Program structure

The Analytics Edge course on edX is structured to provide a deep understanding of how analytics is used to make impactful decisions in real-world scenarios. The course is taught by faculty from MIT and covers a wide range of analytical methods.

Key Modules in the Program Structure:

1. Introduction to Analytics:

   • Overview of how analytics can give organizations a competitive edge.
   • Case studies of how companies have successfully applied analytics.

2. Linear Regression:

   • Learn the fundamentals of regression analysis.
   • Case studies include predicting movie success using box office data.

3. Logistic Regression:

   • Introduction to logistic regression for binary outcomes.
   • Case study: predicting stock prices.

4. Trees and Random Forests:

   • Decision trees and random forests for predictive modeling.
   • Examples include using this method for improving healthcare outcomes.

5. Text Analytics:

   • Application of analytics to unstructured text data.
   • Case study on analyzing newspaper headlines.

6. Optimization:

   • Techniques like linear and integer optimization.
   • Use cases in logistics and operations management.

7. Clustering:

   • Techniques to segment data into meaningful groups.
   • Case study on clustering households based on energy consumption.

8. Visualization:

   • Best practices for presenting data insights visually.
   • Hands-on practice with creating meaningful visualizations.

9. Final Project:

   • Combines the methods learned throughout the course to solve a real-world problem using R programming and analytics.

Tools:

• R Programming Language: The course extensively uses R for data analysis, providing learners with hands-on experience in applying analytics techniques.

For more detailed information, visit the course page on edX.

Fees and Funding

The Analytics Edge course on edX, offered by MIT, is available in two modes:

1. Audit (Free):

   • You can access the course content for free in audit mode. This allows you to view the lectures, participate in discussions, and explore the course materials, but does not provide a certificate or graded assignments.

2. Verified Certificate (Paid):

   • If you want to earn a certificate of completion, you need to pay a fee. The cost typically ranges between $49 and $150 depending on the course and specific offers available at the time of enrollment. This certificate can be shared on LinkedIn or with potential employers to showcase your skills.

Financial Aid:

• edX also offers financial assistance to learners who cannot afford the verified certificate. You can apply for financial aid through the edX platform, which can cover up to 90% of the course fees.
• For more details on financial aid, visit edX Financial Aid.

For the latest details on fees and funding options for this course, visit the course page.

Scholarship Guidance

Currently, the Analytics Edge course on edX does not directly offer specific scholarships. However, edX provides financial aid options for learners who wish to pursue a verified certificate for the course but may not be able to afford the fees.

Financial Aid:

• edX Financial Assistance: Eligible learners can apply for up to 90% off the verified certificate price. To apply, you need to fill out the financial aid form on edX.
• For more information about financial aid on edX, you can visit edX Financial Assistance.

Admission Requirements

The Analytics Edge course on edX does not have formal admission requirements in the same way traditional degree programs do. However, here are some general recommendations for participants to make the most of the course:

1. Basic Knowledge of Statistics and Data Analysis: A background in statistics, probability, and data analysis would be helpful since the course covers advanced analytical techniques.
2. Familiarity with R Programming: The course uses the R programming language extensively for hands-on exercises. While it’s not strictly required to know R beforehand, it would be beneficial to have some experience with it.
3. Mathematical Skills: The course involves mathematical modeling, so familiarity with concepts like regression and optimization is advantageous.

The course is designed to be accessible to learners with an intermediate level of understanding of data science and analytics but does not require formal prerequisites.

For more information, visit the course page on edX.

Application Procedure

• You can audit the course for free or pay for a verified certificate. To apply for the course:
  1. Visit the course page on edX: The Analytics Edge.
  2. Click "Enroll" and choose either the free audit option or the verified certificate option.
  3. Follow the instructions to create an account and register for the course.

No formal application process or admission requirements are necessary beyond registration on edX.