2025 Was a Defining Year for PrepVector — Here’s Our Journey in Review
2025 was the year everything clicked.
What started as a focused learning initiative evolved into a full-fledged ecosystem for data and ML practitioners. But more importantly, it was the year we proved our core thesis: Learning compounds only when it is grounded in the real world.
👋 Hey! This is Manisha Arora from PrepVector. Welcome to the Tech Growth Series, a newsletter that aims to bridge the gap between academic knowledge and practical aspects of data science. My goal is to simplify complicated data concepts, share my perspectives on the latest trends, and share my learnings from building and leading data teams.
We didn’t just grow our numbers; we grew our depth. From NYC coffee shops to advanced A/B testing cohorts, 2025 was about moving beyond “content consumption” toward career-defining execution.
Here is the strategic review of our journey and a preview of where we are going.
1. Moving from “Learning” to “Compounding”
This year marked a big step forward in how we teach and how our learners grow. We moved past the idea of “taking a course”.
Across our programs — Product Data Science, A/B Testing 101, Advanced A/B Testing and AI/ML Project Course, we watched learners:
Transition into data roles
Level up into senior and product-facing positions
Build confidence in experimentation, systems thinking, and decision-making
Every cohort reinforced how structured, hands-on learning compounds when people are solving real problems.
From framing business questions to shipping end-to-end projects, learners didn’t just consume content, they practiced the work they’re expected to do on the job. It reminds us why PrepVector exists in the first place: to make high-quality, practical education accessible and genuinely career-changing.
The Result: A “Wall of Love” filled with promotion stories and successful career pivots.
Expanding our curriculum across analytics, experimentation, and ML systems wasn’t just about adding more topics. It was about building depth, continuity, and progression in how people learn.
2. Radical Clarity through Creating and Publishing
2025 was our most ambitious year for content yet. We published 70+ deep-dive articles, introduced new frameworks, and shared hands-on guides with one goal: Clarity over buzzwords.
Our substack newsletter now spans articles about experimentation design, causal inference, ML systems and AI agents.
We collaborated with practitioners and industry experts like to publish long-form technical blogs, playbooks and structured guides designed for deeper learning. It pushed our thinking and helped raise the bar. Those conversations shaped what we wrote and what we will build next.
👉 If you missed it, we’ve curated all our most-read and most-loved pieces in a separate blog:
“Top Reads of 2025: The Best of PrepVector” — a great place to bookmark for deep work sessions.
3. A Global Ecosystem of Partners
One of the most rewarding parts of 2025 was the partnerships we built. Partnerships with industry leaders further provided diverse perspectives. It helped us build and pressure-test our curriculum against the highest industry standards.
We partnered with Stratascratch, Maven, Times of India, Optimized AI, Data Neighbor Podcast, Grace Hopper, Women in Tech, and MIT Code that helped us reach learners across geographies and career stages.
We truly appreciate each of our partners who trusted in us and have contributed to our growth this year.
4. 🙏 Showing Up for the Community, Online and Offline
2025 wasn’t only about digital learning. It was deeply human.
Every article, workshop, cohort, and experiment was shaped by people who brought sharp thinking, real-world problems, and honest feedback into the PrepVector ecosystem. A heartfelt thank you to all our contributors, collaborators, mentors, speakers, reviewers, and community members who showed up — consistently and generously — throughout the year.
Special appreciation to everyone who contributed across writing, teaching, reviewing, events, podcasts, and partnerships: Siddarth R, Banani Mohapatra, Sai Kumar, Vedha Ravi, Udit Manav, Arnav Ashank, Arun Subramanian, Sravya Madipalli, Karun Thankachan and many others who helped shape ideas behind the scenes.
We met learners and community members in NYC, Boston, Chicago, and the Bay Area, bringing PrepVector conversations into real rooms.
These meetups were energizing reminders that learning doesn’t stop at screens. Whether it was a quick coffee chat or a long career discussion, every interaction shaped how we think about the next chapter we’re building.
Looking Ahead: 2026 Roadmap 🚀
As we close the chapter on 2025, there’s a lot of gratitude and even more momentum. In 2026, we will double down on high-leverage learning experiences that move the needle. We’re kicking it off with a strong lineup of learning experiences and community events.
Demo Day | Jan 17, 2026
Join us to see learners from our Product Data Science Bootcamp tackle real industry problems end-to-end — from framing ambiguous questions to delivering actionable, product-ready recommendations. This is your chance to see what strong product data thinking actually looks, understand how metrics and experimentations come together to drive growth. Finally, you will get to learn about the Product Data Science Bootcamp and interact with alumni who have been through the journey.
Bay Area In-Person Meetup | Jan 24, 2026
We’re bringing the data and product community together in the Bay Area for an evening of community and conversations. Network with data and product professionals, exchange ideas, and learn about the latest in the AI space.
A/B Testing Workshop for Data Scientists & Product Managers | Jan 31 - Feb 02, 2026
This two-day workshop is designed for data scientists and product managers to get started with experimentation, learn how to drive product growth, and understand the basics of good experimentation practices.
Advanced A/B Testing Workshop | Feb 7–8, 2026
This two-day intensive is designed for mid-to-senior DS professionals who want to handle real-world experimentation complexity, including power analysis, heterogeneous treatment effects, advanced causal methods, and decision-making under uncertainty.
Product Data Science Bootcamp | Feb 10, 2026
An immersive, end-to-end program focused on the full lifecycle of Product Data Science:
Framing ambiguous business problems
Defining metrics that matter
Designing experiments that drive revenue
Communicating insights that influence product and leadership decisions
Built for professionals who want to move beyond analysis into real impact.
Let’s build the next chapter together. 🎉