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.
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.
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
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.
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
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
This Architecting with Google Cloud: Design and Process course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective.
This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course.
Limited-time offer: 40% off – sharpen your cloud architecture skills for only RM2,880.
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.
Learn about Google Cloud’s computing and storage services available, including Compute Engine, Google Kubernetes Engine, App Engine, Cloud Storage, Cloud SQL, and BigQuery.
This GCPCIN: Google Cloud Fundamentals: Core Infrastructure course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies
Enroll now for RM1,320 – enjoy 45% off this entry-level course in Google Cloud fundamentals.
Learn more about Multicloud Strategies in Malaysia: Adopting Multicloud Strategies in Malaysia: A 2024 Roadmap
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.
This GCP: GCSO: Understanding Google Cloud Security and Operations course examines cost management, security, and operations in the cloud. First, it explores how businesses can choose to maintain some or none of their own infrastructure by purchasing IT services from a cloud provider. Next, it explains how the responsibility of data security is shared between the cloud provider and the business, and explores the defense-in-depth security built into Google Cloud.
Finally, it covers how IT teams and business leaders need to rethink IT resource management in the cloud and how Google Cloud resource monitoring tools can help them to maintain control and visibility over their cloud environment.
This is the fourth and final course in the Cloud Digital Leader series.
As generative AI becomes more common, the ability to interact with large language models is shifting from niche knowledge to a necessary skill across many different industries and roles.
In this course, you will learn the fundamentals of prompting large language models and exploring further techniques for improving the output from large language models. You will also explore similar concepts when working with multimodal models such as Gemini Vision Pro.
Vertex AI Agent Builder lets developers, even those with limited machine learning skills, tap into the power of Google’s foundation models, search expertise, and conversational AI technologies to create enterprise-grade generative AI applications.
In this course, you learn how to use Vertex AI Agent Builder to create search engines and chat applications. You will then explore how to integrate these search engineers and chat applications into your own applications.
Finally, you learn how to manage the tools built in Vertex AI Agent Builder in production.
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
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.
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.
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.
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.
In this course, you explore generative AI (Gen AI) use cases across specific industries using Google Cloud.
After discussing generative AI in general, you will do a deep dive into two generative AI use cases and then explore your own use case within the same framework. This course targets professionals across different roles, including business analysts, data scientists, software developers, business users, and decision-makers, who are specifically interested in leveraging generative AI for business solutions.
Cloud technology on its own only provides a fraction of the true value to a business; When combined with data–lots and lots of it–it has the power to truly unlock value and create new experiences for customers. In this course, you’ll learn what data is, historical ways companies have used it to make decisions, and why it is so critical for machine learning. This course also introduces learners to technical concepts such as structured and unstructured data. database, data warehouse, and data lakes. It then covers the most common and fastest growing Google Cloud products around data.
This is the second course in the Cloud Digital Leader series. At the end of this course, enroll in the Infrastructure and Application Modernization with Google Cloud course.
In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.
Upskill in introduction to data engineering with 30% off – limited-time price: RM1680
Many traditional enterprises use legacy systems and applications that often struggle to achieve the scale and speed needed to meet modern customer expectations. Business leaders and IT decision makers constantly have to choose between maintenance of legacy systems and investing in innovative new products and services.
This course explores the challenges of an outdated IT infrastructure and how businesses can modernize it using cloud technology. It begins by exploring the different compute options available in the cloud and the benefits of each, before turning to application modernization and Application Programming Interfaces (APIs). The course also considers a range of Google Cloud solutions that can help businesses to better develop and manage their systems, such as Compute Engine, App Engine, and Apigee.
This is the third course in the Cloud Digital Leader series. At the end of this course, enroll in the Understanding Google Cloud Security and Operations course
Optimize Your Infrastructure Management with Terraform for Google Cloud.
This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as a code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building Google Cloud resources using Terraform.
The most automated and scalable managed Kubernetes platform.
Learn how to create and deploy containerized applications on Google Kubernetes Engine (GKE). This GCP-GSGKE: Getting Started with Google Kubernetes Engine course features a combination of lectures, demos, and hands-on labs to help you explore and deploy solution elements —including infrastructure components like pods, and containers.
Are you currently retrenched? If yes, check out our PERKESO EIS: Get Back into the Workforce through Upskilling program.
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
This course is designed for business users, business leaders, and, more generally, decision makers within organizations who are seeking to gain a comprehensive understanding of generative AI and its potential impact on their businesses.
The overall goal of the course is to educate decision makers on the potential impact generative AI can have in their organizations, educate them about generative AI services on Google Cloud and to inspire decision makers to start thinking about what is possible with generative AI technologies.
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.
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.
What is cloud technology or data science? More importantly, what can it do for you, your team, and your business? If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you.
This course defines foundational terms such as cloud, data, and digital transformation. It also explores examples of companies around the world that are using cloud technology to revolutionize their businesses. The course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and aligns them with the Google Cloud solution pillars. But digital transformation isn’t just about using new technology. To truly transform, organizations also need to be innovative and scale an innovation mindset across the organization. The course offers best practices to help you achieve this.
This is the first course in the Cloud Digital Leader series. At the end of this course, enroll in the Innovating with Data and Google Cloud course.
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.
In this course, you’ll learn the fundamentals and best practices of SRE, the importance of adopting an SRE culture, and how SRE can improve collaboration between IT and business leaders—and help the entire organization succeed.
Generative AI is now at the center of transforming how software is designed, built, run, and managed. For developers, generative AI is a powerful tool for making coding more efficient and using APIs, such as the Gemini and PaLM APIs, within their applications.
In this course, you are introduced to how generative AI can be used to make developers more efficient at writing code and implementing new features into applications. You will also explore available models in Vertex AI Model Garden.
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.
This Google Cloud course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
Now RM2,040 – get 15% off this practical LookML data modeling course.
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.
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.
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.