Nothing is impossible. As a novice starting out in the field of technology, I believe this phrase embodies the spirit and enthusiasm of youth. I always find inspiration in my work and enjoy facing challenges. My passion for learning and keeping up with new technologies will always be my top priority. With the desire to become an AI engineer and in the future, evolve into machine learning operations, I strive to improve myself daily through studying, practising, and accessing new knowledge. All in all, with regards to my career, I think that I need a good environment to demonstrate my abilities and hope to find good colleagues to accompany me in the future.Fundamental knowledge of Machine Learning: Supervised/Unsupervised Learning, Cost function, Gradient Descent, Overfitting, Regularization, Cross Validation, ... Basic Machine Learning methods: Linear Regression, Logistic Regression, K Nearest Neighbors, Neural Network, Backpropagation, SVM, …Knowledge about popular CNN (Convolutional Neural Network) architectures: VGG, Inception, ResNet, MobileNet, DenseNet.Object detection, image segmentation models: YOLO, U-Net, U2Net, Deeplabv3.In machine learning operations, managing the lifecycle of a machine learning system, I have become familiar with libraries such as MLFlow, AirFlow, detecting data drift, and concept drift. In addition, I have knowledge of Docker for packaging and deploying systems easily when transitioning to new environments.