Stanford University

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Unsupervised Learning, Recommenders, Reinforcement Learning (Coursera)

Dec 5th 2022
Unsupervised Learning, Recommenders, Reinforcement Learning (Coursera)
Course Auditing
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In the third course of the Machine Learning Specialization, you will: Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection; Build recommender systems with a collaborative filtering approach and a content-based deep learning method; Build a deep reinforcement learning [...]

Supervised Machine Learning: Regression and Classification (Coursera)

Dec 5th 2022
Supervised Machine Learning: Regression and Classification (Coursera)
Course Auditing
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In the first course of the Machine Learning Specialization, you will: build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn; build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic [...]

Advanced Learning Algorithms (Coursera)

Dec 5th 2022
Advanced Learning Algorithms (Coursera)
Course Auditing
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In the second course of the Machine Learning Specialization, you will: build and train a neural network with TensorFlow to perform multi-class classification; apply best practices for machine learning development so that your models generalize to data and tasks in the real world; build and use decision trees and [...]

Formação sobre a COVID-19 para Profissionais de Saúde (Coursera)

Dec 5th 2022
Formação sobre a COVID-19 para Profissionais de Saúde (Coursera)
Free Course
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Effort
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A COVID-19 está se espalhando rapidamente pelo mundo e todos os profissionais de saúde devem estar preparados para reconhecer, estabilizar e tratar pacientes infectados com o novo coronavírus. Após a conclusão deste curso de curta duração, médicos, enfermeiras e outros profissionais de saúde terão uma abordagem unificada e [...]

Introduction to Statistics (Coursera)

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You [...]

AI in Healthcare Capstone (Coursera)

Dec 5th 2022
AI in Healthcare Capstone (Coursera)
Course Auditing
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This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a [...]

How Technology is Shaping Democracy and the 2020 Election (Coursera)

Democracy can only thrive with the participation of well-informed citizens. The 2020 U.S. presidential election will be historic for many reasons and all parties are leveraging the power of technology to both influence and mobilize voters. More than ever, digital tools and platforms are shaping the opinions and behaviors [...]

Introduction to Clinical Data (Coursera)

This course introduces you to a framework for successful and ethical medical data mining. We will explore the variety of clinical data collected during the delivery of healthcare. You will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. We will also explore issues of [...]

Writing in the Sciences (Coursera)

This course teaches scientists to become more effective writers, using practical examples and exercises. Topics include: principles of good writing, tricks for writing faster and with less anxiety, the format of a scientific manuscript, peer review, grant writing, ethical issues in scientific publication, and writing for general [...]

Shortest Paths Revisited, NP-Complete Problems and What To Do About Them (Coursera)

The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).