Sensor Fusion and Machine Learning in Self-Driving Cars
( 25 Modules )

Module #1
Introduction to Self-Driving Cars
Overview of self-driving car technology, its applications, and the importance of sensor fusion and machine learning.

Module #2
Sensor Types and Fundamentals
Exploration of various sensor types used in self-driving cars, including cameras, lidars, radars, ultrasonic sensors, and GPS.

Module #3
Sensor Fusion Basics
Introduction to sensor fusion concepts, including data fusion, feature extraction, and sensor calibration.

Module #4
Machine Learning Fundamentals
Overview of machine learning concepts, including supervised, unsupervised, and reinforcement learning.

Module #5
Introduction to Deep Learning
Basics of deep learning, including neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs).

Module #6
Camera Sensor Fusion
In-depth look at camera sensor fusion, including image processing, object detection, and camera calibration.

Module #7
Lidar Sensor Fusion
In-depth look at lidar sensor fusion, including point cloud processing, object detection, and lidar calibration.

Module #8
Radar Sensor Fusion
In-depth look at radar sensor fusion, including radar signal processing, object detection, and radar calibration.

Module #9
Sensor Fusion Architectures
Overview of different sensor fusion architectures, including centralized, decentralized, and hybrid approaches.

Module #10
Kalman Filter and Bayesian Estimation
In-depth look at Kalman filter and Bayesian estimation techniques for sensor fusion and state estimation.

Module #11
Object Detection and Tracking
Introduction to object detection and tracking techniques, including YOLO, SSD, and tracking algorithms.

Module #12
Scene Understanding and Semantic Segmentation
In-depth look at scene understanding and semantic segmentation techniques, including FCN, U-Net, and segmentation algorithms.

Module #13
Motion Forecasting and Prediction
Introduction to motion forecasting and prediction techniques, including trajectory prediction and motion modeling.

Module #14
Machine Learning for Sensor Fusion
Applications of machine learning in sensor fusion, including sensor selection, feature extraction, and fusion algorithms.

Module #15
Deep Learning for Sensor Fusion
Applications of deep learning in sensor fusion, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

Module #16
Sensor Fusion for Motion Planning
In-depth look at sensor fusion for motion planning, including path planning, motion planning, and control algorithms.

Module #17
Sensor Fusion for Localization and Mapping
In-depth look at sensor fusion for localization and mapping, including SLAM, odometry, and mapping algorithms.

Module #18
Real-World Sensor Fusion Challenges
Discussion of real-world challenges in sensor fusion, including sensor noise, occlusion, and weather conditions.

Module #19
Sensor Fusion for Autonomous Vehicle Testing
In-depth look at sensor fusion for autonomous vehicle testing, including simulation, validation, and verification.

Module #20
Sensor Fusion for Autonomous Vehicle Deployment
In-depth look at sensor fusion for autonomous vehicle deployment, including system integration, calibration, and maintenance.

Module #21
Case Studies in Autonomous Vehicles
Real-world case studies of autonomous vehicle development, including sensor fusion and machine learning applications.

Module #22
Ethics and Regulations in Autonomous Vehicles
Discussion of ethics and regulations in autonomous vehicles, including safety, security, and privacy concerns.

Module #23
Future of Autonomous Vehicles
Overview of the future of autonomous vehicles, including trends, challenges, and opportunities.

Module #24
Hands-on Project:Sensor Fusion and Machine Learning
Guided project to implement sensor fusion and machine learning techniques in a self-driving car scenario.

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Sensor Fusion and Machine Learning in Self-Driving Cars career

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Sensor Fusion and Machine Learning in Self-Driving Cars ( 25 Modules )

Sensor Fusion and Machine Learning in Self-Driving Cars
( 25 Modules )