophet and create a Facebook Prophet Machine learning Model. We will then fit our prepared data to the Facebook Prophet model and command it to make a Forecast for the future 30 days. We will then Visualize the Forecast using the Prophet’s internal visualization tools and then download the Forecast data. In the final section, we will go to Google Sheets and learn to extract financial data of Bitcoin using Google Finance. We will then Import the Forecast data into Google Sheets and compare it against the actual data and evaluate the performance of the Model.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Intended for students and professionals with an interest in financial markets and cryptocurrency trading
Prior experience with Python programing is not required, making it accessible to those with limited technical knowledge
Emphasizes hands-on learning with practical application to real-world financial data
May not provide sufficient depth for individuals seeking advanced knowledge of Facebook Prophet or time series modeling
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Save Bitcoin Price Prediction using Facebook Prophet to your list so you can find it easily later:
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Reviews summary
Excellent bitcoin price prediction course
Learners say this excellent course provides engaging assignments with clear explanations led by an exceptional instructor. However, a few students note some room for improvement in the platform's video playback.
Practical and Engaging Assignments
"Nice implementation "
"Enjoy this quick project and unexpectedly learnt about google finance in google sheets."
"The project was very interesting, really a fast, efficient and without much complication way to use python programming, libraries, pandas, facebook prophet, etc."
Knowledgeable and Engaging Instructor
"Excellent instructor"
"Excellent way to explain things. He makes them sound so easy and the guidance is perfect."
"The project and instructor are good!"
Video Playback Needs Improvement
"Lack of a full screen option for the video was really unfortunate especially since it is a basic feature that you see almost everywhere."
"The instructor's video window kept going back to its smaller size every time I pressed the expand button."
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 Bitcoin Price Prediction using Facebook Prophet with these
activities:
Review basic Python programming concepts
Show steps
Refreshing your Python skills will ensure that you have a solid foundation for the course content.
Browse courses on
Python Programming
Show steps
-
Review online tutorials or documentation
-
Practice writing simple Python scripts
Explore additional resources on time series forecasting
Show steps
Supplementing the course material with external sources will broaden your knowledge and enhance your understanding of the concepts.
Browse courses on
Time Series Forecasting
Show steps
-
Identify reputable sources
-
Review articles, watch videos, or attend webinars
-
Take notes and synthesize information
Organize your notes and resources
Show steps
A well-organized system for your notes and materials will make it easier to review and retain information.
Show steps
-
Create a system for organizing notes
-
Categorize and label resources
-
Use digital tools or physical binders
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group or participate in online forums
Show steps
Engaging with peers provides opportunities to clarify concepts, share insights, and learn from different perspectives.
Browse courses on
Collaboration
Show steps
-
Find a study group or forum
-
Prepare for discussions
-
Actively participate and contribute
Practice using Facebook Prophet to make predictions
Show steps
Applying what you've learned through hands-on exercises will solidify your understanding and proficiency with the Facebook Prophet library.
Browse courses on
Facebook Prophet
Show steps
-
Import necessary libraries and dataset
-
Create and fit the Facebook Prophet model
-
Make predictions using the fitted model
Create a presentation or blog post on your findings
Show steps
Sharing your work not only reinforces your own learning but also allows you to teach others and gain valuable feedback.
Browse courses on
Communication
Show steps
-
Gather your data and results
-
Craft a narrative and outline
-
Develop visuals and presentation
-
Present or publish your work
Build a simple time series forecasting application
Show steps
Applying your skills to a practical project will deepen your understanding, enhance your problem-solving abilities, and showcase your proficiency.
Browse courses on
Project-Based Learning
Show steps
-
Define project scope and goals
-
Gather data and analyze requirements
-
Develop and implement the application
-
Test and refine your solution
Review basic Python programming concepts
Show steps
Refreshing your Python skills will ensure that you have a solid foundation for the course content.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Review online tutorials or documentation
- Practice writing simple Python scripts
Explore additional resources on time series forecasting
Show steps
Supplementing the course material with external sources will broaden your knowledge and enhance your understanding of the concepts.
Browse courses on
Time Series Forecasting
Show steps
Show steps
Show steps
- Identify reputable sources
- Review articles, watch videos, or attend webinars
- Take notes and synthesize information
Organize your notes and resources
Show steps
A well-organized system for your notes and materials will make it easier to review and retain information.
Show steps
Show steps
Show steps
- Create a system for organizing notes
- Categorize and label resources
- Use digital tools or physical binders
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group or participate in online forums
Show steps
Engaging with peers provides opportunities to clarify concepts, share insights, and learn from different perspectives.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find a study group or forum
- Prepare for discussions
- Actively participate and contribute
Practice using Facebook Prophet to make predictions
Show steps
Applying what you've learned through hands-on exercises will solidify your understanding and proficiency with the Facebook Prophet library.
Browse courses on
Facebook Prophet
Show steps
Show steps
Show steps
- Import necessary libraries and dataset
- Create and fit the Facebook Prophet model
- Make predictions using the fitted model
Create a presentation or blog post on your findings
Show steps
Sharing your work not only reinforces your own learning but also allows you to teach others and gain valuable feedback.
