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所在平台: Coursera专项课程 |
课程主页: https://www.coursera.org/specializations/artificial-intelligence-scientific-research
课程评论：没有评论
课程名称：AI与科学研究 课程概述： 在此课程中，您将学习如何在科学情境中运用人工智能，发现数据集中的趋势和模式。该课程内容涵盖完整的机器学习流程，包括如何使用人工智能预测数据集中的序列，以及利用人工智能技术在Python中测试假设。您将获得的数据科学、人工神经网络、人工智能、机器学习、随机森林、回归分析、统计假设检验、医学数据处理、Python编程、主成分分析和物种识别等技能。 课程结构： 本课程分为四个部分。第一部分将介绍与数据科学相关的Python语言及一些现有的分析库，您将应用分类模型来预测患者健康数据中心脏病的存在与否。第二部分则涵盖从数据的读取、清理与转换到进行基本和高级机器学习算法的完整机器学习流程。最终项目中，您将比较不同的机器学习模型。在第三部分，我们将基于基本模型的知识，深入探索更高级的人工智能技术，并通过使用随机森林完成健康患者之间相似性的预测项目。第四部分为总结项目课程，将比较COVID-19突变的基因组序列，以识别药物疗法的潜在靶点，帮助您在基因组测序中找到对抗疾病的方法。 应用学习项目： 每门课程均包含基于Coursera实验室平台的实践实验，利用提供的库和模型，进行机器学习与AI指令的实践，回答数据集中重要问题。最后的课程项目将比较COVID-19突变的基因组序列，以识别药物疗法的潜在目标区域。 证书： 完成课程后，获得可共享证书。课程100%在线，您可以随时开始并按自己的进度学习，灵活设置和维持截止日期。 适合人群： 本课程为初学者级别，不要求特定背景，但了解科学方法、数学和一般计算机逻辑将大有裨益。预计完成时间为4个月，建议每周学习3小时。 适用语言： 课程语言为英语，提供英语字幕。
Course Link: https://www.coursera.org/learn/data-science-and-scikit-learn-in-python
Name:Introduction to Data Science and scikit-learn in Python
Description:Offered by LearnQuest. This course will teach you how to leverage the power of Python and artificial intelligence to create and test ... Enroll for free.
Course Link: https://www.coursera.org/learn/machine-learning-models-in-science
Name:Machine Learning Models in Science
Description:Offered by LearnQuest. This course is aimed at anyone interested in applying machine learning techniques to scientific problems. In this ... Enroll for free.
Course Link: https://www.coursera.org/learn/neural-networks-random-forests
Name:Neural Networks and Random Forests
Description:Offered by LearnQuest. In this course, we will build on our knowledge of basic models and explore advanced AI techniques. We’ll start with a ... Enroll for free.
Course Link: https://www.coursera.org/learn/ai-for-drug-discovery
Name:Capstone Project: Advanced AI for Drug Discovery
Description:Offered by LearnQuest. In this capstone project course, we'll compare genome sequences of COVID-19 mutations to identify potential areas a ... Enroll for free.
What you will learn
How to use AI in scientific situations to discover trends and patterns within datasets
The complete machine learning process
Use artificial intelligence to predict sequences in datasets
Employ artificial intelligence techniques to test hypothesis in Python
Skills you will gain
Data Science
Artificial Neural Network
Artificial Intelligence (AI)
Machine Learning
Random Forest
regression
Statistical Hypothesis Testing
medical data
Python Programming
PCA
identifying specieis
predictions in science
About this Specialization
In the AI for Scientific Research specialization, we'll learn how to use AI in scientific situations to discover trends and patterns within datasets. Course 1 teaches a little bit about the Python language as it relates to data science. We'll share some existing libraries to help analyze your datasets. By the end of the course, you'll apply a classification model to predict the presence or absence of heart disease from a patient's health data. Course 2 covers the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms.In the final project, we'll apply our skills to compare different machine learning models in Python. In Course 3, we will build on our knowledge of basic models and explore more advanced AI techniques. We’ll describe the differences between the two techniques and explore how they differ. Then, we’ll complete a project predicting similarity between health patients using random forests. In Course 4, a capstone project course, we'll compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target. By the end, you'll be well on your way to discovering ways to combat disease with genome sequencing.
Applied Learning Project
Each course in this specialization contains practice labs built on the Coursera lab platform. You will use the provided libraries and models to perform machine learning and AI instructions that help answer important questions in your dataset. The final course is a capstone project where you will compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target. It begins with the basic setup and walks through the entire analysis process.
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
There are no specific background requirements; however, it is very helpful to understand scientific methods, mathematics and general computer logic.
Hours to complete
Approximately 4 months to complete
Suggested pace of 3 hours/week
Available languages
English
Subtitles: English
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
There are no specific background requirements; however, it is very helpful to understand scientific methods, mathematics and general computer logic.
Hours to complete
Approximately 4 months to complete
Suggested pace of 3 hours/week
Available languages
English
Subtitles: English
