AI Engineering with GCP Vertex AI

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AI Engineering with GCP Vertex AI

AI Engineering with GCP Vertex AI Workshop

Build and Modernize Applications with AI Engineering with GCP Vertex AI Workshop

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Join the 56-hour AI Engineering with GCP Vertex AI Workshop
Trained by Experienced Professionals in Machine Learning
Explore How Natural Language Processing (NLP) Works
Intelligent Task Assistant using Agentic GenAI on GCP
Building & deploying AI Apps with GCP Vertex AI

Our Key to Exam and Career Success

Guaranteed to Run Workshops

Expert-Led Study Sessions

Networking Opportunities

Flexible Monthly Payment Plans

Real-World Case Studies

Hands-On Project Experience

Group/Corporate Training

Empower teams through training

skill up your team

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Course overview Benefits Prerequisites Curriculum FAQs Contact Course Advisor

Course Overview

Overview of the AI Engineering with GCP Vertex AI Workshop

AI Engineering with GCP Vertex AI Workshop uses Claude models through Google Cloud’s Vertex AI platform. The workshop provides foundational knowledge of AI models and their applications in Gen AI solutions. Professionals will explore various tools and applications to build a platform using a single codebase. Our workshop enables professionals to implement core API features, understand the RAG system, and recognize the architecture.

What is AI Engineering with GCP Vertex AI Workshop?

The AI Engineering with GCP Vertex AI Workshop helps developers, data professionals, and AI enthusiasts build and deploy AI models. Through this workshop, participants will learn prompt engineering, RAG, deployment strategies, and AI model customization. The Agentic AI with GCP Vertex AI and Google Gemini API workshop offers labs and real-world project experiences that help learners gain experience in the Cloud’s AI ecosystems. Professionals will learn the responsible use of AI applications and how to integrate them to ensure confidentiality when developing next-generation AI solutions for diverse business requirements.

What’s Included in the AI Engineering with GCP Vertex AI Workshop?

Professionals with experience in modern technologies offer Simpliaxis’s AI Engineering with GCP Vertex AI Workshop. Professionals can achieve the following benefits from our training:

Training includes interactive learning, simulation, and lab practices
Gain hands-on experience building and deploying AI
Project setup & planning the use case and defining personas set up
Understand the architecture and examples of MoE models
Working with Gemini API and GenAI SDK

What are the Skills Covered in AI Engineering with GCP Vertex AI Workshop?

The AI Engineering with GCP Vertex AI Workshop provides in-depth knowledge of LangChain & LlamaIndex for RAG App development. Our course enables professionals to achieve skills like:

Comprehensive knowledge of the GCP Vertex AI Platform
Learn actual implementation, including codes and demonstrations of Vertex AI
Construct and implement AI Agents with Google ADK
Utilize GCP Vertex AI for model training with AutoML and Custom Training
GCP AI Agent Builder with actual illustrations
Explore AutoML- Google's low-code/no-code machine learning solution
Generative AI with Google Cloud - A comprehensive overview
Utilize Vertex AI Endpoints for model deployment
Gain the fundamentals of Machine Learning and Generative AI

What are the Modes of this AI Engineering with GCP Vertex AI Workshop?

Simpliaxis provides AI Engineering with GCP Vertex AI Workshop through live, instructor-led online sessions, allowing professionals to learn from anywhere with real-time guidance and interaction.

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AI Engineering with GCP Vertex AI Training Highlights

What are the Key Highlights of AI Engineering with GCP Vertex AI Workshop?

Key features of the AI Engineering with GCP Vertex AI course are listed below:

56 hours of Interactive and Simulation-Based Learning

Pre-assessment and Post-assessment MCQs

Include an Extensive Curriculum with Vertex AI, AutoML, and TensorFlow

Practical Learning with Engage in Authentic AI Projects and Lab

Flexible Learning Alternatives Available Worldwide

Prepare for Google Cloud AI Certification Assessments

Google Agent Development Kit, Langgraph, LangChain, Langflow

Design Intelligent Test Workflows that Accelerate Software Delivery

Vertex AI Workbench & TensorBoard

1:1 Mentorship and Career Support

24/7 Learning Support & Assistance

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Career upliftment

Boost Your Career with the AI Engineering with GCP Vertex AI Workshop

What are the Learning Outcomes of AI Engineering with GCP Vertex AI Workshop?

