How would you measure the success of Great Learning's Data Science Pro Program?

Introduction

Measuring the success of Great Learning's Data Science Pro Program requires a comprehensive approach that considers multiple stakeholders and metrics. To effectively evaluate this product, I'll follow a structured framework covering core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Step 1

Product Context

Great Learning's Data Science Pro Program is an online educational offering designed to equip professionals with advanced data science skills. The program targets working professionals looking to upskill or transition into data science roles.

Key stakeholders include:

1. Students: Seeking career advancement and skill development
2. Employers: Looking for skilled data science professionals
3. Great Learning: Aiming to establish itself as a leading data science education provider
4. Instructors: Delivering high-quality content and mentorship

User flow:

1. Prospective students research and enroll in the program
2. Students complete coursework, projects, and assessments
3. Students receive certifications and career support
4. Graduates apply their skills in the job market

The program aligns with Great Learning's strategy to become a premier online education platform for in-demand tech skills. It competes with other online data science programs from platforms like Coursera, edX, and Udacity.

Product Lifecycle Stage: Growth - The data science education market is expanding rapidly, and Great Learning is likely focused on scaling its program and capturing market share.