Explore Our Courses

Big Data Analytics with Google Colab and Apache Spark

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level data scientists and engineers who wish to use Google Colab and Apache Spark for big data processing and analytics.By the end of this training, participants will be able to:
  • Set up a big data environment using Google Colab and Spark.
  • Process and analyze large datasets efficiently with Apache Spark.
  • Visualize big data in a collaborative environment.
  • Integrate Apache Spark with cloud-based tools.
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Time Series Analysis with Google Colab

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level data professionals who wish to apply time series forecasting techniques to real-world data using Google Colab.By the end of this training, participants will be able to:
  • Understand the fundamentals of time series analysis.
  • Use Google Colab to work with time series data.
  • Apply ARIMA models to forecast data trends.
  • Utilize Facebook’s Prophet library for flexible forecasting.
  • Visualize time series data and forecasting results.
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Google Gemini AI for Data Analysis

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level to intermediate-level data analysts and business professionals who wish to perform complex data analysis tasks more intuitively across various industries using Google Gemini AI.By the end of this training, participants will be able to:
  • Understand the fundamentals of Google Gemini AI.
  • Connect various data sources to Gemini AI.
  • Explore data using natural language queries.
  • Analyze data patterns and derive insights.
  • Create compelling data visualizations.
  • Communicate data-driven insights effectively.
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Introduction to dbt Cloud

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level data engineers, analysts, and scientists who wish to understand how to use dbt Cloud to manage their data warehousing and transformation projects in the cloud. By the end of this training, participants will be able to:
  • Create and manage projects on dbt Cloud.
  • Use the dbt Cloud interface to schedule and run data transformations.
  • Collaborate on projects with team members.
  • Deploy their dbt projects to production.
  • Debug and troubleshoot dbt projects.
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AWS Glue Fundamentals

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at data engineers and analysts who wish to learn beginner to intermediate-level knowledge of using AWS Glue to set up a data pipeline. By the end of this training, participants will be able to:
  • Understand the fundamentals of AWS Glue.
  • Set up an AWS Glue pipeline.
  • Set up AWS Glue crawlers and jobs.
  • Learn how to use AWS Glue transformations.
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Data Analytics with Tableau, Python, R, and SQL

 35 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at data analysts and anyone who is interested to learn how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis.By the end of this training, participants will be able to:
  • Perform data analysis using Python, R, and SQL.
  • Create insights through data visualization with Tableau.
  • Make data-driven decisions for business operations.
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Advanced ArcGIS Pro for Spatial Analysis

 35 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at advanced-level GIS professionals who wish to use ArcGIS Pro to enhance their spatial analysis capabilities, conduct comprehensive geostatistical analysis, and apply advanced 3D modeling techniques for more effective decision-making and problem-solving in real-world scenarios.By the end of this training, participants will be able to:
  • Develop advanced skills in spatial analysis techniques using ArcGIS Pro.
  • Utilize Python scripting for automation and complex data processing.
  • Apply spatial modeling for problem-solving in real-world scenarios.
  • Conduct geostatistical analysis for advanced data interpretation.
  • Integrate external data sources and leverage 3D spatial data analysis.
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IBM Planning Analytics (TM1)

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at analysts who wish to use TM1 to analyze and customize reports and templates for data in a database. By the end of this training, participants will be able to:
  • Learn how to analyze data using IBM Planning Analytics.
  • Create custom views of the data in a database.
  • Build reports and forms that communicate with TM1.
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Azure Synapse Analytics

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level data engineers who wish to become proficient in utilizing Azure Synapse Analytics for a wide range of data processing, analytics, and visualization.By the end of this training, participants will be able to:
  • Understand the core concepts, architecture, and components of Azure Synapse Analytics.
  • Create, configure, and manage scalable data warehouses using Azure Synapse.
  • Master the techniques for ingesting, transforming, and loading data (ETL) from various sources into Azure Synapse.
  • Optimize query performance, secure data, and integrate Azure Synapse with Power BI and other tools to visualize data and share insights.
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ArcGIS Enterprise for Technical Support

