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Additional Content
Prediction
David Silver,
Thomas Hossler,
Antje Muntzinger,
Andreas Haja,
Aaron Brown,
Munir Jojo Verge,
and
Mathilde Badoual
David Silver,
Thomas Hossler,
Antje Muntzinger,
Andreas Haja,
Aaron Brown,
Munir Jojo Verge,
and
Mathilde Badoual
Find additional content here on prediction, helping autonomous vehicles to predict how other vehicles and objects might move in the future.
Register for this course and see more details by visiting:
OpenCourser.com/course/qn2i0i/additional
What's inside
Syllabus
Use data from sensor fusion to generate predictions about the likely behavior of moving objects.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines prediction, which is standard in autonomous vehicles industry
Taught by David Silver, Thomas Hossler, Antje Muntzinger, Andreas Haja, Aaron Brown, Munir Jojo Verge, and Mathilde Badoual, who are recognized for their work in autonomous vehicles
Develops skills in using data from sensor fusion to generate predictions about the likely behavior of moving objects
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Activities
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Additional Content: Prediction.
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Career center
Learners who complete Additional Content: Prediction will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers are responsible for research, design, development and implementation of artificial intelligence solutions. This course on prediction can be very useful for this role, providing insights and techniques for developing and refining predictive models and algorithms.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, develop, build, and test robots. This course on prediction may be useful to them as many robots have predictive capabilities.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. This course can help build a foundation in the area of data science, which can be very useful.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for the design, development, and deployment of machine learning models. This course can help build a foundation in this area, which can be useful.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to help businesses and organizations make informed decisions. This course on prediction may be useful for developing skills in statistical modeling and prediction.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course on prediction is likely to be moderately useful, especially for those who work on self-driving cars.
Product Manager
Product Manager
Product Managers are responsible for the planning, development, and launch of new products. This course on prediction may be useful for understanding how to anticipate customer needs and preferences.
Market Researcher
Market Researcher
Market Researchers study market trends and customer behavior to help businesses make informed decisions. This course on prediction can help build a foundation in understanding how to predict consumer behavior.
Business Analyst
Business Analyst
Business Analysts identify business needs and opportunities and develop solutions to address them. This course on prediction may be useful for understanding how to anticipate future trends and opportunities.
Data Analyst
Data Analyst
Data Analysts clean, analyze, and interpret data to help businesses make informed decisions. This course on prediction may be useful for learning how to identify trends and patterns in data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze and interpret data. This course on prediction may provide some insights into how to predict financial trends.
Risk Manager
Risk Manager
Risk Managers identify, assess, and manage risks to businesses and organizations. This course on prediction may provide insights into how to anticipate and mitigate future risks.
Financial Analyst
Financial Analyst
Financial Analysts evaluate and interpret financial data to help businesses make informed decisions. This course on prediction is less relevant, but may provide some insights into how to anticipate future financial trends.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use analytical and mathematical techniques to help businesses make decisions about how to improve their operations. This course on prediction may be useful for improving forecasting and decision-making skills.
Auditor
Auditor
Auditors examine financial records and documents to ensure that they are accurate and complete. This course on prediction is likely to be of little relevance.
For more career information including salaries, visit:
OpenCourser.com/course/qn2i0i/additional
Reading list
We've selected 13 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Additional Content: Prediction.
Provides an in-depth overview of prediction algorithms and their applications in machine learning and game theory.
Provides a hands-on guide to building and evaluating predictive models using machine learning techniques.
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Provides a hands-on guide to building and evaluating predictive models using machine learning techniques.
Provides a comprehensive overview of sensor fusion and localization algorithms, which are essential for autonomous vehicles to determine their position and orientation in their environment.
Provides a comprehensive overview of machine learning from a probabilistic perspective.
Provides a comprehensive overview of statistical learning methods, which are essential for understanding prediction algorithms.
Provides a comprehensive overview of prediction, optimization, and statistics, which are essential for understanding prediction algorithms.
Provides a comprehensive overview of probabilistic robotics, which combines probability theory and robotics to enable robots to navigate and interact with their environment.
Provides a comprehensive overview of advanced control engineering techniques, which are essential for autonomous vehicles to control their movement and stability.
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Provides a comprehensive overview of planning algorithms, which are essential for autonomous vehicles to make decisions about how to move through their environment.
Provides a solid foundation in probability theory and Bayesian statistics, which are essential for understanding prediction algorithms.
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Provides a comprehensive overview of supervised learning algorithms, which are essential for understanding prediction algorithms.
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Provides a comprehensive overview of computer vision algorithms and their applications in areas such as object detection and tracking.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qn2i0i/additional
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Time
90 hours
Level
Advanced
Via
Udacity
Instructors
David Silver
Thomas Hossler
Antje Muntzinger
Andreas Haja
Aaron Brown
Munir Jojo Verge
Mathilde Badoual
Language
English
Good to know
Examines prediction, which is standard in autonomous vehicles industry
Taught by David Silver, Thomas Hossler, Antje Muntzinger, Andreas Haja, Aaron Brown, Munir Jojo Verge, and Mathilde Badoual, who are recognized for their work in autonomous vehicles
Develops skills in using data from sensor fusion to generate predictions about the likely behavior of moving objects
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