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 BOOTCAMP for TensorRT-ONNX 12+ projects and Python course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The BOOTCAMP for TensorRT-ONNX 12+ projects and Python course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.com
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