Learning Paths

Route: /learning-paths/

Status: Working content draft for review
Purpose: Content architecture, copy direction, SEO starting points, and page-level placeholders
Source basis: WINNOW learning catalogue and Debojyoti Biswas profile documents supplied for the project
Important: Claims, dates, pricing, batch schedules, testimonials, placement outcomes, institutional clients, and certifications must not be published unless verified and approved.

Learning path pages

• Business Analytics
• Data Science & Machine Learning
• Generative AI
• Managers & Business Professionals

Page purpose

Help visitors who know their goal but do not know which WINNOW course name or sequence applies to them.

SEO starting point

• data analytics learning path
• business analytics learning path
• data science learning path
• machine learning learning path
• Generative AI learning path
• Python learning path for data
• analytics courses for managers
• AI learning path for professionals

Tentative hierarchy

1. Hero
2. How to choose
3. Four learning paths
4. Starting-level guidance
5. Programme relationship map
6. CTA

Draft content

Hero

Start with the capability you need.

You do not need to understand WINNOW’s course names before choosing. Start with your current experience and the kind of work you want to be able to do.

Four paths

Business Analytics

For learners who want to analyse business data, improve spreadsheet capability, build dashboards, and progress toward Python-based analysis.

Likely programmes: Excelerate → SeeIt and/or CodeCraft

Data Science & Machine Learning

For learners who want a proper Python and data foundation before building, evaluating and interpreting machine learning models.

Likely programmes: Groundwork → PredictWorks

Generative AI

For learners who want to understand LLMs and modern GenAI technically rather than stopping at prompt usage.

Likely progression: Python/data foundations as needed → The GenAI Odyssey

Managers & Business Professionals

For managers who need analytical confidence, better decision support, or an informed understanding of AI without training as software engineers.

Likely programmes: Excelerate, SeeIt, CodeCraft, or selected/custom AI modules

Course-fit guidance

Add a simple self-selection matrix using:

• current skill level
• coding comfort
• job role
• desired outcome
• time commitment

[CONFIRM: formal prerequisites and whether assessment/counselling is offered before enrolment]

CTA

Still unsure?
Discuss your background and goal before enrolling.

CTA: Discuss Course Fit