Skills for a Data-Driven Future
Quantia Consulting trains professionals and decision-makers to meet the challenges of the data economy. Our programs combine scientific rigor with practical application, helping individuals and organizations build strategic skills in data science, analytics, and digital transformation.
Target
The catalog addresses both technical professionals and business-oriented roles. Technical tracks focus on programming languages, data analysis techniques, and scalable information processing, with emphasis on parallelization and real-time computation. Business courses help participants apply data in decision-making processes, visualize information effectively, and manage data-driven projects. Executive modules are also available for those interested in driving digital transformation.
Methodology
Quantia courses combine theoretical lessons with strong practical activities. Lectures (10–30% of the time) introduce key concepts, while group work (up to 50%) simulates real-world scenarios to apply knowledge. The remaining 20% is used for presentations and discussions to share experiences. Technical courses also include the use of coding notebooks and intensive bootcamps to tackle real-world challenges.
Categories
Business Analytics & Decision Making
Courses for managers and professionals looking to use data to make smarter decisions. Topics include effective visualizations, KPIs, risk management, and agile management of data projects. Perfect for building a data-driven culture.
Example courses:
- Data for Business
- Data Visualization
- Agile Data & MLOps
- Risk Management in Data-Driven Projects
- KPIs and Metrics for AI Project Success
Data Engineering & Cloud Platforms
Technical training on building scalable infrastructures for data management. Focus on data ingestion, preparation, and orchestration using cloud technologies and open-source tools for distributed and real-time processing.
Example courses:
- Data Ingestion & Preparation
- Data Stores & Processing Platforms
- Cloud Data Engineering (BigQuery, Dataflow, Pub/Sub)
- DataOps, DevOps & Infrastructure as Code
- Real-Time Data Processing with Kafka and Spark Streaming
Data Science & AI
Practical training tracks to understand and apply machine learning, deep learning, and data science techniques. Activities include Exploratory Data Analysis (EDA), model selection and development, and results interpretation in dynamic, business-relevant scenarios.
Example courses:
- Exploratory Data Analysis
- Supervised & Unsupervised Machine Learning
- Deep Learning
- Streaming Machine Learning
- Time Series Analytics & Forecasting
- Anomaly Detection
- Model Interpretability & Explainability
Generative AI &
Conversational
Technologies
A hands-on introduction to Generative AI technologies. From foundational models (GPT, GAN, VAE) to business applications involving intelligent agents and Retrieval-Augmented Generation (RAG) systems for process automation, content generation, and decision support. Courses also cover ethical considerations and evaluation methodologies.
Example courses:
- Generative AI – Concepts, Models, Ethics
- GANs, VAEs, Diffusion and Transformer-based Models
- Prompt Engineering & Intelligent Agents
- Generative AI and RAG Systems for Business
- Evaluation and Risk Mitigation for Generative AI
Advanced Analytics & Emerging Technologies
Tracks for those seeking innovation in their organizations by exploring technologies like semantic interoperability, advanced NLP, multimodal AI, and model explainability on complex data.
Example courses:
- Semantic Web Technologies & Ontology Engineering
- Advanced Image & Video Analytics
- Advanced NLP and Language Models (BERT, GPT)
- Explainability on Structured and Unstructured Data
- AI Ethics and Model Governance