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所在平台: Udemy |
课程主页: https://www.udemy.com/course/full-stack-data-science-machine-learning-bootcamp-course/
课程评论:没有评论
课程名称:全栈数据科学与机器学习训练营课程 课程概述:欢迎参加全栈数据科学与机器学习训练营课程,这是您学习数据科学基础技能和进入数据科学领域所需的唯一课程。该Python课程超过40小时,毫无疑问是最全面的数据科学和机器学习在线课程。即使您没有任何编程经验,本课程也将带您从初学者进阶至精通。 课程由印度领先的编程训练营的首席讲师授课,您将学习谷歌、亚马逊或Netflix等数据科学家使用的最新工具和技术。课程内容经过三年的行业专家、研究人员及学生反馈的共同开发,确保不打折扣,配有精彩的动画视频解释和真实世界项目。 到目前为止,讲师已经教授了超过10000名学生编码,许多人已通过此课程改变了生活,获得工作或创办了自己的科技公司。您报名可节省超过12000美元,但将获得与现场编程训练营相同的教学材料及教学课程。 课程通过视频教程逐步引导您,教授成为数据科学家和机器学习专业人士所需的所有知识,包括超过40小时的高清录像教程,让您在解决真实世界问题时提升编程技能。课程覆盖多个重要的数据科学和机器学习主题,如: - 机器学习:线性回归、SVR、决策树、随机森林;聚类:K均值、层次聚类算法;分类:逻辑回归、核SVM、朴素贝叶斯等。 - 自然语言处理:基于词袋的模型及相关算法。 - 深度学习:人工神经网络、卷积神经网络、递归神经网络、长短时记忆网络等。 - Python编程:数据类型和变量、字符串操作、函数、对象、列表、元组和字典、循环与迭代器、条件与控制流等。 - Power BI:导入CSV和Excel文件、查询合并、数据模型关系创建、DAX函数使用等。 此外,课程包含众多实践练习,基于真实案例,不仅讲授理论,更加重视动手实践,让您独立构建模型。课程结束后,您将流利地使用Python编程,能够应对任何数据科学项目。 快来注册吧,期待您的参与!您将获得178+个高清录像讲座、30+个编码挑战和实践、完整的数据科学与机器学习项目,以及我们的畅销电子书《学习编码的12条法则》等丰富资源。
Welcome to the Full Stack Data Science & Machine Learning BootCamp Course, the only course you need to learn Foundation skills and get into data science.At over 40+ hours, this Python course is without a doubt the most comprehensive data science and machine learning course available online. Even if you have zero programming experience, this course will take you from beginner to mastery. Here's why:The course is taught by the lead instructor at the PwC, India's leading in-person programming bootcamp.In the course, you'll be learning the latest tools and technologies that are used by data scientists at Google, Amazon, or Netflix.This course doesn't cut any corners, there are beautiful animated explanation videos and real-world projects to build.The curriculum was developed over a period of three years together with industry professionals, researchers and student testing and feedback.To date, I've taught over 10000+ students how to code and many have gone on to change their lives by getting jobs in the industry or starting their own tech startup.You'll save yourself over $12,000 by enrolling, but get access to the same teaching materials and learn from the same instructor and curriculum as our in-person programming bootcamp.We'll take you step-by-step through video tutorials and teach you everything you need to know to succeed as a data scientist and machine learning professional.The course includes over 40+ hours of HD video tutorials and builds your programming knowledge while solving real-world problems.In the curriculum, we cover a large number of important data science and machine learning topics, such as:MACHINE LEARNING - Regression: Simple Linear Regression, , SVR, Decision Tree , Random Forest,Clustering: K-Means, Hierarchical Clustering AlgorithmsClassification: Logistic Regression, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest ClassificationNatural Language Processing: Bag-of-words model and algorithms for NLPDEEP LEARNING -Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Long short term Memory, Vgg16 , Transfer learning, Web Based Flask Application.Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.By the end of this course, you will be fluently programming in Python and be ready to tackle any data science project. We'll be covering all of these Python programming concepts:PYTHON - Data Types and VariablesString ManipulationFunctionsObjectsLists, Tuples and DictionariesLoops and IteratorsConditionals and Control FlowGenerator FunctionsContext Managers and Name ScopingError HandlingPower BI -What is Power BI and why you should be using it.To import CSV and Excel files into Power BI Desktop.How to use Merge Queries to fetch data from other queries.How to create relationships between the different tables of the data model.All about DAX including using the COUTROWS, CALCULATE, and SAMEPERIODLASTYEAR functions.All about using the card visual to create summary information.How to use other visuals such as clustered column charts, maps, and trend graphs.How to use Slicers to filter your reports.How to use themes to format your reports quickly and consistently.How to edit the interactions between your visualizations and filter at visualization, page, and report level.By working through real-world projects you get to understand the entire workflow of a data scientist which is incredibly valuable to a potential employer.Sign up today, and look forward to:178+ HD Video Lectures30+ Code Challenges and ExercisesFully Fledged Data Science and Machine Learning ProjectsProgramming Resources and CheatsheetsOur best selling 12 Rules to Learn to Code eBook$12,000+ data science & machine learning bootcamp course materials and curriculum