为商业智能洞察在结构化和非结构化数据上部署Python数据科学模型
你会学到什么
了解在谷歌Colab中实现Python数据科学框架的主要方面
学习从不同来源获取非结构化和结构化数据,包括推特、SQL数据库和免费提供的金融数据
创建强大的数据可视化,以理解您的数据并展示您的发现
实施无监督学习算法,从现实生活中的商业和金融数据集(如与股票市场表现相关的数据集)中获取见解
实施常用的统计技术来提取有价值的见解和回答问题
实现强大的机器学习算法来构建预测模型
使用通用自然语言处理(NLP)技术来了解您的客户在亚马逊评论中真正在说什么
流派:电子学习| MP4 |视频:h264,1280×720 |音频:AAC,44.1 KHz
语言:英语+中英文字幕(云桥CG资源站 机译)|大小解压后:2.85 GB |时长:5h 55m
描述
报名参加我的最新课程,学习如何用PYTHON实现商业智能
您是否有兴趣利用结构化和非结构化数据为业务决策提供信息?
你想做数据驱动的财务决策吗?
您是否希望将社交媒体帖子、文章和网页中的非结构化数据转化为真正的见解?
您是否希望开发前沿分析和可视化来支持业务决策?
您是否有兴趣部署预测建模和预测方法以在竞争中取得优势?
如果您能够将Python数据分析技能应用于实用商业智能(BI),那么您就可以获得超越其他数据科学家的优势
通过从常用的结构化和非结构化业务数据中提取可操作的见解来提升公司或业务的价值
通过精通商业智能应用程序最重要的支柱,从其他数据分析师中脱颖而出
我的课程是与实际业务相关问题的实践培训-您将学习使用重要的Python数据科学技术从结构化数据(如从数据库获得的数据)和非结构化文本数据中获取信息和见解
我的课程为使用Python执行实际的、真实的商业智能任务提供了基础。通过参加本课程,您在数据科学之旅中向前迈出了重要的一步,成为了部署Python数据科学技术以回答实际业务问题的专家(例如,什么样的客户注册了长期电话计划?).
你为什么要上我的课?
我拥有英国牛津大学的地理与环境硕士学位。我还在剑桥大学完成了数据科学博士学位(热带生态和保护)。
我在分析来自不同来源的真实数据和为国际同行评审期刊制作出版物方面有几年的经验。
本课程将帮助您使用名为GoogleColab的强大的基于云的python环境,流畅地部署基于数据科学的BI解决方案。具体来说,你会
了解在谷歌Colab中实现Python数据科学框架的主要方面
学习从不同来源获取非结构化和结构化数据,包括推特、SQL数据库和免费提供的金融数据
实施无监督学习算法,从现实生活中的商业和金融数据集(如与股票市场表现相关的数据集)中获取见解
实施常见的统计技术来提取有价值的见解,并回答一些问题,例如哪些客户可能会签署长期电话计划,或者Airbnb租赁在澳大利亚不同城市有何不同。
实现强大的机器学习算法来构建预测模型
执行常见的分析和可视化任务
使用通用自然语言处理(NLP)技术来了解您的客户在亚马逊评论中真正在说什么
你将进行实际的小型案例研究,涉及(a)澳大利亚的Airbnb租赁(b)纳斯达克上市的主要公司的股票价格数据(c)电话公司的客户移交(d)亚马逊评论的文本数据
除了以上所有内容,您还将获得我的持续支持,以确保您从投资中获得最大价值!
立即注册
这门课是给谁的
人们想要掌握数据科学的Python/Google Colab环境
对将Python数据科学技术应用于商业智能问题感兴趣的人
对开发强大的数据可视化感兴趣的学生
希望从结构化和非结构化数据中获得业务相关见解的学生
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.70 GB | Duration: 5h 55m
Deploy Python Data Science Models On Structured and Unstructured Data For BI Insights
What you’ll learn
Learn the main aspects of implementing a Python data science framework within Google Colab
Learn to obtain both unstructured and structured data from different sources including Twitter, SQL databases and freely available financial data
Create powerful data visualisations to both understand your data and present your findings
Implemented unsupervised learning algorithms to obtain insights from real-life business and financial datasets such as those related to stock market performan
Implement common statistical techniques to extract valuable insights and answer questions
Implement powerful machine learning algorithms to build predictive and forecasting models
Use common natural language processing (NLP) techniques to learn what your customers are really saying in their Amazon reviews
Description
ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT CARRYING OUT BUSINESS INTELLIGENCE WITH PYTHON
Are you interested in harnessing the power of structured and unstructured data for informing business decisions?
Do you want to make data-driven financial decisions?
Do you want to turn unstructured data from social media posts, articles and web pages into real insights?
Do you want to develop cutting edge analytics and visualisations to support business decisions?
Are you interested in deploying predictive modelling and forecasting methods to get an edge over the competition?
You Can Gain An Edge Over Other Data Scientists If You Can Apply Python Data Analysis Skills For Practical Business Intelligence (BI)
By enhancing the value of your company or business through the extraction of actionable insights from commonly used structured and unstructured business data
Stand out from a pool of other data analysts by gaining proficiency in the most important pillars of BI applications
MY COURSE IS A HANDS-ON TRAINING WITH REAL BUSINESS RELATED PROBLEMS- You will learn to use important Python data science techniques to derive information and insights from both structured data (such as those obtained from databases) and unstructured text data
My course provides a foundation to carry out PRACTICAL, real-life BI tasks using Python. By taking this course, you are taking an important step forward in your data science journey to become an expert in deploying Python data science techniques for answering practical business questions (e.g. what kind of customers sign up for a long-term phone plan?).
Why Should You Take My Course?
I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a data science intense PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real-life data from different sources and producing publications for international peer-reviewed journals.
This course will help you gain fluency in deploying data science-based BI solutions using a powerful clouded based python environment called GoogleColab. Specifically, you will
Learn the main aspects of implementing a Python data science framework within Google Colab
Learn to obtain both unstructured and structured data from different sources including Twitter, SQL databases and freely available financial data
Implemented unsupervised learning algorithms to obtain insights from real-life business and financial datasets such as those related to stock market performance
Implement common statistical techniques to extract valuable insights and answer questions such as which customers are likely to sign up for a long-term phone plan or how do Airbnb rentals vary across the different cities in Australia.
Implement powerful machine learning algorithms to build predictive and forecasting models
Carry out common analytics and visualization tasks
Use common natural language processing (NLP) techniques to learn what your customers are really saying in their Amazon reviews
You will work on practical mini case studies relating to (a) Airbnb rentals in Australia (b) stock price data relating to the major companies listed on the Nasdaq (c) phone company customer turn over (d) textual data of Amazon reviews
In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!
ENROLL NOW 🙂
Who this course is for
People Wanting To Master The Python/Google Colab Environment For Data Science
People Interested in Applying Python Data Science Techniques For BI Problems
Students Interested In Developing Powerful Data Visualisations
Students Wanting To Derive Business Relevant Insights From Structured and Unstructured Data
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