Explores the challenges and examples of decentralized systems like BitTorrent and Ethereum.
Explores combining data at rest with data in motion, emphasizing the Lambda architecture complexities and quality assessment of streams and batches.
Covers the theory and applications of Markov chains in modeling random phenomena and decision-making under uncertainty.
Explores the Swiss energy sector's actors, ownership structure, challenges, and innovative solutions for future energy supply.
Introduces collaborative data science tools like Jupyter notebooks, Docker, and Git, emphasizing data versioning and containerization.
Explores the convergence of IoT, Big Data, and Deep Learning in Artificial Intelligence applications across various industries.
Covers the review of function spaces and explores the concept of compact operators.
Explores the significance of intellectual property in fostering innovation and protecting creations of the mind, covering patents, trademarks, copyrights, legal frameworks, and enforcement mechanisms.
Covers the essentials of Data Science using Python, Numpy, Pandas, and Scikit-learn, including DNA sequence analysis and classification.
Explores advanced data stream processing concepts, including Kafka, Spark stream, joins, and route planning models.