Establish and authenticate Claude via Vertex AI via the Anthropic SDK.
Choose suitable Claude models considering the trade-offs of intelligence, speed, and cost.
Compose and rigorously assess prompts with objective grading criteria.
Execute a tool for web searching, file manipulation, and other functionalities.
Construct RAG pipelines utilizing text segmentation, embeddings, and hybrid search methodologies.
Utilize advanced functionalities such as extended reasoning, references, and fast storage.
Integrate Claude with external services via the Model Context Protocol (MCP).
Develop workflows for established task sequences and agents to provide adaptable problem-solving.

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AI Engineering with GCP Vertex AI Practice Test

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Sample Papers
Time-Limited
Comprehensive Explanation
Previous Exams

Benefits focused on Individuals and corporate

What are the Benefits of getting AI Engineering with GCP Vertex AI Training?

Individuals Benefits

Enhanced Career Opportunities: Gain in-demand AI and machine learning skills using Google Cloud Vertex AI, making you highly attractive to employers seeking professionals capable of building and deploying enterprise-grade AI solutions.
Hands-On Practical Expertise: Learn to design, train, deploy, and manage machine learning models on a leading cloud platform, enabling you to solve real-world business challenges efficiently and effectively.
Higher Earning Potential: AI and cloud engineering professionals are among the highest-paid technology experts. Vertex AI training can help you qualify for advanced roles with competitive compensation packages.
Industry-Recognized Skill Development: Develop expertise in Google Cloud’s AI ecosystem, strengthening your professional credibility and helping you stay relevant in the rapidly evolving artificial intelligence landscape.

Corporate Benefits

Accelerated AI Adoption: Trained employees can quickly develop and deploy AI solutions using Vertex AI, reducing implementation time and helping organizations achieve faster digital transformation outcomes.
Improved Operational Efficiency: Teams can automate repetitive processes, optimize workflows, and leverage predictive analytics to improve productivity, reduce costs, and enhance overall business performance.
Better Data-Driven Decision Making: Vertex AI enables organizations to extract actionable insights from large datasets, empowering leaders to make informed decisions that support strategic business growth.
Scalable and Secure AI Solutions: Organizations benefit from cloud-native AI applications that are scalable, reliable, and aligned with Google Cloud’s security standards, ensuring sustainable innovation and business continuity.

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Common attendees

Who usually attend AI Engineering with GCP Vertex AI Training

ML leads/ engineers
Data scientists
Software Architects & developers
Cloud architects & engineers

Prerequisites for AI Engineering with GCP Vertex AI certification training

What Prerequisites Are Required for AI Engineering with GCP Vertex AI Workshop?

Basic knowledge of Python programming, including ML & data processing related packages- sklearn, numpy, pandas, matplotlib.
Participants must have basic knowledge of JSON and a Google Cloud account with Vertex AI access.

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Steps to get the AI Engineering with GCP Vertex AI Course:

Enroll:

Attend the AI Engineering with GCP Vertex AI Workshop with Simpliaxis.

Attending Workshop:

Complete all 56 hours of live, intensive lab-based training.

Learning:

Our experienced trainers will provide comprehensive training with real-world scenario-based learning.

Hands-On Experience:

Participants will gain access to hands-on workshops and AI strategy labs.

