本地，有教师指导的实时数据分析（数据分析或数据分析）培训课程通过讨论和实践操作来演示用于执行数据分析的编程语言和方法。数据分析培训可作为“现场实况培训”或“远程实时培训”。现场实地培训可在当地客户现场进行中国或者在NobleProg公司的培训中心中国 。远程实时培训通过交互式远程桌面进行。 NobleProg您当地的培训提供商。
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客户评论
学员的联系方式。这种方法对团队和个人都有好处。
Marcin Szcześniak - Credit Agricole Bank P
课程: BPMN 2.0 dla Analityków Biznesowych
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大量的运动。 Ku
Piotr Kubiński
课程: BPMN 2.0 dla Analityków Biznesowych
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我喜欢练习和学习Python的角落和缝隙
Connor Brierley-Green
课程: Python Programming
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乔伊对编程充满热情。他非常擅长动态适应我们的需求和兴趣。
Randy Enkin
课程: Python Programming
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许多例子让我很容易理解。
Lingmin Cao
课程: Python Programming
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最终测试模拟考试题，我们根据培训期间所获得的知识作为一个团队来解决任务。
Dominik Łubiński
课程: Business Analysis, BABOK V3.0 and IIBA Certification Preparation
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我大多喜欢培训师的知识。
Sripal S
课程: Understanding Business Process Modeling with BPMN 2.0
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我一般都喜欢发表演讲的方式。
Bhaskar naidu
课程: Understanding Business Process Modeling with BPMN 2.0
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对我们所有问题的指导的全面知识给我的期望提供了答案......讲师进行了很好的讨论......他并不缺乏耐心......
Łukasz Matulewicz
课程: Programowanie w języku Python
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对讲师的丰富知识，工具的多样性以及对该主题的实用方法。
Magdalena Stupak
课程: Programowanie w języku Python
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对培训师很了解，如何翻译。
Renata Cylejowska
课程: Programowanie w języku Python
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认真对待定制的事实。
jurgen linsen
课程: Python Programming
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我真的很喜欢教练的帮助。
Urszula Kuza
课程: Tableau Advanced
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所有
Grześ
课程: BPMN 2.0 dla Analityków Biznesowych
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实际例子。 Przemy
Przemysław Domański
课程: BPMN 2.0 dla Analityków Biznesowych
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我在所有问题上得到答案..
Natalia Gladii
课程: Data Analytics With R
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我对流程编辑器，业务规则和BPM S工具环境有了很好的了解。我强烈推荐实用的BPM N for Business Analysts课程，即使是经验丰富的分析师，凭借其出色的流程场景和建模实践，它将为您提供优于其他人的优势！
Anees Baig
课程: BPMN 2.0 for Business Analysts
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非常翔实，并提供了一个很好的课程大纲总结。
Matthew Steptoe
课程: Contemporary Development Principles and Practices
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我很享受第一天的所有活动。
Peter Mahaffey
课程: Contemporary Development Principles and Practices
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事实上，我们已经为特定问题准备好了解决方案+展示了广泛的应用程序+通过了知识汇编。 。
Wojciech Michalak
课程: Power BI
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我喜欢练习，因为这是通过重复学习的唯一方法。
David Rushe
课程: Tableau Advanced
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培训师的知识非常丰富，他可以传达知识。它涉及参与者互动并解决遇到的问题。
Nina Rokita
课程: Power BI
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培训师一直与培训的接受者保持联系，根据我们的需求调整步伐，并持续解决我们的问题并回答我们的问题。
Dominika Jaworska
课程: Power BI
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我喜欢练习，训练室，茶厨房。
Alisher Khaydarov
课程: BPMN 2 Fundamentals and Workshop
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速度和进展非常适合快速理解事物。
Stephen Brewell
课程: BPMN 2.0 for Business Analysts
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给出的例子确实帮助我理解了一些概念。培训师确保我们遵循整个培训，并毫不犹豫地回到之前的任何疑点。培训师根据我们的需求调整培训，重点关注我们希望获得更多细节的项目。实践练习也很好。
Amanda Moscardini - Campinas Valley