Browse courses on
Communication
Show steps
Show steps
Show steps
- Gather your data and results
- Craft a narrative and outline
- Develop visuals and presentation
- Present or publish your work
Build a simple time series forecasting application
Show steps
Applying your skills to a practical project will deepen your understanding, enhance your problem-solving abilities, and showcase your proficiency.
Browse courses on
Project-Based Learning
Show steps
Show steps
Show steps
- Define project scope and goals
- Gather data and analyze requirements
- Develop and implement the application
- Test and refine your solution
Career center
Learners who complete Bitcoin Price Prediction using Facebook Prophet will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst may use data to create a model like the Facebook Prophet Model in order to forecast customer demand. This course helps build a foundation in creating such models.
Market Researcher
Market Researcher
A Market Researcher may utilize a Facebook Prophet model and techniques to forecast market trends, consumer behavior and demand for a product or service.
Financial Analyst
Financial Analyst
A Financial Analyst may use a Facebook Prophet Model and its visualizations to forecast financial data such as stock prices and interest rates.
Business Analyst
Business Analyst
A Business Analyst may utilize a Facebook Prophet model to forecast key metrics for a business, anticipate future business outcomes, and identify growth opportunities.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst may create a model like the Facebook Prophet model to forecast financial risks and make investment decisions.
Data Scientist
Data Scientist
A Data Scientist may use a Facebook Prophet model as part of a larger data science project, such as developing a predictive model for customer churn.
Software Engineer
Software Engineer
A Software Engineer may use a Facebook Prophet model as part of a larger software project, such as developing a system to monitor website traffic.
Product Manager
Product Manager
A Product Manager may use a Facebook Prophet model to forecast demand for a new product or feature.
Marketing Manager
Marketing Manager
A Marketing Manager may create a model like the Facebook Prophet model to forecast the impact of a marketing campaign.
Sales Manager
Sales Manager
A Sales Manager may utilize a Facebook Prophet model to forecast sales volume and sales projections.
Operations Manager
Operations Manager
An Operations Manager may use a Facebook Prophet model to forecast demand for goods or services.
Customer Success Manager
Customer Success Manager
A Customer Success Manager may use a Facebook Prophet model to forecast customer lifetime value.
Project Manager
Project Manager
A Project Manager may utilize a Facebook Prophet model to forecast project timelines and milestones.
Administrative Assistant
Administrative Assistant
An Administrative Assistant may use a Facebook Prophet model to forecast resource allocation.
Human Resources Manager
Human Resources Manager
A Human Resources Manager may use a Facebook Prophet model to forecast staffing needs.
For more career information including salaries, visit:
OpenCourser.com/course/jlpc0r/bitcoin
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
Bitcoin Price Prediction using Facebook Prophet.
Save
Provides a comprehensive overview of forecasting methods, including time series analysis, regression analysis, and machine learning. It valuable resource for anyone who wants to learn more about forecasting.
Provides a comprehensive introduction to time series analysis. It covers a wide range of topics, including data collection, exploratory data analysis, model building, and forecasting. It valuable resource for anyone who wants to learn more about time series analysis.
Provides a comprehensive overview of statistical learning methods. It covers a wide range of topics, including linear regression, logistic regression, decision trees, and support vector machines. It valuable resource for anyone who wants to learn more about statistical learning.
Provides a comprehensive overview of machine learning with Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including data preprocessing, feature engineering, model selection, and model evaluation. It valuable resource for anyone who wants to learn more about machine learning with Scikit-Learn, Keras, and TensorFlow.
Provides a comprehensive overview of machine learning with R. It covers a wide range of topics, including data preprocessing, feature engineering, model selection, and model evaluation. It valuable resource for anyone who wants to learn more about machine learning with R.
Save
Provides a comprehensive overview of machine learning for beginners. It covers a wide range of topics, including data preprocessing, feature engineering, model selection, and model evaluation. It valuable resource for anyone who wants to learn more about machine learning for beginners.
Provides a quick overview of machine learning and the R programming language. It valuable resource for anyone who wants to learn the basics of machine learning in R.
Save
Provides a comprehensive overview of how to prepare for a machine learning interview. It valuable resource for anyone who is preparing for a machine learning interview.
Provides a comprehensive overview of machine learning for hackers. It valuable resource for anyone who wants to learn more about machine learning for hacking.
Provides a comprehensive overview of machine learning with Python for beginners. It valuable resource for anyone who wants to learn more about machine learning with Python for beginners.
Provides a comprehensive overview of machine learning with R for beginners. It valuable resource for anyone who wants to learn more about machine learning with R for beginners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jlpc0r/bitcoin
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Effort
1.5
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Abhishek Jha
Language
English
Good to know
Intended for students and professionals with an interest in financial markets and cryptocurrency trading
Prior experience with Python programing is not required, making it accessible to those with limited technical knowledge
Emphasizes hands-on learning with practical application to real-world financial data
May not provide sufficient depth for individuals seeking advanced knowledge of Facebook Prophet or time series modeling
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