Time Series Forecasting from Udacity

What's inside

Syllabus

In this lesson you’ll learn what attributes make data a time series. You’ll also learn the key components used in time series forecasting, such as seasonality, trends, and cyclical patterns.

In this lesson you’ll learn how to build and use ETS models. ETS stands for error, trend, and seasonality, and are the three inputs in ETS models. You’ll learn how to use time series decomposition plots to visualize each of these components. Then you’ll get hands on practice building out an ETS model in Alteryx.

In this lesson you’ll learn how to build and use ARIMA models. ARIMA stands for autoregressive, integrated, moving average, which are the inputs for ARIMA models. You’ll learn how to stationarize data through differencing, a process that prepares data for ARIMA modeling. You’ll learn the different techniques used in seasonal vs. non-seasonal data. Then you’ll get hands on practice building out an ARIMA model in Alteryx.

This lesson will demonstrate how to interpret the various results from time series model. You’ll learn how to use holdout samples to compare models and select the best one for a business problem. You’ll also learn how to visualize your forecasts through various plots.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops foundational knowledge of time series models, a core skill in business analytics

Explores applications in various business contexts, making it valuable for professionals in different industries

Led by instructor Tony Moses, who is considered an expert in time series modeling

Offered through Udacity, a reputable platform known for its tech-related courses

Provides hands-on practice in building time series forecasting models using Alteryx, a popular software in data science

Helps learners interpret and evaluate forecasts, which is crucial for accurate decision-making

Reviews summary

Time series forecasting overview

This course provides foundational knowledge to build and apply time series forecasting models in various business contexts. One reviewer mentioned that including more comprehensive content would be helpful for moving forward to an advanced stage.

Include more comprehensive content

"...Include a more comprehensive content will be encouraged..."

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 Time Series Forecasting with these activities:

Review the basics of statistics

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Strengthen your statistical foundation to better understand the concepts and models in time series forecasting.

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Review basic statistical concepts.
Practice solving statistical problems.

Practice programming in Python

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Enhance your programming skills in Python to proficiently work with time series data and build forecasting models.

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Review Python basics.
Practice solving programming problems in Python.

Review 'Time Series Forecasting: Concepts and Methods'

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Review the book 'Time Series Forecasting: Concepts and Methods' by George E.P. Box and G.M. Jenkins to gain a foundational understanding of time series forecasting concepts and methods.

View Time Series Analysis on Amazon

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Obtain a copy of the book.
Read the first five chapters.
Take notes on key concepts and methods.
Complete the practice exercises at the end of each chapter.
Discuss the concepts with a peer or mentor.

Five other activities

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Complete the Time Series Forecasting Nanodegree

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Enroll in and complete the Time Series Forecasting Nanodegree offered by Udacity.

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Enroll in the Time Series Forecasting Nanodegree.
Complete the required coursework.
Complete the projects.
Earn the Nanodegree.

Solve practice problems on HackerRank

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Practice solving time series forecasting problems on HackerRank to improve your problem-solving skills.

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Create a HackerRank account.
Search for time series forecasting problems.
Solve the problems.
Review your solutions.

Join a study group

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Connect with other learners, exchange knowledge, and reinforce your understanding through discussions and group projects.

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Find a study group or create your own.
Meet regularly.
Discuss the course material.
Work on projects together.
Support each other.

Create a blog post on a time series forecasting topic

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Write a blog post on a specific topic or case study related to time series forecasting to demonstrate your understanding and share your knowledge.

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Choose a topic.
Research the topic.
Write the blog post.
Publish the blog post.
Promote the blog post.

Develop a time series forecasting model for a business

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Apply your time series forecasting skills to develop a data-driven forecasting model that can be used by a business to make informed decisions.

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Identify a business problem that can be solved using time series forecasting.
Collect and preprocess the data.
Build a time series forecasting model.
Evaluate the model's performance.
Deploy the model and use it to make predictions.

