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Elevate Your Expertise with Advanced Excel Training
Looking to supercharge your Microsoft Excel skills? Our ‘Microsoft Excel 2021 Advanced’ course is your ticket to unlocking the full potential of this powerful tool. Whether you’re a clerk, executive, manager, or just someone passionate about mastering Excel, this course is tailor-made for you. We’ve designed it to take your existing Excel knowledge to the next level, helping you excel in your professional endeavors.
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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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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 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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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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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 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 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 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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The EXIN BCS Machine Learning Award gives you a clear, structured introduction to machine learning—covering key algorithms, data processing, model training, and real-world applications. You’ll learn how to prepare and transform data, understand supervised and unsupervised learning, and get hands-on insights into programming languages and ML frameworks such as Python, TensorFlow, and Scikit-Learn—even if you’re new to AI.
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The EXIN BCS Generative AI Award equips you with the essential knowledge to harness generative AI effectively, ethically, and strategically. Whether you’re looking to enhance your career, future-proof your skills, or gain a competitive edge, this certification validates your expertise in one of today’s most transformative technologies.
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EXIN’s AI Compliance Professional (AICP) is the first certification that directly integrates the EU AI Act, ISO/IEC 42001, and NIST AI RMF into practical, lifecycle-based compliance — ideal for real-world business settings. Designed for professionals who need to implement, audit, and govern AI systems across their entire lifecycle — with ready-to-use templates, checklists, and governance controls. Master AI risk management, data privacy, and responsible AI implementation that customers will trust.
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This course serves as an appropriate entry point to learn Apache Spark Programming with Databricks.
Below, we describe each of the four, four-hour modules included in this course.
Introduction to Apache Spark
This course offers essential knowledge of Apache Spark, with a focus on its distributed architecture and practical applications for large-scale data processing. Participants will explore programming frameworks, learn the Spark DataFrame API, and develop skills for reading, writing, and transforming data using Python-based Spark workflows.
Developing Applications with Apache Spark
Master scalable data processing with Apache Spark in this hands-on course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.
Stream Processing and Analysis with Apache Spark
Learn the essentials of stream processing and analysis with Apache Spark in this course. Gain a solid understanding of stream processing fundamentals and develop applications using the Spark Structured Streaming API. Explore advanced techniques such as stream aggregation and window analysis to process real-time data efficiently. This course equips you with the skills to create scalable and fault-tolerant streaming applications for dynamic data environments.
Monitoring and Optimizing Apache Spark Workloads on Databricks
This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You’ll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.
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This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and configure alerts. This course will prepare you to take the Databricks Certified Data Analyst Associate exam.
This course consists of two four-hour modules.
SQL Analytics on Databricks
In this course, you’ll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights.
You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL.
Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.
AI/BI for Data Analysts
In this course, you’ll learn how to use the features Databricks provides for business intelligence needs: AI/BI Dashboards and AI/BI Genie. As a Databricks Data Analyst, you will be tasked with creating AI/BI Dashboards and AI/BI Genie Spaces within the platform, managing the access to these assets by stakeholders and necessary parties, and maintaining these assets as they are edited, refreshed, or decommissioned over the course of their lifespan. This course intends to instruct participants on how to design dashboards for business insights, share those with collaborators and stakeholders, and maintain those assets within the platform. Participants will also learn how to utilize AI/BI Genie Spaces to support self-service analytics through the creation and maintenance of these environments powered by the Databricks Data Intelligence Engine.
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This is an introductory course that serves as an appropriate entry point to learn Data Engineering with Databricks.
Below, we describe each of the four, four-hour modules included in this course.
1. Data Ingestion with Lakeflow Connect
This course provides a comprehensive introduction to Lakeflow Connect as a scalable and simplified solution for ingesting data into Databricks from a variety of data sources. You will begin by exploring the different types of connectors within Lakeflow Connect (Standard and Managed), learn about various ingestion techniques, including batch, incremental batch, and streaming, and then review the key benefits of Delta tables and the Medallion architecture.
From there, you will gain practical skills to efficiently ingest data from cloud object storage using Lakeflow Connect Standard Connectors with methods such as CREATE TABLE AS (CTAS), COPY INTO, and Auto Loader, along with the benefits and considerations of each approach. You will then learn how to append metadata columns to your bronze level tables during ingestion into the Databricks data intelligence platform. This is followed by working with the rescued data column, which handles records that don’t match the schema of your bronze table, including strategies for managing this rescued data.
The course also introduces techniques for ingesting and flattening semi-structured JSON data, as well as enterprise-grade data ingestion using Lakeflow Connect Managed Connectors.
Finally, learners will explore alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with foundational knowledge to support modern data engineering ingestion.
