


Federated Learning
This lecture overviews that has many applications in distributed Machine Learning and privacy protection.



Web Search based on Ranking
This lecture overviews Web Search based on Ranking that has many applications in Web Science and Social Media Analytics. It covers the following topics in detail: Architecture of Web Search Engine: Crawler, Indexer, Query Processor.



Algebraic Graph Analysis
This lecture overviews Algebraic Graph Analysis that has many applications in Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Graph Basics.



Autonomous Underwater Vessels
This lecture overviews Autonomous Underwater Vessels that has many applications in ocean engineering. It covers the following topics in detail: AUV technologies, sensors, communications, applications.



Autonomous Surface Vessels
Autonomous marine vessels can be described as surface (boats, ships) and underwater ones (submarines).



Hidden Markov Models
This lecture overviews Hidden Markov Models that have many applications in Data Analytics and Signal Analysis. It covers the following topics in detail: Markov Chains. Hidden Markov Chains: Viterbi algorithm, Forward-backward algorithm.



Cinematography Issues in Sports Filming
This lecture overviews Cinematography Issues in Sports Filming that has many applications in digital media and TV productions.



Drone Cinematography
This lecture overviews issues related to drone cinematography for TV, cinema and media production.



Imaging for Drone Safety
This lecture overviews Imaging for Drone Safety that has many applications in autonomous drones.



Introduction to UAV Multicopters
This lecture overviews Introduction to UAV Multicopters that has many applications in autonomous drones.



Introduction to Statistics
This lecture provides an Introduction to Statistics that has many applications in Data Analytics, Machine Learning and Signal Analysis. It covers the following topics in detail: Random Variables. Data Types. Data Sampling.



Geometric Spaces
This lecture overviews Geometric Spaces that has many applications in Machine Learning and Digital Signal Processing and Analysis. It covers the following topics in detail: Vector Spaces, Affine Spaces, Metric Spaces.