Jefferson Rodríguez

Jefferson Rodríguez

Academic profile

Certificates

Deep Learning by deeplearning.ai on coursera Permalink

The Deep Learning Specialization is designed to prepare learners to participate in the development of cutting-edge AI technology, and to understand the capability, the challenges, and the consequences of the rise of deep learning. Through five interconnected courses, learners develop a profound knowledge of the hottest AI algorithms, mastering deep learning from its foundations (neural networks) to its industry applications (Computer Vision, Natural Language Processing, Speech Recognition, etc.).

TensorFlow Developer by deeplearning.ai on coursera Permalink

In this specialization, you got a grounding in what you need to get started with TensorFlow: In Practice. The goal was to help you take the next steps, such as going deeper into understanding Machine Learning and the practice of understanding loss functions, optimizers and more, or perhaps you want to know more about neural networks and the different types of layers, from convolutions to recurrent or LSTM. Now that you have used some of them and seen the impact of different layer types in practice, you can go forward equipped to go deeper!

Huawei certification HCIA-AI Permalink

This certification is jointly launched by Huawei and Chongqing University of Posts and Telecommunications, and Dalian University of Technology，matching the HCIA-AI V3.0（Released on September 17, 2020). Through this course, you will systematically understand the AI development history, the Huawei Ascend AI system, the full-stack all-scenario AI strategy， and the algorithms related to traditional machine learning and deep learning; TensorFlow and MindSpore.

TensorFlow: Data and Deployment by deeplearning.ai on coursera Permalink

In this specialization, you continued to develop your understanding of machine learning with TensorFlow: Data and Deployment. You have gone beyond basic modeling and learned how to train and run your models within a browser, optimize machine learning models for mobile devices, and create effective data pipelines with TensorFlow Data Services. Now that you’ve learned the various ways to deploy your models, you’re well-prepared to take your models into the hands of real people on all kinds of devices!