Career center

Learners who complete Time Series Forecasting will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts translate raw data into insights that can help businesses make better decisions. Time Series Forecasting can be particularly helpful for Data Analysts who work with time-sensitive data, such as financial data or sales data. This course provides a solid foundation in the principles of time series forecasting, which can help Data Analysts build more accurate and reliable models.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use statistical methods and machine learning to extract insights from data. Time Series Forecasting is a key skill for Data Scientists who work with time-sensitive data. This course provides a comprehensive overview of time series forecasting techniques, which can help Data Scientists develop more sophisticated and effective models.

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Financial Analyst

Financial Analysts use financial data to make investment decisions. Time Series Forecasting can be a valuable tool for Financial Analysts who need to forecast future financial performance. This course provides a practical introduction to time series forecasting techniques, which can help Financial Analysts make more informed investment decisions.

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Market Researcher

Market Researchers collect and analyze data about consumer behavior. Time Series Forecasting can be a useful tool for Market Researchers who need to forecast future demand for products or services. This course provides a foundation in the principles of time series forecasting, which can help Market Researchers develop more accurate and reliable forecasts.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical methods to improve the efficiency of business operations. Time Series Forecasting can be a valuable tool for Operations Research Analysts who need to forecast future demand for products or services. This course provides a comprehensive overview of time series forecasting techniques, which can help Operations Research Analysts develop more effective and efficient operations.

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Product Manager

Product Managers are responsible for the development and marketing of new products. Time Series Forecasting can be a useful tool for Product Managers who need to forecast future demand for new products. This course provides a practical introduction to time series forecasting techniques, which can help Product Managers make more informed decisions about product development and marketing.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical methods to analyze financial data. Time Series Forecasting can be a valuable tool for Quantitative Analysts who need to forecast future financial performance. This course provides a comprehensive overview of time series forecasting techniques, which can help Quantitative Analysts develop more sophisticated and effective models.

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Risk Analyst

Risk Analysts assess and manage financial risks. Time Series Forecasting can be a valuable tool for Risk Analysts who need to forecast future financial risks. This course provides a practical introduction to time series forecasting techniques, which can help Risk Analysts make more informed decisions about risk management.

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Sales Analyst

Sales Analysts track and analyze sales data to identify trends and opportunities. Time Series Forecasting can be a useful tool for Sales Analysts who need to forecast future sales. This course provides a foundation in the principles of time series forecasting, which can help Sales Analysts develop more accurate and reliable forecasts.

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Statistician

Statisticians collect and analyze data to draw conclusions about populations. Time Series Forecasting is a key skill for Statisticians who work with time-sensitive data. This course provides a comprehensive overview of time series forecasting techniques, which can help Statisticians develop more sophisticated and effective models.

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Teacher

Teachers plan and deliver lessons to students in various academic subjects. Time Series Forecasting may be useful for Teachers who teach mathematics or statistics, as it can help them develop a deeper understanding of time-series data and forecasting techniques. Additionally, this course can help Teachers stay up-to-date on the latest developments in time series forecasting, which can benefit their students.

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Economist

Economists study the production, distribution, and consumption of goods and services. Time Series Forecasting can be a useful tool for Economists who need to forecast future economic indicators. This course provides a foundation in the principles of time series forecasting, which can help Economists develop more accurate and reliable forecasts.

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Engineer

Engineers design and build machines, structures, and systems. Time Series Forecasting may be useful for Engineers who work with time-sensitive data, such as data from sensors or manufacturing processes. This course can help Engineers develop a deeper understanding of time-series data and forecasting techniques, which can lead to more efficient and reliable systems.

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Financial Advisor

Financial Advisors provide financial advice to individuals and businesses. Time Series Forecasting may be useful for Financial Advisors who need to forecast future financial performance for their clients. This course can help Financial Advisors develop a deeper understanding of time-series data and forecasting techniques, which can lead to more informed investment decisions.

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Journalist

Journalists write, edit, and disseminate news and information. Time Series Forecasting may be useful for Journalists who need to track and analyze trends over time. This course can help Journalists develop a deeper understanding of time-series data and forecasting techniques, which can lead to more informative and accurate reporting.

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