课程: Understanding Business Process Modeling with BPMN 2.0
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黛布拉确保理解我的问题并准确回答。关于如何在特定条件下设计图表的建议非常好。我想强调Debra与我们合作的专业和高效。
Leandro Antonio
课程: Understanding Business Process Modeling with BPMN 2.0
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培训非常一致，我了解了该计划的许多有趣功能。
Anna Klimczak
课程: Power BI
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做好充分准备，练习练习和老师的知识。
Sandra Przewdzing
课程: Power BI
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我喜欢做的练习。
Nour Assaf
课程: Data Mining and Analysis
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动手练习和培训师能够用简单的术语解释复杂的主题。
youssef chamoun
课程: Data Mining and Analysis
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所提供的信息很有意思，最好的部分是在我们从Durex获得数据并且处理我们熟悉的数据并执行操作以获得结果时。
Jessica Chaar
课程: Data Mining and Analysis
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我喜欢乐于助人且非常善良。
Natalia Machrowicz
课程: Python Programming
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我们做了实践练习（我们编写的脚本可以用于我们的日常工作）。它使课程非常有趣。我也喜欢教练分享他的知识的方式。他以一种非常容易接近的方式做到了。
Malwina Sawa
课程: Python Programming
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我认为这些信息很有趣。
Allison May
课程: Data Visualization
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我非常感谢Jeff使用了适用于教育数据的数据和示例。他使它变得有趣和互动。
Carol Wells Bazzichi
课程: Data Visualization
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了解所有图表类型及其用途。学习混乱的价值。了解显示时间数据的方法。
Susan Williams
课程: Data Visualization
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培训师很热情。
Diane Lucas
课程: Data Visualization
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我真的很喜欢内容/讲师。
Craig Roberson
课程: Data Visualization
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我是一名实践学习者，这是他做了很多的事情。
Lisa Comfort
课程: Data Visualization
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我喜欢这些例子。
Peter Coleman
课程: Data Visualization
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我通常从这些例子中受益。
Peter Coleman
课程: Data Visualization
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我喜欢现实世界的好例子，对现有报道的评论。
Ronald Parrish
课程: Data Visualization
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我喜欢Birol定制培训的一些部分，以满足我作为Business分析师的角色。通过这种方式，他能够专注于重要的主题，而不是关注我在工作中通常不会使用的主题。他教的很清楚，并确保你在进入下一个之前理解一个主题。你可以说他是一位经验丰富的教授，对自己的学科知识渊博，并且知道如何分析学生的培训需求，以有效地涵盖必要和相关的主题。这使得他的会话非常有效，因为它灵活且正确。他的材料非常全面，他指出要遵循课程，但要使其与学生更相关。我很欣赏他了解行业标准，并能够提供他的见解。我从来没有像在2天课程中那样学到太多东西，值得花时间和精力。培训确实加快了我对BPM N 2.0的学习，并给了我在工作中开始练习该技术的基础和信心。感谢Birol和NobleProg的精彩学习经历我一定会向未来的同事推荐这门课程和培训师。
Irma Irosido
课程: BPMN 2.0 for Business Analysts
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我真的受益于培训师愿意分享更多。
Balaram Chandra Paul
课程: A practical introduction to Data Analysis and Big Data
Machine Translated
记住/重复关键主题的非常好的方法。非常好的“热身”练习。
课程: Python Programming
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*愉快的练习。 *快速进入更高级的主题。 *培训师很友好，很容易上手。 *根据团队需求定制课程。
Matthew Lucas
课程: Python Programming
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我真的受益于交互性和专门的培训师。
Pierre Bruwier
课程: BPMN 2 Fundamentals and Workshop
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教练有很多轶事，可以在简单的生活讲座上展示内容。
Katarzyna Gołda
课程: Business Analysis
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Bogdan先生是一位出色的专家，他知道如何以一种无障碍的方式传递知识。他了解并注意观众“关闭”时
Unit4 Polska sp. z o.o; ALTEN Polska Sp. z o.o.; UBS; Zerochaos Sp. z o.o.
课程: Business Analysis
Machine Translated
记住/重复关键主题的非常好的方法。非常好的“热身”练习。
课程: Python Programming
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数据分析课程大纲
课程名称
课程时长
课程概览
课程名称
课程时长
课程概览
21小时
课程概览
This course has been created for business analysts who want to use BPMN 2.0 extensively in their projects.