Curriculum

Module 1: Fundamentals- Generative & Agentic AI

Machine Learning- Supervised & Unsupervised methods with examples, use cases
Demo- Building a supervised learning model - Classification in Python
Deep Neural Networks - How it works, Applications
Natural Language Processing (NLP) - How it works, Applications
Transformers for NLP - How it works, Applications
Artificial General Intelligence (AGI), Narrow AI, and Generative AI
Large Language models (LLMs), Small Language models (SLMs), and how they are developed
Mixture-of-Experts architecture and examples of MoE models
Overview of Proprietary and Open-Source LLMs, including Google Gemini, Gemma, and Meta Llama
LLM Mechanics - Context window, token limit, tokenization, vector embeddings
4 ways of working with LLMs- Prompt Engineering, Fine-tuning, RAG, AI Agents
RAG- Concept, baseline architecture, data pipeline, use case examples
Improving accuracy/ performance of RAG/ RAG Evaluation - Reranking, Chunking strategies, RAGAS
LangChain & LlamaIndex for RAG App development
Types of RAG Architectures
Basics of AI Agents/ Agentic AI
Agentic AI Design patterns- Reflection, Planning, Tool use, Multi-agent collaboration
AI Agents interacting with 3rd party apps via MCP Servers, Tools
Business use cases and examples of AI Agents
Application of AI Agents in SDLC (Cursor/ GitHub Copilot)
Q&A
Lab 1: Subword Tokenization
Lab 2: Multimodal Embeddings

Module 1: Fundamentals- Generative & Agentic AI

Machine Learning- Supervised & Unsupervised methods with examples, use cases
Demo- Building a supervised learning model - Classification in Python
Deep Neural Networks - How it works, Applications
Natural Language Processing (NLP) - How it works, Applications
Transformers for NLP - How it works, Applications
Artificial General Intelligence (AGI), Narrow AI, and Generative AI
Large Language models (LLMs), Small Language models (SLMs), and how they are developed
Mixture-of-Experts architecture and examples of MoE models
Overview of Proprietary and Open-Source LLMs, including Google Gemini, Gemma, and Meta Llama
LLM Mechanics - Context window, token limit, tokenization, vector embeddings
4 ways of working with LLMs- Prompt Engineering, Fine-tuning, RAG, AI Agents
RAG- Concept, baseline architecture, data pipeline, use case examples
Improving accuracy/ performance of RAG/ RAG Evaluation - Reranking, Chunking strategies, RAGAS
LangChain & LlamaIndex for RAG App development
Types of RAG Architectures
Basics of AI Agents/ Agentic AI
Agentic AI Design patterns- Reflection, Planning, Tool use, Multi-agent collaboration
AI Agents interacting with 3rd party apps via MCP Servers, Tools
Business use cases and examples of AI Agents
Application of AI Agents in SDLC (Cursor/ GitHub Copilot)
Q&A
Lab 1: Subword Tokenization
Lab 2: Multimodal Embeddings
Lab 3: Build a Naïve RAG Chatbot for Document Q&A on Colab

