This GCP-AMLTF: Advanced Machine Learning with TensorFlow on Google Cloud course will give you hands-on experience optimizing, deploying, and scaling a variety of production ML models. You’ll learn how to build recommendation systems
and scalable, accurate, and production-ready models for structured data, image data, time series, and natural language text.
Accelerate cloud expertise in 2025 with Google Cloud certification training.
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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.
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Empower your business with Dialogflow CX’s Advanced AI capabilities.
In this Google Cloud course, learn how to design customer conversations using Contact Center Artificial Intelligence (CCAI). You’ll use Dialogflow CX to create virtual agents and test them using the simulator. Learn to add functionality to access data from external systems, making virtual agents conversationally dynamic. You’ll be introduced to testing methods, connectivity protocols, APIs, environment management, and compliance measures.
Learn best practices for integrating conversational solutions with your existing contact center software and implementing solutions securely and at scale.
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Take your customer conversations to the next level.
In this GCP-CXCCES: Customer Experiences with Contact Center AIDialogflow ES course, learn how to design customer conversations using Contact Center Artificial Intelligence (CCAI). You’ll use Dialogflow ES to create virtual agents and test them using the simulator.
Learn to add functionality to access data from external systems, making virtual agents conversationally dynamic. You’ll be introduced to testing methods, connectivity protocols, APIs, environment management, and compliance measures. Learn best practices for integrating conversational solutions with your existing contact center software and implementing solutions securely and at scale.
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Master the art of database migration with our comprehensive Google Cloud Database Migration course.
This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to GCP while taking advantage of various GCP services.
This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.
Get 15% off – build your enterprise data migration skills now for RM8,160.
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Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Participants learn how to apply best practices for application development and use the appropriate Google Cloud storage services for object storage, relational data, caching, and analytics.
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This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run.
Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, implement, deploy, secure, manage, and scale applications on Google Cloud using Cloud Run.
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Get the best of on-premises and Apigee cloud advantages.
Learn how to install and manage Google Cloud’s Apigee API Platform in a hybrid cloud. This course uses lectures, hands-on labs, and supplemental resources to show you how to design, install, manage, and scale your Apigee API Platform.
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G Suite just got better — introducing Google Workspace. Content delivered by our partners may still include some references to G Suite as updates are being made but you will still receive relevant training. If you’re a Google Workspace admin who needs to manage and establish Google Workspace best practices for your organization, the lectures and hands-on labs in this course will show you how to use the features in the admin console so that you can manage users, control access to services, configure security settings, monitor Google Workspace operations, and more
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This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions.
It explores the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project. You learn how to build AutoML models without writing a single line of code; build BigQuery ML models using SQL, and build Vertex AI custom training jobs by using Keras and TensorFlow. You also explore data preprocessing techniques
and feature engineering.Take 40% off this in-demand course – now only RM5,760 to level up your ML skills.
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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.
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Learn best practices in cloud security and how the Google Cloud security model can help protect your technology stack. Security Engineers actively assess existing Google Cloud implementations, identifying potential security issues, and prioritizing solutions.
This Google Cloud certification uses lectures, demos, and hands-on labs to teach you about a variety of Google Cloud security controls and techniques. You’ll explore the components of Google Cloud and deploy a secure solution on the platform. You’ll also learn how to mitigate attacks at several points in a Google Cloud-based infrastructure, including distributed denial-of-service attacks, phishing attacks, and threats involving content classification and use.
Explore more about cybersecurity certifications with our cybersecurity training and certifications guide.
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Data Engineers design solutions that ensure maximum flexibility and scalability, while meeting all required security controls.
Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning.
This Google Cloud course covers structured, unstructured, and streaming data.
Upskill in data engineering with 40% off – limited-time price: RM5760.
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This training course builds on the networking concepts covered in the Networking Fundamentals in Google Cloud course. Through presentations, demonstrations, and labs, participants explore and deploy Google Cloud networking technologies.
These technologies include: Virtual Private Cloud (VPC) networks, subnets, and firewalls; Interconnection among networks; Load balancing ;Cloud DNS; Cloud CDN; Cloud NAT.
The course will also cover common network design patterns.
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Learn how to deploy and manage containerized applications on Google Kubernetes Engine (GKE) and the other tools on Google Cloud. This course features a combination of lectures, demos, and hands-on labs to help you explore and deploy solution elements—including infrastructure components like pods, containers, deployments, and services—along with networks and application services. You’ll also learn how to deploy practical solutions, including security and access management, resource management, and resource monitoring.
Learn more about Kubernetes Expertise here: Kubernetes Expertise: Unlocking Cloud Potential in Malaysia
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In this course, you learn about the internals of BigQuery and best practices for designing, optimizing, and administering your data warehouse. Through a combination of lectures, demos, and labs, you learn about BigQuery architecture and how to design optimal storage and schemas for data ingestion and changes.
Next, you learn techniques to improve read performance, optimize queries, manage workloads, and use logging and monitoring tools. You also learn about the different pricing models.
Finally, you learn various methods to secure data, automate workloads, and build machine learning models with BigQuery ML.
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The next generation of Dataflow: Dataflow Prime, Dataflow Go, and Dataflow ML.
This training is intended for big data practitioners who want to further their understanding of Dataflow in order to advance their data processing applications.
Beginning with foundations, this training explains how Apache Beam and Dataflow work together to meet your data processing needs without the risk of vendor lock-in. The section on developing pipelines covers how you convert your business logic into data processing applications that can run on Dataflow.
This training culminates with a focus on operations, which reviews the most important lessons for operating a data application on Dataflow, including monitoring, troubleshooting, testing, and reliability
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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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This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision-making.
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Unlock the power of data with Cloud Data Fusion.
This 2-day Google Cloud 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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Discover how to modernize, manage, and observe applications using Kubernetes—whether the application is deployed on-premises or on Google Cloud. This course uses lectures and hands-on labs to help you explore and deploy using Kubernetes Engine (GKE), GKE Connect, Istio service mesh, and Anthos Config Management capabilities that will enable you to work with modern applications, even when they are split among multiple clusters hosted by multiple providers, or on-premises. This is a continuation of Architecting with GKE, and you’ll need hands-on experience with the technologies covered in that course in order to benefit from this course.
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This GCPGCE: Architecting with Google Compute Engine course will familiarize you with Google Cloud’s flexible infrastructure and platform services, with a specific focus on Compute Engine. This session uses a combination of lectures, demos, and hands-on labs to explore and deploy solution elements, including infrastructure components like networks, systems, and application services.
You’ll also learn how to deploy practical solutions such as secure interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
Now at RM4,500 – get 37.5% off this hands-on course for aspiring cloud engineers.
Learn more about Multicloud Strategies in Malaysia: Adopting Multicloud Strategies in Malaysia: A 2024 Roadmap
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In this course, you will take a journey from a broad overview of gen AI to understanding how to leverage gen AI and Google Cloud for organizational transformation.
Upskill in Generative AI with 30% off – limited-time price: RM3360
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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.