It focuses on practical aspects of all BPMN 2.0 specification as well as implementations of common patterns.
It is a series of short lectures followed by exercises: the delegates will have a problem described in English, and will have to create a proper diagram for each problem. After that, the diagrams will be discussed and assessed by the group and the trainer.
This course doesn't cover execution part of BPMN, it focuses on analysis and process design aspects of BPMN 2.0.
It focuses on practical aspects of all BPMN 2.0 specification as well as implementations of common patterns.
It is a series of short lectures followed by exercises: the delegates will have a problem described in English, and will have to create a proper diagram for each problem. After that, the diagrams will be discussed and assessed by the group and the trainer.
This course doesn't cover execution part of BPMN, it focuses on analysis and process design aspects of BPMN 2.0.
14小时
课程概览
Audience
Analysts, researchers, scientists, graduates and students and anyone who is interested in learning how to facilitate statistical analysis in Microsoft Excel.
Course Objectives
This course will help improve your familiarity with Excel and statistics and as a result increase the effectiveness and efficiency of your work or research.
This course describes how to use the Analysis ToolPack in Microsoft Excel, statistical functions and how to perform basic statistical procedures. It will explain what Excel limitation are and how to overcome them.
Analysts, researchers, scientists, graduates and students and anyone who is interested in learning how to facilitate statistical analysis in Microsoft Excel.
Course Objectives
This course will help improve your familiarity with Excel and statistics and as a result increase the effectiveness and efficiency of your work or research.
This course describes how to use the Analysis ToolPack in Microsoft Excel, statistical functions and how to perform basic statistical procedures. It will explain what Excel limitation are and how to overcome them.
28小时
课程概览
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows).
The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course.
Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.
The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows).
The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course.
Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.
21小时
课程概览
[R](http://www.r-project.org/) is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students. It covers language fundamentals, libraries and advanced concepts. Advanced data analytics and graphing with real world data.
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
7小时
课程概览
This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive
14小时
课程概览
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
21小时
课程概览
Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing.
In this instructor-led, live course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes.
Audience
- Data analysts or anyone interested in learning how to interpret data to solve problems
Format of the Course
- After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations.
In this instructor-led, live course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes.
Audience
- Data analysts or anyone interested in learning how to interpret data to solve problems
Format of the Course
- After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations.
21小时
课程概览
It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.
This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.
By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.
Format of the Course
- Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.
By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.
Format of the Course
- Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
35小时
课程概览
参与者完成此次培训后，将会对大数据及其相关技术、方法、工具有一个实际和真实的理解。
参与者将有机会通过动手练习将这些知识付诸实践。小组互动和讲师反馈是课堂的重要组成部分。
本课程首先介绍大数据的基本概念，然后讲解用于执行数据分析的编程语言和方法，最后我们会讨论可启用大数据存储、分布式处理及可扩展性的工具和基础架构。
受众
- 开发人员/程序员
- IT顾问
课程形式
- 部分讲座、部分讨论、实操、偶尔测评进度
参与者将有机会通过动手练习将这些知识付诸实践。小组互动和讲师反馈是课堂的重要组成部分。
本课程首先介绍大数据的基本概念，然后讲解用于执行数据分析的编程语言和方法，最后我们会讨论可启用大数据存储、分布式处理及可扩展性的工具和基础架构。
受众
- 开发人员/程序员
- IT顾问
课程形式
- 部分讲座、部分讨论、实操、偶尔测评进度
14小时
课程概览
Elasticsearch是一个开源的分布式搜索引擎。它通常与Logstash（数据收集和日志分析引擎）和Kibana（分析和可视化平台）一起使用，组成“ELK堆栈”。
本培训针对希望使用Elasticsearch构建搜索和分析解决方案的软件开发人员。
本培训从讨论Elasticksearch架构开始，包括其分布式模型和搜索API。然后对Elasticsearch的功能、以及如何最好地将其集成到现有应用程序中进行讲解。
动手练习是本次培训的重要组成部分，让学员得以将所学知识运用到实践中，并在实践过程中收到导师的反馈意见。
受众
- 软件开发人员
课程形式
- 以现场动手实操为主。大部分概念是通过示例、练习和动手开发学到的。
本培训针对希望使用Elasticsearch构建搜索和分析解决方案的软件开发人员。
本培训从讨论Elasticksearch架构开始，包括其分布式模型和搜索API。然后对Elasticsearch的功能、以及如何最好地将其集成到现有应用程序中进行讲解。
动手练习是本次培训的重要组成部分，让学员得以将所学知识运用到实践中，并在实践过程中收到导师的反馈意见。
受众
- 软件开发人员
课程形式
- 以现场动手实操为主。大部分概念是通过示例、练习和动手开发学到的。
35小时
课程概览
本次培训的第一部分介绍了MATLAB的基本原理及其作为语言和平台的功能。本次讨论包括MATLAB语法、数组和矩阵、数据可视化、脚本开发及面向对象原理的介绍。
在第二部分中，我们演示如何使用MATLAB进行数据挖掘、机器学习和预测性分析。为了给参与者一个关于MATLAB方法和功能的清晰和实用的观点，我们将使用MATLAB和使用电子表格、C、C ++、Visual Basic等其他工具进行比较。
在培训的第三部分，参与者学习如何通过自动化数据处理和报告生成来简化工作。
在整个课程中，参与者将在实验室环境里把通过动手练习学到的想法付诸实践。培训结束后，参与者将对MATLAB的功能有一个全面的掌握，并将能够用它来解决实际的数据科学问题，并通过自动化来简化他们的工作。
整个课程中将进行评估以衡量进度。
课程形式
- 课程包含理论和实践练习，包括案例讨论、样本代码检查和实操。
注意
- 练习课程将根据预先安排的样本数据报告模板进行。如果您有特殊要求，请联系我们以作安排。
在第二部分中，我们演示如何使用MATLAB进行数据挖掘、机器学习和预测性分析。为了给参与者一个关于MATLAB方法和功能的清晰和实用的观点，我们将使用MATLAB和使用电子表格、C、C ++、Visual Basic等其他工具进行比较。
在培训的第三部分，参与者学习如何通过自动化数据处理和报告生成来简化工作。
在整个课程中，参与者将在实验室环境里把通过动手练习学到的想法付诸实践。培训结束后，参与者将对MATLAB的功能有一个全面的掌握，并将能够用它来解决实际的数据科学问题，并通过自动化来简化他们的工作。
整个课程中将进行评估以衡量进度。
课程形式
- 课程包含理论和实践练习，包括案例讨论、样本代码检查和实操。
注意
- 练习课程将根据预先安排的样本数据报告模板进行。如果您有特殊要求，请联系我们以作安排。
28小时
课程概览
在这一由讲师引导的培训中，参与者将学习高级Python编程技术，包括如何将这种多功能语言应用于解决分布式应用、财务、数据分析和可视化、UI编程及维护脚本等领域的问题。
受众
- 开发人员
课程形式
- 部分讲座、部分讨论、练习和大量实操
注意事项
- 如果您想添加、移除或自定义本课程中的任一部分或主题，请联系我们以作安排。
受众
- 开发人员
课程形式
- 部分讲座、部分讨论、练习和大量实操
注意事项
- 如果您想添加、移除或自定义本课程中的任一部分或主题，请联系我们以作安排。
42小时
课程概览
Data analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions:
What has happened?
- processing and analyzing data
- producing informative data visualizations
What will happen?
- forecasting future performance
- evaluating forecasts
What should happen?
- turning data into evidence-based business decisions
- optimizing processes
The course itself can be delivered either as a 6 day classroom course or [remotely](https://www.nobleprog.co.uk/instructor-led-online-training-courses) over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
What has happened?
- processing and analyzing data
- producing informative data visualizations
What will happen?
- forecasting future performance
- evaluating forecasts
What should happen?
- turning data into evidence-based business decisions
- optimizing processes
The course itself can be delivered either as a 6 day classroom course or [remotely](https://www.nobleprog.co.uk/instructor-led-online-training-courses) over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
21小时
课程概览
The aim of this course is to provide a clear understanding of the use of SQL for different
databases (Oracle, SQL Server, MS Access...). Understanding of analytic functions and the
way how to join different tables in a database will help delegates to move data analysis
operations to the database side, instead of doing this in MS Excel application. This can also
help in creating any IT system, which uses any relational database.
databases (Oracle, SQL Server, MS Access...). Understanding of analytic functions and the
way how to join different tables in a database will help delegates to move data analysis
operations to the database side, instead of doing this in MS Excel application. This can also
help in creating any IT system, which uses any relational database.