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level IT support personnel who wish to provide robust support for ArcGIS Enterprise, addressing any anomalies or failures effectively.By the end of this training, participants will be able to:
  • Understand the architecture and components of ArcGIS Enterprise.
  • Learn to install, configure, and manage ArcGIS Enterprise.
  • Gain skills in troubleshooting and resolving common issues.
  • Develop proficiency in monitoring and maintaining ArcGIS Enterprise environments.
  • Master the techniques for backup, recovery, and performance optimization.
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Analytic Functions Fundamentals

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level database administrators, SQL developers, and data analysts who wish to enhance their SQL skills by mastering the use of Analytic Functions. By the end of this training, participants will be able to:
  • Understand the concept and importance of Analytic Functions.
  • Apply various Analytic Functions to solve complex analytical problems.
  • Combine Analytic Functions with other SQL features for comprehensive data analysis.
  • Optimize queries for better performance using Analytic Functions.
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Data Analysis with MongoDB Aggregation Framework

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at data analysts and data scientists who wish to use the MongoDB Aggregation Framework to perform data analysis while simplifying complex operations and aggregation pipelines. By the end of this training, participants will be able to:
  • Install and configure MongoDB for data analysis.
  • Understand the concepts and stages of the MongoDB Aggregation Framework.
  • Learn about the basic structure, syntax, and operations for aggregation.
  • Learn how to handle advanced operations in aggregation.
  • Apply some optimization tools and techniques to improve aggregation performance.
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ArcGIS Fundamentals

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at beginner-level professionals who wish to learn the fundamental concepts and tools of ArcGIS.By the end of this training, participants will be able to:
  • Understand the basic concepts of GIS and spatial data.
  • Navigate the ArcGIS interface.
  • Create and manage spatial data.
  • Perform basic spatial analysis.
  • Create maps and visualizations.
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ArcMap in ArcGIS

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level environmental scientists and archaeologists who wish to learn how to use ArcMap in ArcGIS for collecting, organizing, managing, and analyzing geographic information. By the end of this training, participants will be able to:
  • Understand the fundamentals of ArcMap and ArcGIS.
  • Collect, organize, manage, and analyze geographic information on the social and archaeological elements.
  • Conduct spatial queries for impact evaluation.
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A Practical Introduction to Data Analysis and Big Data

 35 時間
Participants who complete this instructor-led, live training in 日本 will gain a practical, real-world understanding of Big Data 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 Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability.
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Data Analytics With R

 21 時間
R 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.AudienceDevelopers / data analyticsDuration3 daysFormatLectures and Hands-on
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Data Analysis with Hive/HiveQL

 7 時間
This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive
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Excel For Statistical Data Analysis

 14 時間
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.
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A Practical Introduction to Data Science

 35 時間
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.
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Data and Analytics - from the ground up

42 時間
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 over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
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Data Analysis with Python, Pandas and Numpy

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.By the end of this training, participants will be able to:
  • Set up a development environment that includes Python, Pandas, and NumPy.
  • Create a data analysis application using Pandas and NumPy.
  • Perform advanced data wrangling, sorting, and filtering operations.
  • Conduct aggregate operations and analyze time series data.
  • Visualize data using Matplotlib and other visualization libraries.
  • Debug and optimize their data analysis code.
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Talent Acquisition Analytics

 14 時間
This instructor-led, live training (online or onsite) is aimed at HR professionals and recruitment specialists who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Knowledge Discovery in Databases (KDD)

 21 時間
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.
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Apache Kylin: From Classic OLAP to Real-Time Data Warehouse

 14 時間
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
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Datameer for Data Analysts

 14 時間
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
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HR Analytics for Public Organisations

 14 時間
This instructor-led, live training (online or onsite) is aimed at HR professionals who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Dremio for Self-Service Data Analysis

 21 時間
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.
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IBM Cloud Pak for Data

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at data scientists who wish to use IBM Cloud Pak to prepare data for use in AI solutions.By the end of this training, participants will be able to:
  • Install and configure Cloud Pak for Data.
  • Unify the collection, organization and analysis of data.
  • Integrate Cloud Pak for Data with a variety of services to solve common business problems.
  • Implement workflows for collaborating with team members on the development of an AI solution.
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Python for Excel

 14 時間
In this instructor-led, live training in 日本 (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.
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Data Analysis for Marketers

 14 時間
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.
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Data Analysis with SQL, Python and Spotfire

