Vormada Logo
Vormada
Walid Alzohili, Tech Consultant & Trainer

Unlock Your Potential with Expert Tech Guidance

Personalized training and strategic consulting in Python Programming, Data Science, and Machine Learning.

Explore Our Services

About Vormada

Vormada is a technology consulting and training firm based in Stockholm, Sweden. We specialize in empowering businesses and individuals through cutting-edge solutions and education in Python Programming, Data Science, and Machine Learning.

Founded by Walid Alzohili, a dedicated developer and consultant, Vormada bridges the gap between technological innovation and practical application. We offer expert guidance, hands-on training, and tailored consulting to help you master technology and achieve your goals.

We provide on-site services in the Stockholm area and deliver remote consulting and training worldwide, making our expertise accessible globally. Whether you're an entrepreneur, a corporate team, or an individual learner, Vormada is your partner in turning ideas into reality.

Our Services

Expert guidance starting at $50 USD per hour.

Available on-site in Stockholm, Sweden, and remotely worldwide.

Consulting

Expert technical guidance for your projects, short-term or long-term engagements.

Team Training

Customized training programs to upskill your team in cutting-edge technologies.

Personalized Lessons

Master specific skills with tailored one-on-one tutoring and mentorship.

Our Expertise

Leverage our deep knowledge in the following areas:

Python Programming Data Analysis & Science Machine Learning Pandas Scikit-learn (Sklearn) SciPy Data Visualization Algorithms & Data Structures Databases (SQL/NoSQL) LaTeX

Research Projects

Modeling the carbon cycle with a box-model

By Walid Alzohili | Published: 2023-05

This project aims to create a model that will predict the global temperature changes from current time until the year 2100. The predictive model is based on a box model for the carbon cycle.

View PDF

Predicting Atmospheric CO2 Concentrations With Machine Learning

By Walid Alzohili | Published: 2024-02

This report aims to improve the prediction of atmospheric CO2 concentrations using various machine-learning algorithms, motivated by climate change concerns and scientific interest in forecasting. It evaluates model performance under four emission scenarios, two increasing and two decreasing, using fossil fuel and land use emissions as inputs.

View PDF

Get Started with Vormada

Ready to enhance your skills or boost your project? Contact us today!

contact@vormada.com