By the end of this course, learners will be able to apply forecasting concepts, analyze real-world datasets, detect seasonal trends, construct regression models, and predict future outcomes with Microsoft Excel. They will practice using weighted and exponential averages to capture data trends, explore correlations and regression analysis for deeper insights, and forecast scenarios such as climate projections and workforce attrition.



What you'll learn
Define forecasting concepts and analyze low, medium, and high emission scenarios.
Apply weighted and exponential averages for climate data forecasting.
Perform correlation and regression modeling to predict outcomes in Excel.
Skills you'll gain
- Excel Formulas
- Analytical Skills
- Statistical Modeling
- Time Series Analysis and Forecasting
- Correlation Analysis
- Probability & Statistics
- Estimation
- Graphing
- Forecasting
- Microsoft Excel
- Statistical Methods
- Trend Analysis
- Statistical Analysis
- Data Analysis Software
- Regression Analysis
- Data Manipulation
- Predictive Analytics
Details to know

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October 2025
19 assignments
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There are 5 modules in this course
This module introduces learners to the fundamentals of time series analysis and climate forecasting using Microsoft Excel. It explores low, medium, and high emission scenarios of the 21st century, helping learners build a strong foundation in interpreting climate projections through Excel tools.
What's included
8 videos4 assignments1 plugin
This module focuses on advanced techniques such as weighted averages and exponential averages for forecasting climate data. Learners will gain hands-on experience in handling multi-scenario datasets, applying statistical methods, and interpreting temperature projections with improved accuracy.
What's included
10 videos4 assignments
This module advances into correlation studies and regression models for predictive analytics. Learners will understand how minimum and maximum temperatures are interrelated across scenarios and how to use simple and multiple regression techniques to predict climate outcomes.
What's included
9 videos4 assignments
This module introduces the fundamentals of time series analysis using Microsoft Excel, focusing on employee attrition data. Learners will prepare datasets, apply essential and advanced Excel formulas, and calculate overall and quarterly attrition. The module emphasizes building strong analytical skills and preparing accurate datasets for deeper forecasting tasks.
What's included
7 videos3 assignments
This module advances into trend visualization, seasonality recognition, and forecasting techniques for HR attrition. Learners will use moving averages and trend lines to uncover hidden patterns, analyze recurring seasonal effects, and build Excel-based forecasting models. Additionally, they will evaluate attrition at department and organizational levels to generate actionable HR insights.
What's included
9 videos4 assignments
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