Practical Time Series Analysis By The State University (Free Online Course) : Time series analysis is a powerful statistical method used to analyze data points collected or recorded at specific time intervals. It is widely applied in fields such as finance, economics, weather forecasting, and supply chain management to identify trends, patterns, and seasonal variations. Practical time series analysis goes beyond theoretical concepts, focusing on real-world applications that help businesses make data-driven predictions and decisions. By leveraging techniques such as moving averages, ARIMA models, and exponential smoothing, analysts can gain insights into future behavior based on historical data. This introduction will explore the fundamentals of time series analysis and how it can be practically applied across industries for forecasting and optimization.
What You Will Learn?
| Module 1 – WEEK 1: Basic Statistics |
| Module 2 – Week 2: Visualizing Time Series, and Beginning to Model Time Series |
| Module 3 – Week 3: Stationarity, MA(q) and AR(p) processes |
| Module 4 – Week 4: AR(p) processes, Yule-Walker equations, PACF |
| Module 5 – Week 5: Akaike Information Criterion (AIC), Mixed Models, Integrated Models |
| Module 6 – Week 6: Seasonality, SARIMA, Forecasting |
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Skills You Will Gain
- Time Series Forecasting
- Time Series
- Time Series Models
Course Enrollment Process
Here are steps on how to enroll in the “Introduction to Cybersecurity Fundamentals” course on Coursera:
- Visit the Course Page: Go to the course page on Coursera.
- Click on “Enroll for Free”: Located on the far-left side under the course title.
- Choose Enrollment Type: Opt for either the “Free Audit” or a paid version for certification.
- Sign In or Register: Log in or create a Coursera account.
- Start Learning: Once enrolled, access the course materials.
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