From Logistics to AI: Sahand Azizi's WBS CODING SCHOOL Journey

WBS CODING SCHOOL has been training data professionals through its comprehensive Data Science and AI program. We recently spoke with graduate Sahand Azizi, who, after a decade in foreign trade and supply chain management, leveraged the program to pivot into a new career he starts this month. We sat down with Sahand to discuss what inspired his career change into data science and AI, the reality of his year-long bootcamp and internship experience, and the innovative way he landed his new role.

Sahand, what was your background before joining WBS CODING SCHOOL?

Before joining WBS CODING SCHOOL, I was studying civil engineering at first, but I paused that and shifted my focus to foreign trade and logistics because I'm multilingual. After some time, I noticed that we had very repetitive, time-consuming tasks every day – things like quoting and cost estimation. I was using Excel to automate those and save my data, but I knew I was going to hit the limits of Excel. 

My last role was as an executive assistant at Unilever in Iran, and after that, I migrated to Germany. That move became my chance to actually learn data science and all the tools that come with it – to evolve in this new era.

Why did you choose the Data Science and AI program at WBS CODING SCHOOL over other options? What stood out to you?

To be honest, the main reason was their people-centric attitude. I was new in Germany and didn't know much about the institutions or other schools there. But the way they helped me – walking me through every step, explaining the curriculum and everything I was going to experience over the next year – made me feel secure enough to commit to the program.

What was the day-to-day experience like in the data science and AI program?

Honestly, at first I was afraid I wouldn't be able to keep up, because it was a full-time commitment – 9 a.m. to 5:30 p.m., with only two breaks across the entire year. But once I got started, I realized we really did need that much time, because we covered so many topics and needed plenty of time for practice.

Whenever I was stuck or losing focus, I could easily go back and watch the recorded sessions from our classes, or read through the learning materials WBS CODING SCHOOL had created for us. I also had great classmates – we were learning together during the day and gaming online together at night. We lost a lot of matches, but it was a lot of fun.

What did you learn at WBS CODING SCHOOL?

The key topics were Python, SQL, Looker Studio, Tableau, machine learning, statistics, and cloud computing with Microsoft Azure. One important thing was that for each tool we used, we worked with near-real-world data – very practical, not just theoretical exercises. We also covered data cleaning, which is something anyone learning in this field really needs to know how to handle well.

What was the most challenging or rewarding subject?

Definitely machine learning. It was very challenging, but also very promising. So much of what we use today – everything AI-related – comes from machine learning. For me, it's almost like an art: translating images, voices, sounds, and text into numbers that machines can understand, generating the desired output, and then translating that back into human language. That was the topic I enjoyed the most.

Tell me about the portfolio you built in the program. Can you tell me about one of the projects you worked on?

I remember when I was applying to the program, they told me we'd complete 13 hands-on projects – but I think I ended up with 18 or more, between the coursework and things I built on my own time. My favorite was our final project, which was required to complete the course.

It was a solar panel planner. The idea was that you could enter your address, view your rooftop, see how many panels could fit, how shadows would affect your power output, and how the sun's azimuth and panel angles would impact efficiency. You could also calculate how much you'd need to invest and what your projected earnings would look like – and at the end, you could send an inquiry directly to your nearest solar panel installer for a personalized offer.

I wasn't working alone – my teammates Olaf and Victoria co-created this project with me. We used a lot of Python, machine learning, computer vision, AI retrieval-augmented generation – pretty much everything we learned throughout the course made it into that final project.

Tell me about your internship experience. Did WBS CODING SCHOOL set it up for you, or did you find it yourself?

Because the school guaranteed an internship as part of the program, it gave us the confidence to pursue the process. Paola from WBS CODING SCHOOL's Career Services was the one who recommended I apply for this particular internship. I applied, went through the interviews, and got accepted. The company was share – an FMCG company. It was important to me to spend those two internship months in a role that was meaningful and aligned with my previous experience. So while the school didn't place me directly, they really did help me secure it.

So what did you learn from this internship that you couldn't learn in class?

In my previous experience, I'd worked with a lot of data pulled from ERP (enterprise resource planning) systems. But working inside a company that makes real decisions based on data, using raw data for a specific purpose – that was a different level of challenge. The data was much messier than you'd expect, and you have to know clearly what you need and what you want to do with it before you can clean and prepare it properly. That internship taught me that data cleaning is probably 50% of the actual role.

