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  • 4 Days SPVC

    This WF318G: Developing Applications in IBM Datacap v9.1.7 course provides technical professionals with the skills that are needed to build Datacap applications.

    The course begins with an introduction to IBM Datacap. You learn about capture concepts, Datacap process, page identification methods, and architecture. You process batches for Datacap applications in the Datacap clients.

    You learn about the design and components of a Datacap application. You build a Datacap application by using Forms Template in Datacap Studio and configure it. You learn how to troubleshoot a Datacap application. You configure a Datacap application to process documents of multiple page types in a single batch. You implement OCR and OMR to extract data from data fields and from multiple choice check boxes. You export data to a text file and also to an IBM FileNet Content Manager repository. You build page layouts, create virtual page blocks, and extract data from tables and label-value pairs. Through instructor-led presentations and hands-on lab exercises, you learn about the core features of IBM Datacap.

  • 4 Days SPVC

    In this 3-days TOD67G: Network Performance Insight 1.3.1 – Implementation and Configuration course, you learn how to install IBM Network Performance Insight and integrate it with IBM Netcool Operations Insight. This course is lab-intensive, with an emphasis on hands-on exercises.

    If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. /terms

  • 4 Days ILT, VILT

    IBM Network Performance Insight is a network performance monitoring system. It offers real-time and historical trends in network performance and interactive views of network data that help reduce network downtime and optimize network performance. Network Performance Insight provides IBM Netcool Operations Insight with comprehensive IP network device performance monitoring and traffic analysis. In this 3-day course, you learn how to install IBM Network Performance Insight and integrate it with IBM Netcool Operations Insight. This course is lab-intensive, with an emphasis on hands-on exercises.

    If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

  • 1 Day SPVC

    This learning offering will tell a holistic story of Cloud Pak for Data including collaboration across an organization, which is key in this platform. Applicable to all personas. Multiple use cases will provide understanding of how organizations can benefit from Cloud Pak for Data. A variety of features will also be explored, providing students with the insight on how to use the platform. This learning is relevant for Cloud Pak for Data and Cloud Pak for Data System. This WBT contains instructional and interactive content, demonstrations and hands-on simulated exercises.

  • 1 Day SPVC

    This course goes through the stages of a data science project from importing data to deployment, using services in Watson Studio and Watson Machine Learning for Cloud Pak for Data.

  • 5 Days ILT, VILT

    IBM App Connect Enterprise provides connectivity and universal data transformation in heterogeneous IT environments. It enables businesses of any size to eliminate point-to-point connections and batch processing, regardless of operating system, protocol, and data format.

    This course teaches you how to use IBM App Connect Enterprise to develop, deploy, and support message flow applications. These applications use various messaging topologies to transport messages between service requesters and service providers, and allow the messages to be routed, transformed, and enriched during processing.

    In this course, you learn how to construct applications to transport and transform data. The course explores how to control the flow of data by using various processing nodes, and how to use databases and maps to transform and enrich data during processing. You also learn how to construct data models by using the Data Format Description Language (DFDL).

  • 1 Day ILT, VILT

    This GCP-AWS: Google Cloud Fundamentals for AWS Professionals course is designed for AWS system administrators, solutions architects, and SysOps administrators who are familiar with AWS features and setup and want to gain experience configuring Google Cloud products immediately. This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud.

  • 4 Days ILT, VILT

    If you are new to Google Workspace, this training will equip you with the skills you need to be productive in the workplace. Through a series of lectures, demonstrations, and hands-on activities, you will become proficient in the use of the following core Google Workspace applications: Gmail, Google Calendar, Google Drive, Google Docs, Google Sheets, Google Slides, Google Meet and Google Chat.

  • 5 Days ILT, VILT

    What is machine learning, and what kinds of problems can it solve? Why are neural networks so popular right now? How can you improve data quality and perform exploratory data analysis? How can you set up a supervised learning problem and find a good, generalizable solution using gradient descent? In this course, you’ll learn how to write distributed machine learning models that scale in Tensorflow 2.x, perform feature engineering in BQML and Keras, evaluate loss curves and perform hyperparameter tuning, and train models at scale with Cloud AI Platform.

  • GCP-MPGC: ML Pipelines on Google Cloud

    Price range: RM9,600.00 through RM10,442.00
    4 Days ILT, VILT

    In this GCP-MPGC: ML Pipelines on Google Cloud course, you will learn about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. The first few modules discuss pipeline components, pipeline orchestration with TFX, how you can automate your pipeline through CI/CD, and how to manage ML metadata.

    Then we will discuss how to automate and reuse ML pipelines across multiple ML frameworks such as tensorflow, pytorch, scikit learn, and xgboost. You will also learn how to use Cloud Composer to orchestrate your continuous training pipelines, and MLflow for managing the complete machine learning life cycle.

  • GCP-MLOF: MLOps (Machine Learning Operations) Fundamentals

    Price range: RM2,400.00 through RM3,242.00
    1 Day ILT, VILT

    This GCP-MLOF: MLOps (Machine Learning Operations) Fundamentals course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.

    Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

  • -30%

    LMOGC: Logging, Monitoring and Observability in Google Cloud

    Original price was: RM7,200.00.Current price is: RM5,040.00.
    2 Days ILT, VILT

    The Logging, Monitoring and Observability in Google Cloud training course teaches participants techniques for monitoring, troubleshooting, and improving infrastructure and application performance in Google Cloud.

    Learn how to monitor, troubleshoot, and improve your infrastructure and application performance. Guided by the principles of Site Reliability Engineering (SRE), this official Google Cloud course features a combination of lectures, demos, hands-on labs, and real-world case studies. In this course, you’ll gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, and profiling CPU and memory usage.

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