Time Series Analysis and Forecasting using Python
Learn about time series analysis & forecasting models in Python |Time Data Visualization|AR|MA|ARIMA|Regression| ANN.
What you’ll learn
- Get a solid understanding of Time Series Analysis and Forecasting
- Understand the business scenarios where Time Series Analysis is applicable
- Building 5 different Time Series Forecasting Models in Python
Requirements
- Students will need to install Python and Anaconda software
Description
You’re looking for a complete course on Time Series Forecasting to drive business decisions involving production schedules, inventory management, manpower planning, and many other parts of the business., right?
You’ve found the right Time Series Forecasting and Time Series Analysis course using Python Time Series techniques. This course teaches you everything you need to know about different time series forecasting and time series analysis models and how to implement these models in Python time series.
After completing this course you will be able to:
- Implement multivariate time series forecasting models based on Linear regression and Neural Networks.
- Confidently practice, discuss and understand different time series forecasting, time series analysis models and Python time series techniques used by organizations
How will this course help you?
If you are a business manager or an executive, or a student who wants to learn and apply forecasting models in real world problems of business, this course will give you a solid base by teaching you the most popular forecasting models and how to implement it. You will also learn time series forecasting models, time series analysis and Python time series techniques.
Why should you choose this course?
We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:
- Theoretical concepts and use cases of different forecasting models, time series forecasting and time series analysis
- Step-by-step instructions on implement time series forecasting models in Python
- Downloadable Code files containing data and solutions used in each lecture on time series forecasting, time series analysis and Python time series techniques
- Class notes and assignments to revise and practice the concepts on time series forecasting, time series analysis and Python time series techniques
Who this course is for:
- People pursuing a career in data science
- Working Professionals beginning their Machine Learning journey
- Statisticians needing more practical experience