| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Time Series Forecasting Data Trends Moving Averages Data Analysis |
About the Basics of Time Series Forecasting Course
The Basics of Time Series Forecasting course is a free, beginner-friendly self-paced program designed to introduce learners to how data over time is analyzed and used to make future predictions.
The course explains how patterns such as trends, seasonality, and cycles in time-based data can be used to forecast future values. Learners will explore simple forecasting concepts and understand how time series analysis is applied in business, finance, weather prediction, and demand planning.
Program Highlights
• Free beginner-level time series forecasting course
• Online self-paced learning format
• Simple explanation of time-based data and forecasting concepts
• Covers trends, seasonality, and prediction basics
• Real-world examples from business and finance
• Suitable for students and first-time learners
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to Time Series Data
- What is Time Series Data?
- Examples of Time-Based Data
- Importance of Time in Data Analysis
- Applications of Time Series
Module 2: Understanding Patterns in Time Series
- Trend, Seasonality, and Cycles
- Identifying Patterns in Data
- Stationary vs Non-Stationary Data: Basic Idea
- Visualizing Time Series Data
Module 3: Basic Forecasting Techniques
- Introduction to Forecasting
- Moving Average Concept
- Simple Trend-Based Forecasting
- Examples of Prediction Using Time Data
Module 4: Evaluating Forecasts
- Understanding Forecast Accuracy
- Error and Performance Basics
- Limitations of Forecasting
- Improving Predictions
Module 5: Applications and Next Steps
- Time Series in Business, Finance, and Weather Forecasting
- Demand and Sales Forecasting
- Career and Learning Pathways in Data Science
- Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
Time Series Forecasting Data Trends Moving Averages Data Analysis
Real-World Applications
- Forecasting sales and demand in business
- Predicting stock market trends and financial data
- Analyzing weather and environmental data
- Monitoring trends in healthcare and research
- Preparing for advanced learning in data science and machine learning
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, freshers, and professionals who want to understand how time-based data is used for prediction.
- It is also useful for learners from business, finance, economics, engineering, and data-related fields.
Certification