14小时
课程概览
Apache Kylin is an extreme, distributed analytics engine for big data.
In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse.
By the end of this training, participants will be able to:
- Consume real-time streaming data using Kylin
- Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency
Note
- We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)
Audience
- Big data engineers
- Big Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse.
By the end of this training, participants will be able to:
- Consume real-time streaming data using Kylin
- Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency
Note
- We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)
Audience
- Big data engineers
- Big Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14小时
课程概览
Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion.
In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.
By the end of this training, participants will be able to:
- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results
Audience
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.
By the end of this training, participants will be able to:
- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results
Audience
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14小时
课程概览
Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow.
This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project.
By the end of this training, participants will be able to:
- Explore how data is being interpreted by machine learning models
- Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it
- Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals.
- Explore the properties of a specific embedding to understand the behavior of a model
- Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project.
By the end of this training, participants will be able to:
- Explore how data is being interpreted by machine learning models
- Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it
- Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals.
- Explore the properties of a specific embedding to understand the behavior of a model
- Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21小时
课程概览
kdb+ is an in-memory, column-oriented database and q is its built-in, interpreted vector-based language. In kdb+, tables are columns of vectors and q is used to perform operations on the table data as if it was a list. kdb+ and q are commonly used in high frequency trading and are popular with the major financial institutions, including Goldman Sachs, Morgan Stanley, Merrill Lynch, JP Morgan, etc.
In this instructor-led, live training, participants will learn how to create a time series data application using kdb+ and q.
By the end of this training, participants will be able to:
- Understand the difference between a row-oriented database and a column-oriented database
- Select data, write scripts and create functions to carry out advanced analytics
- Analyze time series data such as stock and commodity exchange data
- Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed
- Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages
- Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring
Audience
- Developers
- Database engineers
- Data scientists
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to create a time series data application using kdb+ and q.
By the end of this training, participants will be able to:
- Understand the difference between a row-oriented database and a column-oriented database
- Select data, write scripts and create functions to carry out advanced analytics
- Analyze time series data such as stock and commodity exchange data
- Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed
- Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages
- Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring
Audience
- Developers
- Database engineers
- Data scientists
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21小时
课程概览
Data science is the application of statistical analysis, machine learning, data visualization and programming for the purpose of understanding and interpreting real-world data. F# is a well suited programming language for data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration.
In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems.
By the end of this training, participants will be able to:
- Use F#'s integrated data science packages
- Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python
- Use the Deedle package to solve time series problems
- Carry out advanced analysis with minimal lines of production-quality code
- Understand how functional programming is a natural fit for scientific and big data computations
- Access and visualize data with F#
- Apply F# for machine learning
Explore solutions for problems in domains such as business intelligence and social gaming
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems.
By the end of this training, participants will be able to:
- Use F#'s integrated data science packages
- Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python
- Use the Deedle package to solve time series problems
- Carry out advanced analysis with minimal lines of production-quality code
- Understand how functional programming is a natural fit for scientific and big data computations
- Access and visualize data with F#
- Apply F# for machine learning
Explore solutions for problems in domains such as business intelligence and social gaming
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
28小时
课程概览
R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems.
