Time Series: From Concepts to Smart Decisions

About Course

Unlock the power of time series analysis and learn to make informed decisions with data. This beginner-to-intermediate course simplifies complex concepts and equips you with practical forecasting skills.

✅ Understand Key Concepts – Grasp the fundamentals of trends, seasonality, and stationarity
✅ Master Proven Techniques – Learn essential models like ARIMA and LSTM for accurate predictions
✅ Step-by-Step Guidance – Easy explanations with real-world examples to build your confidence
✅ Hands-on Learning – Apply techniques to real datasets and turn insights into decisions
✅ For Everyone – Designed for students, analysts, and professionals with no prior experience required

Whether you’re forecasting sales, predicting trends, or analyzing data patterns, this course will help you move from concepts to confident decisions.

💻 Start Learning Today and Forecast with Confidence! 🚀

Course Content

Introduction to Time Series
Overview of time series data and its real-world applications.

What is Time Series?

00:00
What_is_Time_Series

Stationarity & Differencing
Understanding stationarity and transforming non-stationary data.

Time Series Forecasting Basics
Introduction to forecasting models and their applications.

Feature Engineering for Time Series
Creating new features from time series data to improve forecasting.

Advanced Forecasting Techniques
Complex models for better prediction accuracy.

Deep Learning for Time Series
Available on Request, use the 'comments' option to request.

Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.

Student Ratings & Reviews

No Review Yet

Time Series: From Concepts to Smart Decisions

About Course

Course Content

Introduction to Time Series
Overview of time series data and its real-world applications.

What is Time Series?

What_is_Time_Series

Stationarity & Differencing
Understanding stationarity and transforming non-stationary data.

Stationarity and testing it with ADF

Stationarity_ADF

Time Series Forecasting Basics
Introduction to forecasting models and their applications.

Moving Averages

Exponential Smoothing

ARIMA Model

ARIMA_Model

Naïve Forecasting

Feature Engineering for Time Series
Creating new features from time series data to improve forecasting.

Lag Features

Lag_Features

Seasonality Encoding

Seasonality

Rolling Window Features

Advanced Forecasting Techniques
Complex models for better prediction accuracy.

SARIMA

STL Decomposition

Facebook Prophet

Evaluating Forecast Accuracy

Deep Learning for Time Series
Available on Request, use the 'comments' option to request.

Introduction to LSTMs

Implementing LSTMs

Transformer Models

Earn a certificate

About Course

Course Content

Introduction to Time Series Overview of time series data and its real-world applications.

What is Time Series?

What_is_Time_Series

Stationarity & Differencing Understanding stationarity and transforming non-stationary data.

Stationarity and testing it with ADF

Stationarity_ADF

Time Series Forecasting Basics Introduction to forecasting models and their applications.

Moving Averages

Exponential Smoothing

ARIMA Model

ARIMA_Model

Naïve Forecasting

Feature Engineering for Time Series Creating new features from time series data to improve forecasting.

Lag Features

Lag_Features

Seasonality Encoding

Seasonality

Rolling Window Features

Advanced Forecasting Techniques Complex models for better prediction accuracy.

SARIMA

STL Decomposition

Facebook Prophet

Evaluating Forecast Accuracy

Deep Learning for Time Series Available on Request, use the 'comments' option to request.

Introduction to LSTMs

Implementing LSTMs

Transformer Models

Earn a certificate

Student Ratings & Reviews

Introduction to Time Series
Overview of time series data and its real-world applications.

Stationarity & Differencing
Understanding stationarity and transforming non-stationary data.

Time Series Forecasting Basics
Introduction to forecasting models and their applications.

Feature Engineering for Time Series
Creating new features from time series data to improve forecasting.

Advanced Forecasting Techniques
Complex models for better prediction accuracy.

Deep Learning for Time Series
Available on Request, use the 'comments' option to request.