Module 2: Building & deploying AI Apps with GCP Vertex AI

Building & deploying AI Apps with GCP Vertex AI
Data Engineering for AI with GCP BigQuery/ other services - Standard practices & Architectures
Working with Gemini API and GenAI SDK
Working with the Gemini 3 family of LLMs
Vertex AI Search- Concept, Architecture, Demo
Vertex AI Agent Builder
LangChain & LlamaIndex for RAG App development
Agentic RAG - Concept, Reference Architecture, Demo
GraphRAG - Concept, Reference Architecture, Demo
AI Infra- GPU VMs, Containerization
Vertex AI Model Catalog
Model deployment using Vertex AI Endpoints
Prediction strategies- batch vs online
Serving models using TF Serving
Monitoring with Vertex AI & custom metrics (incl alerts, logs for serving, inference)
Containerized deployments- Kubernetes, Cloud Run
Deployment optimization using auto scaling, load balancing, etc
Feature comparisons - GCP Vertex AI, AWS Bedrock, Azure AI Foundry
Vertex AI Workbench- Environment setup, experiment management, model deployment - Walkthrough/ demo
Vertex AI Pipelines- Building and orchestrating ML pipelines - Walkthrough/ demo, use case example
Vertex AI Tensorboard- Visualizing model performance and debugging- Walkthrough/ demo
Vertex AI Feature Store- Feature management and serving- Walkthrough/ demo
Vertex AI Model Development and Training - Walkthrough/ demo
Vertex AI Model Monitoring - Drift detection, anomaly detection, performance maintenance
Google Agent Development Kit (ADK) and A2A Protocol for agent-to-agent communication
Agentic Memory- Short & Long term
Agents controlling browser, mouse clicks, and keystrokes
Deep Agents for long-running tasks
AI app deployment & scaling (Model Registry, Endpoints, Batch Inference, Monitoring, Provisioned throughput)
Agentic AI Reference Architectures
Vibe coding with Google AI Studio- AI and deployment on GCP
Working with MCP Servers on GCP
MCP Server Security
Agent Evaluation & LLM-as-judge
Agent Security & Observability
Q&A
Lab 4: Build a data pipeline for training using Dataflow & BigQuery
Lab 5: Working with Vertex AI Search
Lab 6: Working with Vertex AI Agent Builder
Lab 7: Build Multimodal RAG App in GCP
Lab 8: Build Agentic RAG App in GCP
Lab 9: Build GraphRAG App in GCP
Lab 10: Advanced Prompt Engineering with Google Gemini
Lab 11: AI Agent with Google ADK, deploy on GCP
Lab 12: Multi-agent communication with A2A protocol with Google ADK GCP
Lab 13: Agentic Memory
Lab 14: Agent Evaluation
Lab 15: Setting up Langflow in local laptop/ GCP CloudRun
Lab 16: AI Agent use case & spec writing

Module 3: Responsible AI

Responsible AI Framework - AI Ethics, Fairness, Reliability, others with examples
Bias & mitigation
Explainability and Interpretability of models
Model monitoring- drift, bias, fairness
Logging & auditing
AI Safety with Guardrailing
Guardrailing tools - NVIDIA Nemo Guardrails, AWS Bedrock Guardrails (best-in-class amongst cloud providers)
Constitutional AI
Sovereign AI
Global AI Regulations & Guidelines (EU AI Act, California AI Bill, NIST framework, etc.)
Q&A
Lab 17: Guardrailing LLMs for content filtering
Lab 18: Explainable AI

Course Curriculum

AI Engineering with GCP Vertex AI Workshop Curriculum

Download Curriculum

Machine Learning- Supervised & Unsupervised methods with examples, use cases
Demo- Building a supervised learning model - Classification in Python
Deep Neural Networks - How it works, Applications
Natural Language Processing (NLP) - How it works, Applications
Transformers for NLP - How it works, Applications
Artificial General Intelligence (AGI), Narrow AI, and Generative AI
Large Language models (LLMs), Small Language models (SLMs), and how they are developed
Mixture-of-Experts architecture and examples of MoE models
Overview of Proprietary and Open-Source LLMs, including Google Gemini, Gemma, and Meta Llama
LLM Mechanics - Context window, token limit, tokenization, vector embeddings
4 ways of working with LLMs- Prompt Engineering, Fine-tuning, RAG, AI Agents
RAG- Concept, baseline architecture, data pipeline, use case examples
Improving accuracy/ performance of RAG/ RAG Evaluation - Reranking, Chunking strategies, RAGAS
LangChain & LlamaIndex for RAG App development
Types of RAG Architectures
Basics of AI Agents/ Agentic AI
Agentic AI Design patterns- Reflection, Planning, Tool use, Multi-agent collaboration
AI Agents interacting with 3rd party apps via MCP Servers, Tools
Business use cases and examples of AI Agents
Application of AI Agents in SDLC (Cursor/ GitHub Copilot)
Q&A
Lab 1: Subword Tokenization
Lab 2: Multimodal Embeddings

