Data Analysis
A key tool for the development of sustainable innovative solutions
Why?
An enormous amount of data is generated globally every minute. Novel techniques such as machine learning and AI are powerful tools to refine and utilize the potential in that data. However, many insights are still obtained via manual programming work and e.g. regression techniques.
Globally, we are currently facing complex challenges with many contributing factors, such as global warming. I believe AI tools and sophisticated algorithms working in tandem will be part of the key tools to find sustainable innovative solutions to such problems.
How?
So far, I have worked in Julia, Python, Java, C++, HTML, CSS, JavaScript, COMSOL and MATLAB. I am also familiar with SQL, R and REST.
Regarding machine learning tools, I have worked mainly in Python (PyTorch, Keras, Tensorflow) and MATLAB, but also in Julia (Flow.jl etc). In addition to applications built on neural networks, related AI-concepts such as Hidden Markov Models, Gaussian processes and different types of optimized search-algorithms are also within my comfort zone.
To use data analysis to develop innovative solutions and contribute to a sustainable future is a passion of mine.
Completed university courses on AI & Data Science:
- Artificial Intelligence (DD2380, KTH)
- Search Engines and Information Retrieval Systems (DD2476, KTH)
- Deep Learning in Data Science (DD2424, KTH)
- Scientific Machine Learning (02977, DTU)
- Advanced Topics in Machine Learning (02901, DTU)
- Bayesian Scientific Computing (02962, DTU)