How did that internship experience confirm that data science is the career path where you want to grow?

In my previous job, I was forecasting sales for sales representatives across different regions to set targets and motivate the team. But I was doing that mainly with historical data, Excel formulas, and experience-based judgment – so the targets weren't always as accurate as I'd have liked.

At share, they wanted to build statistical sales forecasting using time series analysis – a branch of machine learning – to predict how sales would look in future months. I only had seven or eight weeks, but in that time I was able to improve their forecasting accuracy from 55% to 79%. That made me realize how much more is possible with code. What might take a team of ten people doing different things manually, you can accomplish much more efficiently with the right tools.

Did you earn any certifications during the program? Did they help you in the job market?

Aside from the final certificate from the school, we also earned three professional certifications. When I first saw the list of topics on the WBS CODING SCHOOL certificate, I thought they'd exaggerated what we'd learned, until I realized we actually had covered all of it in one year.

• The first certification was the PCEP, the Python Certified Entry-Level Programmer

• Microsoft Azure DP-900, for cloud computing

• Scikit-learn Practitioner

I’m most proud of the Scikit-learn certification. Scikit-learn is one of the machine learning libraries we used throughout our projects. What made that exam memorable was that we were allowed to reference the library documentation during the test – but mine wouldn't open. My first instinct was panic, but once I focused, I realized I knew the material well enough to answer everything from memory. A big thanks to Kevin, our instructor in that area, for that preparation.

As for whether the certifications help – absolutely. When I say on my resume that I know how to program in Python, these certifications validate that. For me, they are proof of what I am claiming.

You're about to start a new job – congratulations! Can you share what the role is, how you landed it, and whether WBS CODING SCHOOL was helpful in that process?

Throughout the course, we had a lot of sessions on how to write CVs, how to approach employers, and what to focus on when applying. But after finishing the program, I actually built my own job search automation tool using what I'd learned.

It was a fully automated system that read job listings from my preferred locations, and then used AI to score each one based on my profile. Instead of applying to 100 or 200 jobs, I focused on quality – identifying the best-fit opportunities and applying to those carefully.

The job I found is a Design Engineer role at Facade Technologies, part of the Züblin company. The reason I accepted it comes back to my previous experience in that field – but what set me apart from other candidates was the data science and AI background. Construction work isn't just about drawings and technical documents; it involves heavy calculations, from bill of materials to static structural analysis. In this role, I'll be building automation tools to reduce errors and improve those processes. I start next week.

Can you walk me through the timeline of your job search, from deciding to build your custom search engine to landing your new role?

I started searching early – six months before finishing the course – but the main search began after my internship. It only took about 20 days to land the job because my job search automation tool was so helpful. It let me stop spending time reading through listings and deciding if something was a fit – and instead focus all my energy on applying as well as possible to the right opportunities.

What is your advice for others with an established career who are considering a change into data science?

For me personally, I have to feel genuine passion for something in order to push through and actually achieve it. So if you love looking at data and making decisions based on it, I'd absolutely encourage you to explore this field.

I also want to say that my goal was never specifically to become a data scientist in the traditional sense – that's more of an academic title. For me, data science was a tool. Whatever I learned, I planned to apply it to my own domain knowledge and previous experience to create better solutions – whether in construction, FMCG, or anywhere else.

If you already have domain experience, you're going to be able to put these new skills to powerful use immediately. And if you don't have industry experience yet, that's fine too – you'll bring these skills to a company and use them to answer their questions and solve their problems. Either way, there's a path.

Was WBS CODING SCHOOL worth it for you?

Well, they did give me a free MacBook Air – I'm just kidding! That was a nice bonus, of course.

But what really stood out to me was the quality of the instructors. It felt like they were handpicked from all over the world. They didn't just have real-world industry experience – they also had deep academic knowledge in what they were teaching, and they were genuinely invested in helping us succeed.

The Career Services component was also a major differentiator. Learning new skills matters, but being able to sell yourself to an employer – explaining clearly what you can do and how you can solve their problems – that's equally important. In my opinion, it was a complete package for anyone who wants to grow in this new world.

Find out more and read WBS CODING SCHOOL reviews on Course Report. This article was produced by the Course Report team in partnership with WBS CODING SCHOOL.