Training programs and individual courses
This course is for those who want to understand the link between data and business value and have an effective process to produce data that provides measurable business value. You will learn a process to iteratively go from requirements to finished datasets that can be used for everything from visualizations, such as dashboards, to machine learning models. You will learn effective ways to develop concrete requirements that will help you in your data analysis and the different ways you can go from these requirements to concrete datasets. From these datasets, you will then learn how to effectively plan a structure that makes it easier to work with.
This course is for those who want to understand how modern data pipelines are built and optimized, as well as what tools and techniques are used in industry today to manage, transform and load data. You will learn how to create efficient ELT and ETL workflows, from data sources to final destinations such as data warehouses or analytics platforms. The course covers common tools and platforms used in the industry, as well as typical pitfalls that can affect performance, data quality and scalability. You will also gain insights into troubleshooting and best practices to avoid common mistakes and optimize your data flows for robustness and efficiency.
This course is for those who want to understand how modern databases and data storage work, and how to manage both batch and real-time data effectively. You will learn the differences between different types of databases and how to choose the right solution for specific business and technical needs. You will also learn how to use files effectively for large amounts of data and its benefits. The course covers techniques for storing and processing everything from small to large data sets and how to create efficient workflows for both batch and real-time data. You will also gain insight into how these processes impact performance, scalability and reliability in modern data-driven environments.
This course is for those who want to learn how to manage and optimize data in the cloud. It is suitable for those who are new to the industry or want to shift their focus to cloud data management and want to understand how to create scalable and high-performance data solutions in the cloud. Learn how organizations today are using the cloud to manage data and build scalable solutions. Learn about different cloud services, their pros and cons across different providers, and how to get the most out of your data. We will go through common workflows that Data Engineers use to implement their solutions on cloud platforms.
This course provides you with a basic understanding of artificial intelligence (AI) and machine learning (ML) with a focus on how these techniques can be used to analyze, process, and draw insights from large data sets. You will learn common methods and tools in AI and ML that are useful for developers and data engineers, as well as frameworks for implementing these techniques to create business value. The course also covers data prediction and the data requirements needed for effective analytics. We will also address aspects of data security and data compliance
Marc Jamot is a prominent data specialist with a focus on evaluating, planning and running data/ML/AI projects from start to finish. He also has a broad experience in setting up frameworks, supporting and guiding decision makers in organizations to use data as a tool to gain a better understanding in decision making.
For the past 10 years, Marc has played a central role in building up data management at companies such as Aller, Lendo and Fever. He has been running STOIX for a couple of years, which provides products and services in data automation and strategy in data management and linking data to corporate strategy. STOIX has had Spotify, LKAB and Stockholm University as customers. Marc has a Master of Science in Information Technology from Chalmers University of Technology.
Stockholm
Göteborg