Machine Learning- Supervised & Unsupervised methods with examples, use cases
Demo- Building a supervised learning model - Classification in Python
Deep Neural Networks - How it works, Applications
Natural Language Processing (NLP) - How it works, Applications
Transformers for NLP - How it works, Applications
Artificial General Intelligence (AGI), Narrow AI, and Generative AI
Large Language models (LLMs), Small Language models (SLMs), and how they are developed
Mixture-of-Experts architecture and examples of MoE models
Overview of Proprietary and Open-Source LLMs, including Google Gemini, Gemma, and Meta Llama
LLM Mechanics - Context window, token limit, tokenization, vector embeddings
4 ways of working with LLMs- Prompt Engineering, Fine-tuning, RAG, AI Agents
RAG- Concept, baseline architecture, data pipeline, use case examples
Improving accuracy/ performance of RAG/ RAG Evaluation - Reranking, Chunking strategies, RAGAS
LangChain & LlamaIndex for RAG App development
Types of RAG Architectures
Basics of AI Agents/ Agentic AI
Agentic AI Design patterns- Reflection, Planning, Tool use, Multi-agent collaboration
AI Agents interacting with 3rd party apps via MCP Servers, Tools
Business use cases and examples of AI Agents
Application of AI Agents in SDLC (Cursor/ GitHub Copilot)
Q&A
Lab 1: Subword Tokenization
Lab 2: Multimodal Embeddings
Lab 3: Build a Naïve RAG Chatbot for Document Q&A on Colab

Building & deploying AI Apps with GCP Vertex AI
Data Engineering for AI with GCP BigQuery/ other services - Standard practices & Architectures
Working with Gemini API and GenAI SDK
Working with the Gemini 3 family of LLMs
Vertex AI Search- Concept, Architecture, Demo
Vertex AI Agent Builder
LangChain & LlamaIndex for RAG App development
Agentic RAG - Concept, Reference Architecture, Demo
GraphRAG - Concept, Reference Architecture, Demo
AI Infra- GPU VMs, Containerization
Vertex AI Model Catalog
Model deployment using Vertex AI Endpoints
Prediction strategies- batch vs online
Serving models using TF Serving
Monitoring with Vertex AI & custom metrics (incl alerts, logs for serving, inference)
Containerized deployments- Kubernetes, Cloud Run
Deployment optimization using auto scaling, load balancing, etc
Feature comparisons - GCP Vertex AI, AWS Bedrock, Azure AI Foundry
Vertex AI Workbench- Environment setup, experiment management, model deployment - Walkthrough/ demo
Vertex AI Pipelines- Building and orchestrating ML pipelines - Walkthrough/ demo, use case example
Vertex AI Tensorboard- Visualizing model performance and debugging- Walkthrough/ demo
Vertex AI Feature Store- Feature management and serving- Walkthrough/ demo
Vertex AI Model Development and Training - Walkthrough/ demo
Vertex AI Model Monitoring - Drift detection, anomaly detection, performance maintenance
Google Agent Development Kit (ADK) and A2A Protocol for agent-to-agent communication
Agentic Memory- Short & Long term
Agents controlling browser, mouse clicks, and keystrokes
Deep Agents for long-running tasks
AI app deployment & scaling (Model Registry, Endpoints, Batch Inference, Monitoring, Provisioned throughput)
Agentic AI Reference Architectures
Vibe coding with Google AI Studio- AI and deployment on GCP
Working with MCP Servers on GCP
MCP Server Security
Agent Evaluation & LLM-as-judge
Agent Security & Observability
Q&A
Lab 4: Build a data pipeline for training using Dataflow & BigQuery
Lab 5: Working with Vertex AI Search
Lab 6: Working with Vertex AI Agent Builder
Lab 7: Build Multimodal RAG App in GCP
Lab 8: Build Agentic RAG App in GCP
Lab 9: Build GraphRAG App in GCP
Lab 10: Advanced Prompt Engineering with Google Gemini
Lab 11: AI Agent with Google ADK, deploy on GCP
Lab 12: Multi-agent communication with A2A protocol with Google ADK GCP
Lab 13: Agentic Memory
Lab 14: Agent Evaluation
Lab 15: Setting up Langflow in local laptop/ GCP CloudRun
Lab 16: AI Agent use case & spec writing

