IsraelX: Bayesian Algorithms for Self-Driving Cars
|
“Bayesian Algorithms for Self-Driving Cars” is an advanced Computer science course, designed to equip the student with the most important localization algorithms now deployed in modern autonomous vehicles.
About this course
“Bayesian Algorithms for Self-Driving Cars ” is a MOOC that will boost your skills and will prepare you for a career in the industry.
The course was designed to help students bridge the gap between “classic” algorithms and the concept of Bayesian localization algorithms.
We will explore topics such as the Markov assumption and which is utilized in the Kalman filter, the concept of Histogram filter and multi-modal distributions, the particle filter and how to efficiently program it, and many more.
In addition to many questions and exercises, we’ve included also 4 programing assignments so you will be able to actually program these algorithms for yourself.
At a Glance:
Institution: IsraelX
Subject: Computer Science
Level: Introductory
Prerequisites:
None
Language: English
Video Transcript: English
Associated skills:Localization, Computer Science, Algorithms, Kalman Filter, Particle Filter
User Reviews
Be the first to review “IsraelX: Bayesian Algorithms for Self-Driving Cars”
Related Products
ETHx: Autonomous Mobile Robots
Basic concepts and algorithms for locomotion, perception, and intelligent navigation.
GTx: Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps
Become familiar with nonlinear and hierarchical data structures. Study various tree structures: Binary Trees, BSTs and Heaps. Understand tree operations and algorithms. Learn and implement HashMaps that utilize key-value pairs to store data. Explore probabilistic data structures like SkipLists. Course tools help visualize the structures and performance.
UCSanDiegoX: Machine Learning Fundamentals
Understand machine learning's role in data-driven modeling, prediction, and decision-making.
TokyoTechX: Introduction to Computer Science and Programming
The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simulation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to the basic key concepts of computer science. By following the lectures and exercises of this course, you will gain an understanding of algorithms by programming using the language Ruby.
HarvardX: Data Science: Machine Learning
Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
IBM: Machine Learning with Python: A Practical Introduction
Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning.
There are no reviews yet.