In this instructor-led, live training, participants will learn how to use R to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the R programming language
- Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate deploy and optimize an R application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
In this instructor-led, live training, participants will learn how to use R to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the R programming language
- Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate deploy and optimize an R application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
21小时
课程概览
Apache Drill是一种无模式、分布式、内存列式SQL查询引擎，用于Hadoop、NoSQL及其他云和文件存储系统。Apache Drill的强大之处在于它能够使用单个查询连接来自多个数据存储的数据。Apache Drill支持许多NoSQL数据库和文件系统，包括HBase、MongoDB、MapR-DB、HDFS、MapR-FS、Amazon S3、Azure Blob Storage、Google Cloud Storage、Swift、NAS和本地文件。
在这一由讲师引导的现场培训中，学员将学习Apache Drill的基础知识，然后利用SQL的强大功能和便利性在无需编写代码的情况下交互式查询大数据。学员还将学习如何优化分布式SQL执行的Drill查询。
在本次培训结束后，学员将能够：
- 对Hadoop上的结构化和半结构化数据进行“自助式”探索
- 使用SQL查询来查询已知以及未知数据
- 了解Apache Drills如何接收和执行查询
- 编写SQL查询来分析不同类型的数据，包括Hive中的结构化数据，HBase或MapR-DB表中的半结构化数据，以及Parquet和JSON文件中保存的数据。
- 使用Apache Drill执行即时模式发现，绕过对复杂ETL和模式操作的需求
- 将Apache Drill与BI（商业智能）工具（如Tableau、Qlikview、MicroStrategy、Excel）集成在一起
受众
- 数据分析师
- 数据科学家
- SQL程序员
课程形式
- 部分讲座、部分讨论、练习和大量实操
在这一由讲师引导的现场培训中，学员将学习Apache Drill的基础知识，然后利用SQL的强大功能和便利性在无需编写代码的情况下交互式查询大数据。学员还将学习如何优化分布式SQL执行的Drill查询。
在本次培训结束后，学员将能够：
- 对Hadoop上的结构化和半结构化数据进行“自助式”探索
- 使用SQL查询来查询已知以及未知数据
- 了解Apache Drills如何接收和执行查询
- 编写SQL查询来分析不同类型的数据，包括Hive中的结构化数据，HBase或MapR-DB表中的半结构化数据，以及Parquet和JSON文件中保存的数据。
- 使用Apache Drill执行即时模式发现，绕过对复杂ETL和模式操作的需求
- 将Apache Drill与BI（商业智能）工具（如Tableau、Qlikview、MicroStrategy、Excel）集成在一起
受众
- 数据分析师
- 数据科学家
- SQL程序员
课程形式
- 部分讲座、部分讨论、练习和大量实操
14小时
课程概览
AI is a collection of technologies for building intelligent systems capable of understanding data and the activities surrounding the data to make "intelligent decisions". For Telecom providers, building applications and services that make use of AI could open the door for improved operations and servicing in areas such as maintenance and network optimization.
In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry.
Audience
- Network engineers
- Network operations personnel
- Telecom technical managers
Format of the course
- Part lecture, part discussion, hands-on exercises
In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry.
Audience
- Network engineers
- Network operations personnel
- Telecom technical managers
Format of the course
- Part lecture, part discussion, hands-on exercises
21小时
课程概览
Dremio is an open-source "self-service data platform" that accelerates the querying of different types of data sources. Dremio integrates with relational databases, Apache Hadoop, MongoDB, Amazon S3, ElasticSearch, and other data sources. It supports SQL and provides a web UI for building queries.
In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories.
By the end of this training, participants will be able to:
- Install and configure Dremio
- Execute queries against multiple data sources, regardless of location, size, or structure
- Integrate Dremio with BI and data sources such as Tableau and Elasticsearch
Audience
- Data scientists
- Business analysts
- Data engineers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Notes
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories.
By the end of this training, participants will be able to:
- Install and configure Dremio
- Execute queries against multiple data sources, regardless of location, size, or structure
- Integrate Dremio with BI and data sources such as Tableau and Elasticsearch
Audience
- Data scientists
- Business analysts
- Data engineers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Notes
- To request a customized training for this course, please contact us to arrange.
14小时
课程概览
In this instructor-led, live training in 中国 (onsite or remote), participants will learn how to combine the capabilities of Python and Excel.
By the end of this training, participants will be able to:
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
By the end of this training, participants will be able to:
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
14小时
课程概览
A business' marketing strategy is one of its most essential tools to ensure success. The rise in technology and advances in data gathering and analysis has led to a continuous transformation of marketing. Data analysis is now considered to be a crucial skill for marketers to learn. Likewise, applying data science to marketing principles is also important in helping data science professionals maximize their contributions.
In this instructor-led, live training, participants will learn how to gain valuable insights from large data sets and how to use these for marketing strategies.
By the end of this training, participants will be able to:
- Install and configure tools for data-driven marketing tools (Tableau, Google Analytics, Zarget, etc)
- Measure, test, and optimize the performance of their marketing strategies using data
- Use data to segment their customers and prospects
- Use predictive modeling to improve response rates
- Implement step-by-step data analytics to drive better marketing decisions
Audience
- Marketers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training, participants will learn how to gain valuable insights from large data sets and how to use these for marketing strategies.
