English | Size: 4.34 GB
Genre: eLearning
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
Learn about Auto regression and Moving average Models
Learn about ARIMA and SARIMA models for forecasting
Use Pandas DataFrames to manipulate Time Series data and make statistical computations
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 time series forecasting and time series analysis models such as AutoRegression, Moving Average, ARIMA, SARIMA etc.
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?
A Verifiable Certificate of Completion is presented to all students who undertake this Time Series Forecasting course on time series analysis and Python time series applications.
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
The practical classes where we create the model for each of these strategies is something which differentiates this course from any other available online course 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
Anyone curious to master Time Series Analysis using Python in short span of time
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