 14 時間
In this instructor-led, live training in 日本, participants will learn three different approaches for accessing, analyzing and visualizing data. We start with an introduction to RDMS databases; the focus will be on accessing and querying an Oracle database using the SQL language. Then we look at strategies for accessing an RDMS database programmatically using the Python language. Finally, we look at how to visualize and present data graphically using TIBCO Spotfire. Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
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kdb+ and q: Analyze Time Series Data

 21 時間
In this instructor-led, live training in 日本, 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.
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Azure for Data Engineer

 35 時間
Data analysis refers to the process of obtaining, cleaning, and analyzing data, often times in a visual manner, to derive insights for better decision making. More and more data is being stored in databases in the cloud so it is important to have a strategy for understanding, managing and accessing such data. One popular tool for accessing and visualizing data is Power Bi. This instructor-led, live training (online or onsite) is aimed at technical persons who wish to gain a practical understanding of available cloud solutions, the data analysis processes needed to work with data in the cloud, and the hands-on practice to apply tools such as Power BI to analyze data. By the end of this training, participants will be able to:
  • Install and configure Power BI.
  • Evaluate the various data solutions offered by cloud providers such as Azure.
  • Gain an understanding of the different structures, modeling approaches, and data warehouse designs used to store, manage and access Big Data.
  • Apply tools and techniques to clean data in preparation for analysis.
  • Build reporting and analytics solutions based on on-premise as well as cloud data.
  • Integrate data analytics solutions with a data warehouse.
  • Mitigate data security risks and ensure data privacy.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
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Apache Arrow for Data Analysis across Disparate Data Sources

 14 時間
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.
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Search and Analytics with Amazon OpenSearch

 21 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at developers and administrators who wish to use OpenSearch to perform distributed search and data analytics in a unified and secure system.By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building search and analytics solutions with OpenSearch and OpenSearch Dashboards.
  • Understand the three approaches (snapshot, restart, and rolling) in upgrading from Elasticsearch OSS to OpenSearch.
  • Learn how to index data, create data streams, run queries, and streamline cross-cluster operations in OpenSearch.
  • Explore and use plugins, APIs, clients, and ingestion tools (Beats, Logstash, Grafana, etc.) to optimize search experience while keeping clusters secure.
  • Use OpenSearch Dashboards to centralize data management, visualization, logging, monitoring, and maintenance.
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Python for Data Analysis

 28 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc.. By the end of this training, participants will be able to:
  • Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
  • Analyze data from sources such as Excel, CSV, JSON files and databases.
  • Clean data to improve its usefulness before analyzing it.
  • Perform simple statistical analysis.
  • Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
  • Gain valuable insight from data, including trends in performance, problematic areas.
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F# for Data Science

 21 時間
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
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Embedding Projector: Visualizing Your Training Data

 14 時間
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
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Scaling Data Analysis with Python and Dask

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets. By the end of this training, participants will be able to:
  • Set up the environment to start building big data processing with Dask and Python.
  • Explore the features, libraries, tools, and APIs available in Dask.
  • Understand how Dask accelerates parallel computing in Python.
  • Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
  • Optimize the Dask environment to maintain high performance in handling large datasets.
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SQL Advanced level for Analysts

21 時間
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.
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Exploratory Data Analysis

 7 時間
This instructor-led, live training in 日本 (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.
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LibreOffice Calc for Data Analysis

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at data analysts who wish to use LibreOffice Calc to conduct many forms of data analysis (from basic to advanced), leveraging similar functionalities found in Excel and other spreadsheet software. By the end of this training, participants will be able to:
  • Install the LibreOffice suite on any operating system.
  • Understand the full features and functionalities available in LibreOffice Calc.
  • Learn how to clean, validate, manipulate, and visualize data in Calc.
  • Apply the various functions and tools in Calc to perform complex data analysis.
  • Gain some tips and insights on conducting advanced data analysis.
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ArcGIS for Spatial Analysis

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at field ecologists and conservation managers who wish to create data spatial projects in ArcGIS.By the end of this training, participants will be able to:
  • Output spatial data as visualizations.
  • Conduct geostatics on actual data.
  • Implement spatial data analysis, data processing, and mapping with ArcGIS.
  • Analyze spatial data for projects in ArcGIS.
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ArcGIS Pro for Spatial Analysis

