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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-drug-designing-with-python-and-ai/
课程评论：没有评论
**课程名称：SageMaker ML Development** **课程概述：** 本课程专为生命科学背景但希望进入药物设计领域的学习者设计。通过该课程，您将学会使用Python和人工智能（AI）在Google Colab这一用户友好的环境中运行专业的脚本和代码。课程提供免费的定制化Notebooks，指导您一步步掌握药物设计的复杂流程。完成课程后，您将能够识别、获取和筛选数据，定义和编译自己的人工神经网络（ANN）模型，并将其应用于数据的拟合和评估。最终，您将能够预测数据集中未知化合物的pIC50。 课程还将介绍专门为处理不同复杂度的项目而设计的Google Colab Notebooks。讲师保证，学员将掌握多项实用技能，能够处理各类化合物数据，并进行创新。 **核心内容：** * Python和AI在药物设计中的应用 * 在Google Colab中运行专业脚本和代码 * 使用定制化Notebooks进行药物设计流程 * 数据识别、获取与筛选 * 定义、编译ANN模型，并进行数据拟合与评估 * 预测未知化合物的pIC50 **目标学员：** * 生命科学背景，希望学习药物设计的专业人士 * 对Python和AI在科学研究中的应用感兴趣的学习者
Are you from a life sciences background and eager to dive into the world of drug design? Our comprehensive course, "Master Drug Designing with Python and AI," is tailor-made for you.Unlock the potential of Python and artificial intelligence as you learn to run professional scripts and codes effortlessly in the user-friendly environment of Google Colab. This course provides free access to specialized, custom-designed notebooks that will guide you step-by-step through the intricacies of drug design. Upon completion, you will be able to identify, fetch, and filter your data. In addition to a basic introduction, you will also be able to define and compile your own ANN model and use it for fitting and evaluation on your data. Finally, this course will enable you to predict pIC50 for the unknown compounds present in your dataset.Besides learning the tricks, I will introduce you to the tailor-made Google Colab notebooks specifically written to handle projects ranging from simple to complex. I gurantee you that after taking this course you will take much more things as skills, and can treat variety of compounds data.Join us and transform your expertise in life sciences into cutting-edge skills in drug discovery and development. Let's innovate together!
