Full Course on TensorRT, ONNX for Development and Profuction Course includes 18 hrs video content and enrolled by 500+ students and received a 4.4 average review out of 5. Now, you will get 90%OFF on the original price of the course and discount price differs from country to country, and the course provider offers 30-days money-back guarantee! If you are not satisfied in any way, you’ll get your money back.
Full Complete TensorRT Vs ONNX Course. Get Hired with Advance Unique Knowledge – By PhD Researcher AI & Robotics Scientist Fikrat Gasimov
What you’ll learn
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1. What is Docker and How to use Docker & their practical usage
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2. What is Kubernet and How to use with Docker & their practical usage
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3. Nvidia SuperComputer and Cuda Programming Language & their practical usage
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4. What are OpenCL and OpenGL and when to use & their practical usage
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6.(LAB) Tensorflow/TF2 and Pytorch Installation, Configuration with DOCKER
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7. (LAB)DockerFile, Docker Compile and Docker Compose Debug file configuration
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8. (LAB)Different YOLO version, comparisons, and when to use which version of YOLO according to your problem
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9. (LAB)Jupyter Notebook Editor as well as Visual Studio Coding Skills
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10. (LAB) Visual Studio Code Setup and Docker Debugger with VS
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11. (LAB) what is ONNX fframework and how to use apply onnx to your custom problems
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11. (LAB) What is TensorRT Framework and how to use apply to your custom problems
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12. (LAB) Custom Detection, Classification, Segmentation problems and inference on images and videos
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13. (LAB) Python3 Object Oriented Programming
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14.(LAB)Pycuda Language programming
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15. (LAB) Deep Learning Problem Solving Skills on Edge Devices, and Cloud Computings
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16. (LAB) How to generate High Performance Inference Models , in order to get high precision, FPS detection as well as less gpu memory consumption
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17. (LAB) Visual Studio Code with Docker
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18.(LAB Challenge) yolov4 onnx inference with opencv dnn
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19.(LAB Challenge) yolov5 onnx inference with opencv dnn
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20.(LAB Challenge) yolov5 onnx inference with Opencv DNN
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21.(LAB Challenge) yolov5 onnx inference with TensorRT and Pycuda
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22.(LAB) ResNet Image Classificiation with TensorRT and Pycuda
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23.(LAB) yolov5 onnx inference on Video Frames with TensorRT and Pycuda
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24. (LAB) Prepare Yourself for Python Object Oriented Programming Inference!
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25. (LAB) Python OOP Inheritance Based on YOLOV7 Object Detection
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26. Deep Theoretical Knowledge about Small Target Detection and Image Masking
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27. Deep Insight on Yolov5/Yolov6/Yolov7/Yolov8 Architectures and Practical Use Cases
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28. Deep Insight on YoloV5 P5 and P6 Models & Their Practical Usage
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29. Key Differences:Explicit vs. Implicit Batch Size
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30. (Theory) TenSorRT Optimization Profile Tutorial
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31. (Theory) Boost TensorRT Knowledge for Beginner Level Quizzies
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32. (Theory Challenge) Boost TensorRT Knowledge for Intermediate Level Quizzies
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33. Theory Challenge) Boost TensorRT Knowledge for Advance Level Quizzies
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34.(Theory Challenge) Boost Cuda Runtime for Beginner/Intermediate/Advance practical & theorytical Quizzies
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35.(Theory Challenge) Boost your OpenCV-ONNX Knowledge by doing Mixed practical & theorytical Quizzies
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36.(Deep Theoratical Knowledge) YoloV8 ONNX Model Input and Output Inference
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37.(Deep Theoratical Knowledge) YoloV8 Model usage and applied sectors.
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38.(Deep Practical Knowledge) YoloV8 ONNX Model for Detection and Segmentation
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39.(Bonus Lecture) Mastering Deep Reinforcement Learning with Advance Exercises
Can I download Full Course on TensorRT, ONNX for Development and Profuction course?
Course videos can be downloaded for offline viewing using the Udemy mobile app on Android and iOS. Some courses may allow downloading lectures on a computer only if the instructor has enabled it, but this is not guaranteed and is not the primary method Udemy supports.Can I get a certificate after completing the course?
Yes. After successful completion of the Full Course on TensorRT, ONNX for Development and Profuction, learners will receive a certificate of completion. The certificate confirms that the course has been completed and can be downloaded and shared on resumes or professional profiles.Are there any other coupons available for this course?
Additional coupons for this course may be available from time to time. Coupon availability is time-limited and may change or expire at any time, so it’s recommended to check regularly for updated offers.Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