 14 時間
By the end of this training, participants will be able to:
  • Understanding GIS concepts and spatial data types using the latest version of ArcGIS Pro.
  • Investigate the user interface and evaluate the uses
  • Explore ArcGIS* Pro and how to utilize online content
  • Manage, manipulate and analyze your own data
  • Display and share your data in a meaningful and creative way
Note: We will use the latest version of ArcGIS Pro.
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ArcGIS with Python Scripting

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at GIS analysts who wish to automate repetitive tasks in GIS processes.By the end of this training, participants will be able to:
  • Build GIS applications using Python and ArcGIS tools.
  • Develop with the ArcGIS package ArcPy, using Python.
  • Apply the ArcGIS modules for map automation using object classes in Python.
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QGIS for Geographic Information System

 21 時間
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics. QGIS functions as geographic information system (GIS) software, allowing users to analyze and edit spatial information, in addition to composing and exporting graphical maps. QGIS supports both raster and vector layers; vector data is stored as either point, line, or polygon features. Multiple formats of raster images are supported, and the software can georeference images. To summarize it allows the users to Create, edit, visualise, analyse and publish geospatial information on Windows, Mac, Linux, BSD. This program, in its first phase, introduces the QGIS interface for general usage. In the second phase, we introduce PyQGIS - the python libraries of QGIS that allows the integration of GIS functionalities in your python code or your python application, so that you may even create your own Python Plugin around a particular GIS functionality.
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Advanced Data Analysis with TIBCO Spotfire

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at business analysts who wish to learn advanced Spotfire Analyst techniques for analyzing data.By the end of this training, participants will be able to:
  • Share visualizations among different team members.
  • Secure access to software based on roles and access controls.
  • Create visualizations such as map charts.
  • Integrate statistical computing languages such as R with Spotfire.
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Introduction to Spotfire

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at business analysts and data analysts who wish to learn basic Spotfire Analyst techniques for analyzing data.By the end of this training, participants will be able to:
  • Install and configure TIBCO Spotfire.
  • Combine data from different databases.
  • Visualize large datasets.
  • Create and share complex dashboards.
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AI-Driven Data Analysis with TIBCO Spotfire X

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at business analysts and data analysts who wish to use TIBCO Spotfire X with its artificial intelligence capabilities to visualize, transform, and analyze data.By the end of this training, participants will be able to:
  • Install and configure TIBCO Spotfire X.
  • Understand the features and architecture of TIBCO Spotfire X.
  • Understand the concepts behind augmented and predictive analytics.
  • Learn how to load, process, and visualize data using Spotfire X.
  • Create interactive and enhanced data visualizations.
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Insurtech: A Practical Introduction for Managers

 14 時間
Insurtech (a.k.a Digital Insurance) refers to the convergence of insurance + new technologies. In the field of Insurtech "digital insurers" apply technology innovations to their business and operating models in order to reduce costs, improve the customer experience and enhance the agility of their operations.In this instructor-led training, participants will gain an understanding of the technologies, methods and mindset needed to bring about a digital transformation within their organizations and in the industry at large. The training is aimed at managers who need to gain a big picture understanding, break down the hype and jargon, and take the first steps in establishing an Insurtech strategy.By the end of this training, participants will be able to:
  • Discuss Insurtech and all its component parts intelligently and systematically
  • Identify and demystify the role of each key technology within Insurtech.
  • Draft a general strategy for implementing Insurtech within their organization
Audience
  • Insurers
  • Technologists within the insurance industry
  • Insurance stakeholders
  • Consultants and business analysts
Format of the course
  • Part lecture, part discussion, exercises and case study group activities
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Sensu: Beginner to Advanced

 14 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at devops engineers who wish to create monitoring systems for multi-cloud infrastructures.By the end of this training, participants will be able to:
  • Monitor an enterprise from any cloud.
  • Use auto-scaling and real-time visibility to create advanced monitoring systems.
  • Authenticate a monitoring system with the Sensu API.
  • Share programmed monitoring workflows amongst team members.
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お客様の声(25)

The ability of the trainer to align the course with the requirements of the organization other than just providing the course for the sake of delivering it.

Masilonyane - Revenue Services Lesotho

コース - Big Data Business Intelligence for Govt. Agencies

The content was tough but that extra effort I had to put helped me remember and understand power BI better.

