What you'll get
- 68+ Hours
- 14 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- The course offers a thorough introduction to forecasting methods and data modeling with advanced analytical tools.
- Learners have full access to all course materials for one year.
- The program is open to anyone committed to learning Time Series Analysis.
- Participants should have basic knowledge of R and Python, and be familiar with tools such as Minitab and SPSS.
- Learners earn a Certificate of Completion for all 14 courses and gain experience through practical projects.
- Each certificate is verifiable and includes a unique link that can be added to a resume or LinkedIn profile to showcase new skills.
- Training is delivered through self-paced video lessons, allowing participants to learn on their own schedule.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Statistical Tools in Excel | 1h 11m | ✔ | View Curriculum |
| Machine Learning - Statistics Essentials | 8h 23m | ✔ | View Curriculum |
| Statistics for Data Science using Python | 3h 23m | ✔ | View Curriculum |
| Statistics Essentials for Analytics - Beginners | 2h 5m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Forecasting the Sales of the Store Using Time Series Analysis | 2h 13m | ✔ | View Curriculum |
| EViews:05 - Univariate Time Series Modeling | 2h 23m | ✔ | View Curriculum |
| Business Analytics - Forecasting using R | 4h 34m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Predictive Modeling using SPSS | 13h 17m | ✔ | View Curriculum |
| Predictive Modeling using Minitab | 15h 32m | ✔ | View Curriculum |
| SAS - Predictive Modeling with SAS Enterprise Miner | 9h 19m | ✔ | View Curriculum |
| Card Purchase Prediction using R | 2h 28m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Project on Time Series Analysis: Future Climatic Change Scenarios | 3h 5m | ✔ | View Curriculum |
| Project on Time Series Analysis: MNCs Attrition Patterns | 2h 01m | ✔ | View Curriculum |
| Forecasting the Sales of the Store Using Time Series Analysis | 2h 13m | ✔ | View Curriculum |
Description
A time series is a set of data points recorded in chronological order, usually at regular intervals. Analyzing these patterns reveals insights and characteristics that support forecasting. Because each value often depends on previous observations, time series analysis helps select models that improve prediction accuracy and inform decision-making. This method is especially useful for data with sequential dependencies, such as stock market analysis, website performance tracking, and population studies.
In machine learning, time series analysis is essential for building statistical models that generate reliable, interpretable, and predictive insights from chronological data. Common models include autoregressive, integrated, and moving-average types, which can be combined for more advanced forecasting.
Sample Certificate
Requirements
- This Time Series Analysis Course is designed to be accessible to those without prior programming experience.
- It introduces foundational statistical techniques using Microsoft Excel, starting from the basics to ensure every learner can follow comfortably.
- Participants are expected to have a general understanding of quantitative methods and familiarity with standard tools such as MS Office and Paint.
- While advanced programming skills are not required, a basic awareness of R's purpose and common applications will be helpful.
- Similarly, learners do not need in-depth knowledge of machine learning; a basic understanding of fundamental concepts is sufficient.
- A basic introduction to Python is also recommended to better understand the libraries and packages commonly used in time series analysis.
Target Audience
- This course is ideal for MBA and BBA students or graduates, especially those specializing in human resources, marketing, sales, operations, or related fields.
- It also offers valuable learning for HR and finance professionals seeking to strengthen their analytical skills.
- Those with a background in mathematics or statistics will find the concepts accessible and can apply the techniques more quickly.
- Financial, market, and research analysts will also benefit from the course’s introduction to modern tools and methods for data analysis and forecasting.