By the end of this training, participants will be able to:
- Install and configure tools for data-driven marketing tools (Tableau, Google Analytics, Zarget, etc)
- Measure, test, and optimize the performance of their marketing strategies using data
- Use data to segment their customers and prospects
- Use predictive modeling to improve response rates
- Implement step-by-step data analytics to drive better marketing decisions
Audience
- Marketers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
35小时
课程概览
Participants who complete this training will gain a practical, real-world understanding of Data Science and its related technologies, methodologies and tools.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.
Audience
- Developers
- Technical analysts
- IT consultants
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.
Audience
- Developers
- Technical analysts
- IT consultants
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
14小时
课程概览
Apache Arrow is an open-source in-memory data processing framework. It is often used together with other data science tools for accessing disparate data stores for analysis. It integrates well with other technologies such as GPU databases, machine learning libraries and tools, execution engines, and data visualization frameworks.
In this onsite instructor-led, live training, participants will learn how to integrate Apache Arrow with various Data Science frameworks to access data from disparate data sources.
By the end of this training, participants will be able to:
- Install and configure Apache Arrow in a distributed clustered environment
- Use Apache Arrow to access data from disparate data sources
- Use Apache Arrow to bypass the need for constructing and maintaining complex ETL pipelines
- Analyze data across disparate data sources without having to consolidate it into a centralized repository
Audience
- Data scientists
- Data engineers
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
In this onsite instructor-led, live training, participants will learn how to integrate Apache Arrow with various Data Science frameworks to access data from disparate data sources.
By the end of this training, participants will be able to:
- Install and configure Apache Arrow in a distributed clustered environment
- Use Apache Arrow to access data from disparate data sources
- Use Apache Arrow to bypass the need for constructing and maintaining complex ETL pipelines
- Analyze data across disparate data sources without having to consolidate it into a centralized repository
Audience
- Data scientists
- Data engineers
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
14小时
课程概览
About the Course:
Microsoft Power BI transforms your company data into rich visuals that facilitate new ways of thinking about and organizing your data, so that you can focus on what is important to achieving your goals. This course covers both Power BI on Line and Power BI desktop.
Audience:
This course is intended for Business Managers, Report Developers, Analysts, Project Managers and Team Leads.
At Course Completion
Upon completing this course, students will have a basic understanding of the topics below, as well as an ability to utilize and implement the concepts learned.
- Power BI
- Power BI Desktop
- Working with CSV, TXT, and Excel Worksheets
- Connecting to Databases
- Merging, Grouping, Summarizing, and Calculating Data
- Reporting
- Power BI Online
Microsoft Power BI transforms your company data into rich visuals that facilitate new ways of thinking about and organizing your data, so that you can focus on what is important to achieving your goals. This course covers both Power BI on Line and Power BI desktop.
Audience:
This course is intended for Business Managers, Report Developers, Analysts, Project Managers and Team Leads.
At Course Completion
Upon completing this course, students will have a basic understanding of the topics below, as well as an ability to utilize and implement the concepts learned.
- Power BI
- Power BI Desktop
- Working with CSV, TXT, and Excel Worksheets
- Connecting to Databases
- Merging, Grouping, Summarizing, and Calculating Data
- Reporting
- Power BI Online
7小时
课程概览
This instructor-led, live training in 中国 (online or onsite) is aimed at persons who wish to use graphical and numerical techniques to better understand the structure of a dataset before commencing more formal analysis.
By the end of this training, participants will be able to:
- Identify variables that that indicate connections within the data.
- Identify unusual patterns in data.
- Generate visually appealing and easy to read graphics that provide insight into the data.
- Use exploratory analysis to pave the way for more complex statistical modeling.
By the end of this training, participants will be able to:
- Identify variables that that indicate connections within the data.
- Identify unusual patterns in data.
- Generate visually appealing and easy to read graphics that provide insight into the data.
- Use exploratory analysis to pave the way for more complex statistical modeling.
14小时
课程概览
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
近期数据分析培训课程
17-08-2021 09:30
上海 - 上海中区广场
28 小时
23-08-2021 09:30
上海 - 上海中区广场
7 小时
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21 小时
08-09-2021 09:30
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14 小时
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