2. Deploy Workloads with Lakeflow Jobs
Deploy Workloads with Lakeflow Jobs course teaches how to orchestrate and automate data, analytics, and AI workflows using Lakeflow Jobs. You will learn to make robust, production-ready pipelines with flexible scheduling, advanced orchestration, and best practices for reliability and efficiency-all natively integrated within the Databricks Data intelligence Platform. Prior experience with Databricks, Python and SQL is recommended.
3. Build Data Pipelines with Lakeflow Spark Declarative Pipelines
This course introduces users to the essential concepts and skills needed to build data pipelines using Lakeflow Spark Declarative Pipelines (SDP) in Databricks for incremental batch or streaming ingestion and processing through multiple streaming tables and materialized views. Designed for data engineers new to Spark Declarative Pipelines, the course provides a comprehensive overview of core components such as incremental data processing, streaming tables, materialized views, and temporary views, highlighting their specific purposes and differences.
Topics covered include:
– Developing and debugging ETL pipelines with the multi-file editor in Spark Declarative Pipelines using SQL (with Python code examples provided)
– How Spark Declarative Pipelines track data dependencies in a pipeline through the pipeline graph
– Configuring pipeline compute resources, data assets, trigger modes, and other advanced options
Next, the course introduces data quality expectations in Spark Declarative Pipelines, guiding users through the process of integrating expectations into pipelines to validate and enforce data integrity. Learners will then explore how to put a pipeline into production, including scheduling options, and enabling pipeline event logging to monitor pipeline performance and health.
Finally, the course covers how to implement Change Data Capture (CDC) using the AUTO CDC INTO syntax within Spark Declarative Pipelines to manage slowly changing dimensions (SCD Type 1 and Type 2), preparing users to integrate CDC into their own pipelines.
4. Data Management and Governance with Unity Catalog
In this course, you’ll learn about data management and governance using Databricks Unity Catalog. It covers foundational concepts of data governance, complexities in managing data lakes, Unity Catalog’s architecture, security, administration, and advanced topics like fine-grained access control, data segregation, and privilege management.
* This course seeks to prepare students to complete the Associate Data Engineering certification exam, and provides the requisite knowledge to take the course Advanced Data Engineering with Databricks.
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This course serves as an appropriate entry point to learn Advanced Data Engineering with Databricks.
Below, we describe each of the four, four-hour modules included in this course.
Databricks Streaming and Lakeflow Spark Declarative Pipelines
This course provides a comprehensive understanding of Spark Structured Streaming and Delta Lake, including computation models, configuration for streaming read, and maintaining data quality in a streaming environment.
Databricks Data Privacy
This content is intended for the learner persona of data engineers or for customers, partners, and employees who complete data engineering tasks with Databricks. It aims to provide them with the necessary knowledge and skills to execute these activities effectively on the Databricks platform.
Databricks Performance Optimization
In this course, you’ll learn how to optimize workloads and physical layout with Spark and Delta Lake and and analyze the Spark UI to assess performance and debug applications. We’ll cover topics like streaming, liquid clustering, data skipping, caching, photons, and more.
Automated Deployment with Databricks Asset Bundles
This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.
The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Databricks Asset Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Databricks Asset Bundles for multiple environments with different configurations using the Databricks CLI.
Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Databricks Asset Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Databricks Asset Bundles.
By the end of this course, you will be equipped to automate Databricks project deployments with Databricks Asset Bundles, improving efficiency through DevOps practices.
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Welcome to Machine Learning with Databricks!
This course is your gateway to mastering machine learning workflows on Databricks. Dive into data preparation, model development, deployment, and operations, guided by expert instructors. Learn essential skills for data exploration, model training, and deployment strategies tailored for Databricks. By course end, you’ll have the knowledge and confidence to navigate the entire machine learning lifecycle on the Databricks platform, empowering you to build and deploy robust machine learning solutions efficiently. -
In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Databricks Asset Bundles (DABs), Workflows, and Mosaic AI Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.
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Trainocate: A Global Leader in Technology, Business, and People Development
In a world that never stands still, we help you move forward.
With over 30 years of experience, Trainocate has been empowering individuals and businesses to build the essential skills that drive growth and success. Whether it’s professionals advancing in their careers or organizations transforming their workforce, our training programmes deliver results.
Specializing in cloud computing, data & AI, cybersecurity, and digital leadership, our training is powered by industry-leading technology partners like AWS, Alibaba Cloud, Cisco, EC-Council, Fortinet, Google Cloud, IBM, ISACA, ISC2, Microsoft, NetApp, Nutanix, Oracle, Palo Alto, Splunk, Red Hat, Rocheston, Trend Micro, and VMware.
Trainocate Group operates in 24 countries blending global expertise with localized insights to train the next generation of tech professionals and business leaders.
Trainocate Malaysia, based in KL Eco City, is proud to be an HRD Corp Registered Training Provider and a Yayasan Peneraju ALTI, driving workforce development across Malaysia.
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