Everywhere you look, there is another “learn X in 6 weeks” promise. Short courses and certificates are easy to start and easy to share on LinkedIn. But if you want to work seriously with Data Science and AI, are quick snippets really enough.

Mark, a Data Science and AI student at Amsterdam Tech, does not think so. After 25 years in global banking and tech, he chose a 17–18 month foundational journey instead of one more short course. His story shows why depth beats speed when you want to build something that lasts.

From early internet banking to AI‑driven marketing

Mark is originally from Rotterdam. He has spent more than two decades in financial services, often at the front edge of change. Early in his career, he joined a core team that built internet and phone based banks across Europe, the US, and Australia.

From there, his path moved through payments, data warehousing, business intelligence, and marketing campaign management. He has always worked where business and technology meet, and he believes they only work well when they are integrated, not separate.

Today he lives in Chicago and works for one of the largest banks in the United States. His focus is marketing technology. He and his team connect the bank’s data with platforms like Google, Meta, and Amazon to understand how customers move and choose. To keep up with this complex world, they use predictive AI, robotics, machine learning, and data science.

Why a veteran chose to “go back to school”

With this kind of background, you might expect Mark to feel “done” with formal learning. Instead, he decided to return to structured study.

He chose Amsterdam Tech for three main reasons:

• Self‑paced learning. The online curriculum lets him study at his own rhythm. It demands discipline, but it fits around meetings, travel, and different time zones.
• Flexibility of place and time. Mark has lived in eight countries. He needs learning that can move with him, not tie him to one city or campus.
• Foundational depth. He had already taken short, certificate based courses from top universities. They were useful, but each one was just a small piece of the puzzle. He wanted a long, connected journey that builds solid understanding over 17–18 months.

For Mark, speed was no longer the main goal. Depth, structure, and continuity mattered more.

Why short snippets were not enough

Short courses can give you a taste of a topic. They can boost your confidence or fill a small gap. But Mark noticed their limits. Each one was like a single chapter without the rest of the book.

He wanted:

• A consistent path from basic concepts to more advanced models.
• Enough time to connect ideas, instead of jumping from trend to trend.
• A learning journey that matched the complexity of the problems he faces at work.

In other words, he did not just want to “talk AI.” He wanted to understand it well enough to do AI in real systems, with real impact.

How project based learning keeps depth practical

Amsterdam Tech’s project based approach was an extra benefit for Mark. It mirrors what happens in the office.

In Module 1 of his programme, he and his group:

• Explored data through Exploratory Data Analysis (EDA).
• Cleaned data and detected anomalies, so models would not be built on bad inputs.
• Practised feature engineering with methods like RFM (Recency, Frequency, Monetary)and PCA (Principal Component Analysis) to make data more meaningful.

For Mark, these projects were not just homework. They were a chance to step away from routines and ask a deeper question. Not “How fast can I finish this task,” but “Am I doing the right things right.”

This is what a long, foundational journey gives you. Time to question, refine, and re‑design how you think.

Resetting skills to sharpen leadership

Mark has led large agile transformations and helped design organisations. He already understands strategy and leadership. Yet he chose to restart his Python skills from zero.

He is not trying to become a full‑time software developer. His goal is to understand the conceptual approach behind the code his teams write. By starting again, he:

• Sees where he had become “unconsciously incompetent,” assuming he knew more than he did.
• Gains fresh insight into the tools that power the systems he leads.
• Bridges the gap between leadership and technology, so he can have clearer, more grounded conversations with his teams.

This is another benefit of a longer programme. You have space to rebuild foundations instead of patching over weak spots with quick fixes.

Looking ahead: from concepts to real models

The next phase of Mark’s journey is Machine Learning. He sees this as the point where data concepts turn into working models.

He wants to learn how to:

• Build models that actually learn from data.
• Validate and value those models, so you know when they are reliable.
• Scale them, so they work in real systems, not just in notebooks.

For him, this is where the 17‑month journey really shows its worth. There is enough time to understand each step, practise it, and connect it to real work.

What you can take from Mark’s story

You might not have 25 years in banking or eight countries on your CV. That is fine. Mark’s story still holds a message for you.

If you are serious about Data Science, AI, or any deep tech field:

• Short courses can be helpful, but they are not a full education.
• A long, foundational path can feel slower, but it builds confidence that lasts.
• Your existing experience, in business or any other field, becomes more powerful when you add real technical depth.

At Amsterdam Tech, our online, part time programmes are designed for exactly this kind of journey. You get structure, projects, and a community that supports you as you move from “curious” to “capable.”

When you are ready, you do not have to rush through another shortcut. Explore our programmes, see if a 17‑month foundational journey in Data Science and AI or another tech field fits your goals, and treat it as the start of a deeper, more confident chapter in tech, on your terms.