Melvin - TLI Group

コース - Power BI DAX Fundamentals

The energy, knowledge and style of teaching of the trainer

Ioana - MOLSONCOORS GLOBAL BUSINESS SERVICES SRL

コース - From Tableau Beginners to Advanced User

The course material was commendable, featuring insightful overviews of Linux and Superset. While the Python component was comprehensive, it demanded a substantial coding proficiency

EMMANUEL MFANA KUNENE - Palladium Group

コース - Apache Superset for Administrators

Practical exercises. Q&A session at the end regarding how this can be applied in our organization.

Franciszek - Bank Millennium S.A.

コース - Business Analysis, BABOK V3.0 and IIBA Certification Preparation

私たちのプロジェクトで使用しているデータ（ラスター形式の衛星画像）とより類似したデータを使用して、より実践的な演習を行えること

Matthieu - CS Group

コース - Scaling Data Analysis with Python and Dask

Machine Translated

実践的な練習がたくさん

Marcin - Narodowy Bank Polski

コース - Splunk Data Administration

Machine Translated

私たちの問題について話し合う

Rr Dwi Putri Periska Sari - PT. Becton Dickinson Indonesia

コース - Power BI for Developers

Machine Translated

Data management, reporting and statistics concepts.

Dumisani - Interfront SOC Ltd

コース - Stata: Beginner to Advanced

The training materials.

Mona Dobre - DB Global Technology

コース - SQL Advanced level for Analysts

It was insightful and I gained a lot of data analysis skills

Mamonyane Taoana - Road Safety Department

コース - Data Cleaning

Weronika created a really friendly, informal atmosphere. The training involved a lot of useful knowledge transfer, technical skills exercises and theory, as well as best practices and guidance on how to handle our own data.

Julia Kuczma - DLA Piper GSC Poland Sp. z o.o.

コース - Tableau Intermediate Training Course

sharing experiences and sharing other materials not included in the package.

BRYAN SANTOS - Mizuho Bank Ltd - Manila Branch

コース - Agile Business Analysis

What I liked the most was the coach's openness regarding the change in content as well as the approach that was previously prepared to accommodate our real needs

Ernesto Sitoe Junior - Electricidade de Mocambique

コース - Advanced Power BI

All the topics which he covered including examples. And also explained how they are helpful in our daily job.

madduri madduri - Boskalis Singapore Pte Ltd

コース - QGIS for Geographic Information System

Understanding big data beter

Shaune Dennis - Vodacom

コース - Big Data Business Intelligence for Telecom and Communication Service Providers

私はパブロのスタイル、レポートのデザイン、HTML によるカスタマイズからシンプルな ML アルゴリズムの実装まで、多くのテーマをカバーしている点が気に入りました。Go理論情報と演習のバランスも取れています。パブロは私が興味を持っているすべてのトピックを実際にカバーし、私の質問に包括的に答えてくれました。

Cristian Tudose - SC Automobile Dacia SA

コース - Advanced Data Analysis with TIBCO Spotfire

Machine Translated

Got to know new features in OS which I wasn't aware before.

Dhivyalakshmi Ponnusamy - Mercedes-Benz AG

コース - Search and Analytics with Amazon OpenSearch

Good hands on experience with the tool and excellent documentation provided

Ryan McNamara - Penten

コース - Nagios XI Administration

私たちのニーズに合わせて非常にダイナミックに調整された点が気に入りました。

Bogdan Dinica - Sennheiser Consumer Electronics GmbH, Brasov Division

コース - MicroStrategy Business Intelligence (BI)

Machine Translated

Very hands-on practice, engaging and good amount of breaks in between. Thus did not feel tired/lethargic.

Charles Lim - Ministry of Defence, Singapore

コース - Python for Data Analysis

Younes is a great trainer. Always willing to assist, and very patient. I will give him 5 stars. Also, the QLIK sense training was excellent, due to an excellent trainer.

Dietmar Glanninger - BMW

コース - Qlik Sense for Data Science

Instructor is an expert in her subject matter. Teaching over zoom can be difficult since it's hard to gauge your audience but the instructor did great.

Nicolo Menez - AllianceBernstein

コース - Python with Plotly and Dash

Hands on exercise and the guidance of the trainer

Jackielou Nina Dellosa - Asiagate Networks, Inc.

コース - JasperReports

アプリケーションの例を共有する

コース - Alteryx for Data Analysis

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