First Data Analysis from Zero to Hero projects presentation

Swiss Coding Academy hosted an important event - the first defense of the final projects of our Data Analysis from Zero to Hero program. It was a powerful, emotional and very inspiring evening, which was a real demonstration of how much a person can achieve in just a few months of intensive training.

Jury

The participants' projects were evaluated by:

• Hoan Quoc - Senior Data Analyst, course instructor
• Anton Agapov - international guest from Europe (Serbia), researcher in the field of education and human sciences
• Mariia Usherovich - former Head of Analytics Department, course instructional designer
• Ruslan Abkadirov - Managing Director, former Head of Product, Swiss Coding Academy

Anton Agapov noted:

"I was surprised by the depth of students' thinking. Their projects are not academic exercises, but full-fledged analytical studies that can be applied in real business. You can see that they understand data, sense patterns, and are able to make decisions based on facts - and that's the real skill of a data analyst."

Anton Agapov, Researcher from Europe (Serbia)

What the projects were about

Students submitted work reflecting a wide range of real-world challenges, from marketing and healthcare to banking analytics. For example:

🧠 Analyzing the risk of Alzheimer's disease and creating a predictive model

One of the projects focused on analyzing risk factors for Alzheimer's disease. The student built a model that categorizes the likelihood of the disease based on medical, demographic, and cognitive variables.

📈 Marketing analytics for the luxury apartment rental market

The other work was a comprehensive marketing analytics using Python, Power BI, and machine learning techniques. The project included predicting key metrics, studying factors affecting advertising effectiveness, and analyzing user behavior.

💳 Bank card transaction analytics (24 million records!)

One of the largest projects: analyzing 24 million Kaggle transactions, identifying fraudulent transactions, studying credit limits, customer behavior and spending trends.

📉 Cost per lead (CPL) prediction model for different advertising channels

Student developed their own CPL prediction model across Facebook, Google and LinkedIn channels, built dashboards and conducted a factor analysis, providing recommendations for optimizing a company's media budget.

What results the graduates have shown

We are truly proud of each participant. The defense presentations proved that the students:

• perform deep and complex analytics, including data cleaning, EDA, model building, and interpretation of results;
• are proficient in Python tools including pandas, seaborn, sklearn, and statistical methods;
• are adeptat building professional dashboards in Power BI that are suitable for real-world companies;
• draw informed conclusions from the data and confidently answer questions from the jury;
• actually solve business problems, rather than "doing a project for the sake of a project".

The graduates demonstrated not only technique, but also maturity of analytical thinking - something that distinguishes Junior+ level specialists.

This is just the beginning

This defense was a symbol for us that we are moving in the right direction. Our students have, in a short time, become practicing analysts who can bring value to businesses today.

We congratulate the graduates and thank all the faculty, experts and mentors who invested time and heart in this stream.

New projects, new challenges and new success stories are ahead.