Search Constraints
Number of results to display per page
Results for:
Polyu oer sim
No
Remove constraint Polyu oer sim: No
Resource Type
MOOC
Remove constraint Resource Type: MOOC
« Previous |
1 - 10 of 13
|
Next »
Search Results
-
MOOC
The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.
It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start.
- Course related:
- AAE5103 Artificial Intelligence in Aviation Industry
- Subjects:
- Computing
- Keywords:
- Machine learning Artificial intelligence
- Resource Type:
- MOOC
-
MOOC
Video games as a medium go back more than 50 years to mainframe computers. Even the central design of video games can be traced back to the first games themselves. To be a good game designer, it's essential to have an understanding of the video game design industry's fascinating history. We've partnered with The Strong National Museum of Play to give you a unique look into the history of all things video game. The International Center for the History of Electronic Games at The Strong is the largest and most comprehensive public assemblage of video games and related materials in the world. The staff are celebrated experts in the field and the ICHEG is visited by scholars of video games from around the world. You'll gain amazing insight into the history of video games with a guided exploration of key artifacts from the collection of more than 100,000 electronic games and materials.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Video games -- Design History
- Resource Type:
- MOOC
-
MOOC
Game designers work with a wide range of asset creators, programmers, producers, and others to bring a video game from concept to product. In this course, you will learn about the different types of teams a game designer is a member of, both large and small.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Video games -- Design
- Resource Type:
- MOOC
-
MOOC
Modern video games are incredibly complex multimedia productions involving still and motion graphics, code, audio, interface elements, narrative elements and much more. In this course, you will learn how and where all these pieces come from, who's in charge of each piece and the different stages of the game design process. We will also show you how everything is brought together to create a final product.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Video games
- Resource Type:
- MOOC
-
MOOC
Virtual reality is changing the way we interact with the world. But how does it work, what hardware is involved, and how is software written for it? In this course, part of the Virtual Reality Professional Certificate program, we will explore the foundations of user-friendly virtual reality app development for consumers, as well as enterprise solutions. Both hardware and software aspects will be discussed. You will learn to evaluate devices necessary for virtual reality applications, what their differences are, how you write interactive applications for virtual reality, and we will discuss the most frequent problems you are going to need to solve to write virtual reality software. In this course, you will explore the basics of virtual reality software through copying and modifying JavaScript to explore tradeoffs in VR application design. Extensive programming experience is not required. By the end of this course, you will understand what is important for successful virtual reality software and learn how to write simple virtual reality programs themselves with WebVR. This course is taught by an instructor with almost two decades of experience in virtual reality who leads the Immersive Visualization Laboratory at UC San Diego.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Computer simulation Virtual reality Human-computer interaction
- Resource Type:
- MOOC
-
MOOC
Many natural and man-made structures can be modeled as assemblages of interconnected structural elements loaded along their axis (bars), in torsion (shafts) and in bending (beams). In this course you will learn to use equations for static equilibrium, geometric compatibility and constitutive material response to analyze structural assemblages. This course provides an introduction to behavior in which the shape of the structure is permanently changed by loading the material beyond its elastic limit (plasticity), and behavior in which the structural response changes over time (viscoelasticity). This is the second course in a 3-part series. In this series you will learn how mechanical engineers can use analytical methods and “back of the envelope” calculations to predict structural behavior. The three courses in the series are: Part 1 – 2.01x: Elements of Structures. (Elastic response of Structural Elements: Bars, Shafts, Beams). Fall Term Part 2 – 2.02.1x Mechanics of Deformable Structures: Part 1. (Assemblages of Elastic, Elastic-Plastic, and Viscoelastic Bars in axial loading). Spring Term Part 3 – 2.02.2x Mechanics of Deformable Structures: Part 2. (Assemblages of bars, shafts, and beams. Multi-axial Loading and Deformation. Energy Methods). Summer Term
- Subjects:
- Mechanical Engineering
- Keywords:
- Strength of materials Deformations (Mechanics)
- Resource Type:
- MOOC
-
MOOC
In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the coordination among multiple vehicles. This course will teach you the fundamental mathematical model for many of these real-world problems. Key topics include Markov decision process, reinforcement learning and event-based methods as well as the modelling and solving of decision-making for autonomous systems. This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge in decision-making models for autonomous systems. Enhance your decision-making skills in automotive engineering by learning from Chalmers, one of the top engineering schools that distinguished through its close collaboration with industry.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Decision making Automobiles -- Design construction Automated vehicles
- Resource Type:
- MOOC
-
MOOC
Electric powertrains are estimated to propel a large part of road vehicles in the future, due to their high efficiency and zero tailpipe emissions. But, the cost and weight of batteries and the time to charge them are arguments for the conventional powertrain in many vehicles. This makes it important for engineers working with vehicles to understand how both these powertrains work, and how to determine their performance and energy consumption for different type of vehicles and different ways of driving vehicles. This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge about electric powertrains. In this course, you will learn how electric and conventional combustion engine powertrains are built and how they work. You will learn methods to calculate their performance and energy consumption and how to simulate them in different driving cycles. You will also learn about the basic function, the main limits and the losses of: Combustion engines, Transmissions Electric machines, Power electronics Batteries. This knowledge will also be a base for understanding and analysing different types of hybrid vehicles, discussed in the course, Hybrid Vehicles. As a result of support from MathWorks, students will be granted access to MATLAB/Simulink for the duration of the course.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Electric vehicles Automobiles -- Power trains
- Resource Type:
- MOOC
-
MOOC
The building industry is exploding with data sources that impact the energy performance of the built environment and health and well-being of occupants. Spreadsheets just don’t cut it anymore as the sole analytics tool for professionals in this field. Participating in mainstream data science courses might provide skills such as programming and statistics, however the applied context to buildings is missing, which is the most important part for beginners. This course focuses on the development of data science skills for professionals specifically in the built environment sector. It targets architects, engineers, construction and facilities managers with little or no previous programming experience. An introduction to data science skills is given in the context of the building life cycle phases. Participants will use large, open data sets from the design, construction, and operations of buildings to learn and practice data science techniques. Essentially this course is designed to add new tools and skills to supplement spreadsheets. Major technical topics include data loading, processing, visualization, and basic machine learning using the Python programming language, the Pandas data analytics and sci-kit learn machine learning libraries, and the web-based Colaboratory environment. In addition, the course will provide numerous learning paths for various built environment-related tasks to facilitate further growth.
- Keywords:
- City planning -- Statistical methods Python (Computer program language) Information visualization
- Resource Type:
- MOOC
-
MOOC
In this course, we will introduce you to the fundamentals of sensor fusion for automotive systems. Key concepts involve Bayesian statistics and how to recursively estimate parameters of interest using a range of different sensors. The course is designed for students who seek to gain a solid understanding of Bayesian statistics and how to use it to fuse information from different sensors. We emphasize object positioning problems, but the studied techniques are applicable much more generally. The course contains a series of videos, quizzes and hand-on assignments where you get to implement many of the key techniques and build your own sensor fusion toolbox. The course is self-contained, but we highly recommend that you also take the course ChM015x: Multi-target Tracking for Automotive Systems. Together, these courses give you an excellent foundation to tackle advanced problems related to perceiving the traffic situation around an autonomous vehicle using observations from a variety of different sensors, such as, radar, lidar and camera.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Automobiles -- Electronic equipment Automotive sensors
- Resource Type:
- MOOC