Hakutulokset sanalle: dp-100

DP-100: Designing and Implementing a Data Science Solution on Azure

Koulutuksessa opit käyttämään Microsoft Azuren Machine Learning PaaS-työkalua sekä sen tekoäly- ja koneoppimisominaisuuksia. Koulutuksen jälkeen osaat hallinnoida datan siirtoa ja prosessointia analysointia varten.
Koulutus valmistaa sertifiointitestiin DP-100: Designing and Implementing a Data Science Solution on Azure.

MS-100: Microsoft 365 Identity and Services

MS-100: Microsoft 365 Identity and Services -koulutus antaa sinulle valmiudet hallita ja ylläpitää  identiteettejä ja palveluita Microsoft 365 -ympäristössä. Lisäksi koulutus auttaa sinua valmistautumaan Microsoftin viralliseen sertifiointitestiin MS-100: Microsoft 365 Identity and Services.
MS-100on yksi kolmesta sertifiointitestistä, jotka vaaditaan aiemman MCSA: Office 365 -sertifioinnin korvaavan Microsoft 365 Certified: Enterprise Administrator Expert -sertifikaatin suorittamiseksi.
Expert-tason sertifikaattiin sinun tulee lisäksi suorittaa MS-101 – Microsoft 365 Mobility and Security -sertifikaatti. MS-100 ja MS-101-sertifikaattien lisäksi sinulla on oltava suoritettuna yksi MD-sertifikaateista. Suosittelemme MD-101: Managing Modern Desktops -sertifikaattia, johon löytyy valikoimistamme koulutus.

AI-100: Designing and Implementing an Azure AI Solution

Koulutuksessa perehdytään tekoälysovelluksen tekemiseen Microsoft Azure -ympäristössä. Koulutuksen aikana opit toteuttamaan asiakaspalvelu-botin Azure tekoälypalveluiden työkaluilla. Lisäksi opit käyttämään muun muqassa Azure Cognitive Services -palvelua.
Koulutus valmistaa sertifiointitestiin AI-100: Azure AI Engineer Associate.

DP-200: Implementing an Azure Data Solution

Koulutuksen jälkeen osaat käyttää Microsoftin data-alustoja liiketoiminnan vaatimukset ja tekniset kriteerit täyttävien ratkaisujen luomiseksi sekä relaatio- että No-SQL-tietokantoihin, pilveen, hybridinä tai omaan konesaliin. Opit myös prosessoimaan dataa useilla eri tekniikoilla ja kielellä. Koulutuksen jälkeen osaat myös huolehtia datan turvallisuudesta sekä määritellä ja toteuttaa dataratkaisun monitorointia.

SAFe DevOps Practitioner with SDP Certification

SAFe® DevOps course provides you a comprehensive overview for understanding the DevOps competencies needed to accelerate time-to-market by improving the flow of value through the Continuous Delivery Pipeline. Attending the class prepares you to take the exam and become a certified SAFe DevOps Practitioner (SDP).
A SAFe 5 Certified DevOps Practitioner (SDP) is a SAFe professional responsible for improving the complete flow of value through a Continuous Delivery Pipeline from idea to operational solution. Key areas of responsibility include participating in Continuous Exploration, Continuous Integration, Continuous Deployment, Release-on-Demand, continuous testing, continuous security, and building a culture of shared responsibility.
Optimizing Your Value Stream with the Scaled Agile Framework SAFe, version 5.1
The course will build an understanding of the complete flow of value from Continuous Exploration to Continuous Integration, Continuous Deployment, and Release on Demand. Attendees will explore SAFe’s CALMR (Culture, Automation, Lean, Measure, Recover) approach to DevOps, which helps create a culture of shared responsibility for the full spectrum of Solution delivery. It helps align people, processes, and technology throughout the organization to achieve faster time-to-market.
Attendees will leave with the tools they need to execute an implementation plan for improving their delivery pipeline, and the knowledge they need to support the plan.
Attendees may be eligible to apply for 15 PDUs toward their continuing education requirements with the Project Management Institute (PMI) for PMP and PMI-ACP certifications.
SAFe® and Scaled Agile Framework® are registered marks of Scaled Agile, Inc.

DP-203: Data Engineering on Microsoft Azure

In this course, the student will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics.