In this course you will learn how to translate various concepts in Amazon Redshift to the analogous concepts in BigQuery. You will learn how the high-level architectures of Amazon Redshift and BigQuery compare, understand differences in how to configure datasets and tables, map data types in Amazon Redshift to data types in BigQuery, understand schema mapping from Amazon Redshift to BigQuery, optimize your new schemas in BigQuery, and do a high-level comparison of SQL dialects in Amazon Redshift and BigQuery.
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In this course you will learn how to translate various concepts in Snowflake to the analogous concepts in BigQuery. You will learn how the high-level architectures of Snowflake and BigQuery compare, understand differences in how to configure datasets and tables, map data types in Snowflake to data types in BigQuery, understand schema mapping from Snowflake to BigQuery, optimize your new schemas in BigQuery, and do a high-level comparison of SQL dialects in Snowflake and BigQuery.
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In this course you will learn how to translate various concepts in Teradata to the analogous concepts in BigQuery. You will learn how the high-level architectures of Teradata and BigQuery compare, understand differences in how to configure datasets and tables, map data types in Teradata to data types in BigQuery, understand schema mapping from Teradata to BigQuery, optimize your new schemas in BigQuery, and do a high-level comparison of SQL dialects in Teradata and BigQuery
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This 2-day course introduces learners to Google Cloud’s data integration capability using Cloud Data Fusion. In this course, we discuss challenges with data integration and the need for a data integration platform (middleware). We then discuss how Cloud Data Fusion can help to effectively integrate data from a variety of sources and formats and generate insights.
We take a look at Cloud Data Fusion’s main components and how they work, how to process batch data and real time streaming data with visual pipeline design, rich tracking of metadata and data lineage, and how to deploy data pipelines on various execution engines.
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The PECB Chief Information Security Officer (CISO) training course is tailored for aspiring CISOs, providing them with the necessary knowledge, skills, and strategies to lead information security programs effectively and safeguard information and assets in today’s dynamic digital environment.
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This is a comprehensive two-day course designed for non-technical mid-level and senior managers aiming to deepen their understanding of Artificial Intelligence. This course covers fundamental AI concepts, explores the intricacies of Generative AI, and demonstrates practical ways AI can boost productivity within organizations. Through interactive sessions, case studies, and discussions on the latest AI technologies, participants will gain valuable insights into leveraging AI for strategic advantage.
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In this course, you will learn how to use the most common FortiGate features.
In interactive labs, you will explore firewall policies, user authentication, high availability, logging and monitoring, site-to-site IPsec VPN, FortiGate in Cloud, FortiSASE, and how to protect your network using security profiles, such as IPS, antivirus, web filtering, application control, and more. These administration fundamentals will provide you with a solid understanding of how to implement the most common FortiGate features.
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Data Engineering on AWS is a 3-day intermediate course, designed for professionals seeking a deep dive into data engineering practices and solutions on AWS.
Through a balanced combination of theory, practical labs, and activities, participants learn to design, build, optimize, and secure data engineering solutions using AWS services.
From foundational concepts to hands-on implementation of data lakes, data warehouses, and both batch and streaming data pipelines, this course equips data professionals with the skills needed to architect and manage modern data solutions at scale.
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In this course, you will learn about the basics of SD-WAN deployment scenarios using the Fortinet Secure SD-WAN solution. You will learn how to configure SDWAN on FortiGate and learn how SD-WAN interacts with FortiGate routing and firewall. This fundamental understanding of SD-WAN topics will help you design, deploy, maintain, and enhance SD-WAN deployments and existing SD-WAN deployment performance.
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In this course, you will learn how to deploy and manage FortiSASE to provide secure internet access and protect access to Software-as-a-Service (SaaS) applications for users working from on-site or remote locations. These topics will help you build a fundamental knowledge of FortiSASE basics, and learn how to enforce security policies using endpoint profiles and content inspection.
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In this course, you will learn how to protect your organization and improve its security against advanced threats that bypass traditional security controls. You will learn about how FortiSandbox detects advanced threats.
You will also learn about how FortiSandbox dynamically generates local threat intelligence, and how other advanced threat protection (ATP) components leverage this threat intelligence information to protect organizations from advanced threats.
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In this interactive course, you will learn how to deploy, provision, and manage a FortiSwitch with FortiGate using FortiLink. This course also covers the deployment and troubleshooting of Layer 2 and Layer 3 features, as well as the most common FortiSwitch stack topologies, including those that leverage multichassis link aggregation group (MCLAG) for redundancy and higher performance. You will also learn about FortiSwitch in standalone mode, its unique features, and how to manage a standalone switch directly, or from FortiLAN Cloud.
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In this course, you will learn how to deploy, configure, and troubleshoot secure wireless LAN using an integrated wireless solution. Using interactive labs, you will enforce your knowledge of deploying a secure wireless LAN centrally managed from the FortiGate wireless controller.
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Candidates should be able to demonstrate a knowledge and understanding in the application of ethical and sustainable Artificial Intelligence (AI):
- Human-centric Ethical and Sustainable Human and Artificial Intelligence (AI);
- Artificial Intelligence (AI) and Robotics;
- applying the benefits of AI projects – challenges and risks;
- Machine Learning (ML) Theory and Practice – Building a Machine Learning (ML) Toolbox;
- the Management, Roles and Responsibilities of Humans and Machines – The Future of AI.
Artificial Intelligence (AI) is a methodology for using a non-human system to learn from experience and imitate human intelligent behavior. The EXIN BCS Artificial Intelligence Foundation certification tests a candidate’s knowledge and understanding of the terminology and general principles of AI. This preparation guide covers the potential benefits and challenges of ethical and sustainable robust Artificial Intelligence (AI); the basic process of Machine Learning (ML) – Building a Machine Learning (ML) Toolkit; the challenges and risks associated with an AI project, and the future of AI and Humans in work. This Foundation certificate includes and expands on the knowledge taught in the EXIN BCS Essentials Certificate in Artificial Intelligence.






