What you'll get
- 47+ Hours
- 18 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Explore forecasting techniques using Excel, R, and Python.
- Access all course materials for 1 year and learn at your own pace.
- Designed for learners aiming to develop practical data forecasting skills.
- Learners should have a basic familiarity with Excel and introductory programming to understand the material fully.
- Complete 18 courses and hands-on projects to earn verifiable certificates.
- Certificates include unique verification links for resumes, portfolios, and LinkedIn profiles.
- Self-paced video lessons allow learners to progress at their own pace.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Statistical Tools in Microsoft 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 |
| Machine Learning Project #3 - Predicting Prices using Regression | 2h 18m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Business Analytics - Forecasting using R | 4h 34m | ✔ | View Curriculum |
| Telecom Customer Churn Prediction | 1h 27m | ✔ | View Curriculum |
| Project on Term Deposit Prediction using Logistic Regression | 1h 38m | ✔ | View Curriculum |
| House Price Prediction using Linear Regression | 3h 2m | ✔ | View Curriculum |
| Employee Attrition Prediction Using Random Forest Technique | 1h 6m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Card Purchase Prediction using R | 2h 28m | ✔ | View Curriculum |
| Project on Term Deposit Prediction using R | 3h 2m | ✔ | View Curriculum |
| Decision Tree Case Study Using R- Bank Loan Default Prediction | 1h 47m | ✔ | View Curriculum |
| Machine Learning Project-Churn Prediction | 1h 22m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Forecasting the Sales of the Store Using Time Series Analysis | 2h 13m | ✔ | View Curriculum |
| Predictive Modeling with Python | 8h 26m | ✔ | View Curriculum |
| Logistic Regression-Predicting the Survival of Passenger in Titanic | 2h 6m | ✔ | View Curriculum |
| Data Science with Python Project-Predict Diabetes on Diagnostic Measures | 1h 02m | ✔ | View Curriculum |
Description
The Forecasting Models Program provides a practical and comprehensive introduction to predictive analytics. Learners gain the skills to anticipate trends and make data-driven decisions using Excel, R, and Python. The course combines theory with hands-on exercises, ensuring participants can confidently apply forecasting techniques to real-world scenarios.
With 1 year of access to the program, participants can study at their own pace. Designed for individuals with foundational Excel and programming knowledge, the course covers essential forecasting methods, algorithm applications, and practical projects. Each module culminates in a verifiable completion certificate, complete with a unique link to highlight new expertise on professional profiles.
This self-paced course is ideal for professionals and students interested in data analytics, business intelligence, and data science, offering a structured path to mastering forecasting skills.
Sample Certificate
Goals
- Equip learners with the ability to apply forecasting methods in practical scenarios.
- Enhance understanding of predictive modeling using Excel, R, and Python.
- Develop confidence in interpreting trends and making data-driven decisions.
Objectives
- Learn core forecasting techniques and their applications in real-world data analysis.
- Complete hands-on projects to reinforce understanding of predictive algorithms.
- Gain verifiable certifications to showcase newly acquired skills.
- Build proficiency in working with Excel, R, and Python for forecasting purposes.
Highlights
- Comprehensive coverage of forecasting methods and predictive analytics.
- Hands-on projects that simulate real-world scenarios.
- Self-paced video lessons are accessible for one year.
- Verifiable certificates for all courses and projects with unique links.
- Suitable for beginners with basic Excel and programming skills.
Requirements
- No prior professional experience required.
- Basic knowledge of Excel is recommended.
- Introductory familiarity with R and Python is beneficial but not mandatory.
- Foundational understanding of algorithms enhances learning, though advanced data science skills are not required.
Target Audience
- Individuals looking to strengthen their data analytics and forecasting skills.
- Data analysts working with large datasets are seeking predictive insights.
- IT professionals, technical managers, and software engineers aiming to enhance forecasting expertise.
- Students and professionals preparing for careers in data science or business intelligence.
FAQ
Q1. Is prior programming experience necessary?
No advanced programming skills are required, though basic knowledge of R, Python, and Excel will help learners follow concepts more easily.
Q2. How long can I access the course materials?
Participants have one full year of access to all lessons, exercises, and projects.
Q3. Are certificates verifiable?
Yes, the course provides each certificate with a unique link that learners can add to their resumes, portfolios, or LinkedIn profiles.
Q4. What kind of projects are included?
Hands-on projects simulate real-world forecasting problems to reinforce the practical application of techniques learned.
Career Benefits
- Acquire in-demand skills in data analytics and predictive modeling.
- Strengthen professional profiles with verifiable certificates.
- Improve ability to make informed, data-driven business decisions.
- Enhance career opportunities in data science, business intelligence, analytics, and related fields.
