


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.



Set Theory
This lecture overviews Set Theory that has many applications in Probability/Statistics, Machine Learning and Computer Vision.



Drone Communication Networks
This lecture overviews Drone Communication Networks that has many applications in autonomous drones.



Drone Mission Simulations
This lecture overviews various drone mission simulator architectures, notably AirSim and Gazebo.



Multiple Drone Communications
This lecture overviews various concepts related to multiple drone communications: LTE and WiFi communications, LTE communication infrastructure, IP network issues, Security analysis, throughput, latency and quality-of-service issues.



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.