Brief Introduction
Predictive analytics has proved to be a powerful tool to help businesses analyze data and predict future outcomes and trends. Making forecasts using advanced analytics is crucial in today’s data-driven economy. In this course, you’ll learn how to use advanced forecasting models to predict the future. You'll learn this through improving your fluency in Alteryx, a data analytics tool that enables you prepare, blend, and analyze data quickly. This course is ideal for anyone who is interested in purCourse Summary
Learn how to use time-series forecasting techniques to predict future trends and behavior patterns from historical data, and apply them to a variety of business scenarios.Key Learning Points
- Understand the fundamentals of time-series forecasting and its applications in real-world scenarios
- Learn how to analyze and visualize time-series data using Python and popular libraries like Pandas and Matplotlib
- Apply various forecasting models such as ARIMA, Prophet, and LSTM to build accurate time-series models
Related Topics for further study
Learning Outcomes
- Develop a strong foundation in time-series forecasting and its applications
- Analyze and visualize time-series data using Python and popular libraries
- Build and deploy accurate time-series models using various forecasting techniques
Prerequisites or good to have knowledge before taking this course
- Basic understanding of Python programming
- Familiarity with statistical concepts such as mean, median, and variance
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Applied Data Science with Python
- Data Analysis with Python
Related Education Paths
Notable People in This Field
- Jason Brownlee
- Rob J Hyndman
Related Books
Description
The Time Series Forecasting course provides students with the foundational knowledge to build and apply time series forecasting models in a variety of business contexts.Requirements
- No programming experience required. Interested in using data to make better business decisions. Alteryx license (provided to Nanodegree students at no cost, compatible with Windows only) See the Technology Requirements for using Udacity.
Knowledge
- Instructor videosLearn by doing exercisesTaught by industry professionals
Outline
- lesson 1 Time Series Fundamentals Learn what attributes make data a time series. Get introduced to a variety of simple forecasting methods. Learn about seasonality trends and cyclical patterns. lesson 2 ETS Models Learn how to build and use ETS models. Use decomposition plots to visualize time series data. Get practice building an ETS model in Alteryx. lesson 3 ARIMA Models Learn how to build and use ARIMA models. Learn the techniques used in seasonal and non-seasonal ARIMAs. Get practice building an ARIMA model in Alteryx. lesson 4 Analyzing and Visualizing Results Learn how to interpret time series model results. Learn how to use holdout samples to compare forecasting models. Visualize your forecasts through various plots.
Summary of User Reviews
Discover the art of Time Series Forecasting with Udacity's online course. Learners rave about the comprehensive curriculum and real-world examples, resulting in an impressive overall rating.Key Aspect Users Liked About This Course
Learners appreciate the practical and applicable nature of the course material.Pros from User Reviews
- The course content is well-organized and easy to follow.
- Real-world examples and case studies are used to illustrate concepts.
- The course provides a strong foundation for those new to time series forecasting.
- The instructors are knowledgeable and engaging.
- The course includes hands-on exercises to reinforce learning.
Cons from User Reviews
- Some learners may find the course challenging if they lack a strong mathematical background.
- A few users have reported technical issues with the course platform.
- The pace of the course may be too slow for those with previous experience in time series forecasting.
- The course does not cover advanced forecasting techniques.
- The course does not include a formal certification or recognized credential.
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