Responsible AI Framework - AI Ethics, Fairness, Reliability, others with examples
Bias & mitigation
Explainability and Interpretability of models
Model monitoring- drift, bias, fairness
Logging & auditing
AI Safety with Guardrailing
Guardrailing tools - NVIDIA Nemo Guardrails, AWS Bedrock Guardrails (best-in-class amongst cloud providers)
Constitutional AI
Sovereign AI
Global AI Regulations & Guidelines (EU AI Act, California AI Bill, NIST framework, etc.)
Q&A
Lab 17: Guardrailing LLMs for content filtering
Lab 18: Explainable AI

Download Curriculum

Have more questions or need

personalized guidance?

Contact Learning Advisor

What you will learn in this AI Engineering with GCP Vertex AI workshop

What are the Learning Objectives of AI Engineering with GCP Vertex AI Workshop?

Introduction to Google Cloud AI & Vertex AI & AutoML:

Overview of AI services and GCP architecture. Learn how to build, educate, and deploy machine learning models.

Learn AI APIs & Services:

Our AI Engineering with GCP Vertex AI Workshop enables professionals to explore Vision AI, Natural Language AI, and Speech-to-Text APIs.

MLOps & AI Deployment:

Learn how to automate AI workflows and scale models on GCP.

Develop Coding Skills:

Through our workshop, participants can improve their Python coding skills. end-to-end understanding of creating container-based training and deployment of models.

Deploying Vertex AI:

Deploying a model in Vertex AI Endpoint, Cloud Run, and Google Kubernetes Engine (GKE). Using Colab Enterprise & Workbench Notebooks for training and deployment of models

AI Engineering with GCP Vertex AI Certification Course For Corporates

Why do corporates choose us for the AI Engineering with GCP Vertex AI Workshop?

We at Simpliaxis designed the AI Engineering with GCP Vertex AI Workshop to help organizations build real AI applications for testing automation. Our practical, hands-on AI training is tailored to real-world project environments and helps professionals learn to design, develop, and deploy Vertex AI systems. Therefore, it elevates efficiency, scalability, and precision. Why do organizations choose us:

Our custom training improves productivity and the workforce in the software development industry.
Many employees and groups around the world trust Simpliaxis for their professional development.
Simpliaxis offers significant discounts on group training and additional discounts on advanced courses.

Corporate Group enquiry

Our Customer words for us

Take a Look at Our Clients

What is AI Engineering with GCP Vertex AI Workshop?

The AI Engineering with GCP Vertex AI Workshop provides training on designing, deploying, and managing AI applications through Google Cloud Vertex AI.

Who can enroll in this AI Engineering with GCP Vertex AI Workshop?

Aspiring learners interested in AI and in professions such as software developers, data scientists, AI engineers, and cloud professionals can choose to attend this course.

Is any previous knowledge of AI required to participate in the workshop?

Knowledge of programming AI and coding may be advantageous. But for any participant without prior experience, our experts will teach them the same.

What is Google Vertex AI?

Vertex AI is the unified platform provided by Google Cloud for developing, training, deploying, and managing ML and generative AI models.

Will the AI Engineering with GCP Vertex AI Workshop cover Generative AI and Gemini models?

Yes, participants will learn how to use Gemini models in Vertex AI.

Are there any hands-on activities in AI Engineering with GCP Vertex AI Workshop?

Yes, the workshop includes hands-on activities and lab practice.

Which programming languages are being used in the workshop?

The programming language being used for AI development is Python.

Will you learn how to develop AI agents in this AI Engineering with GCP Vertex AI Workshop?

Yes, the workshop covers AI agents and shows how to create them.

Will I need a Google Cloud account to attend the workshop?

Yes, participants might need a Google Cloud account.

What topics are going to be discussed during the workshop?

Some of the topics that will be covered in the workshop include Vertex AI basics, prompt engineering, Gemini API, and the ethical use of AI.

What happens to my token or partial payment if I don’t enroll immediately?

Token or partial payments will become non-refundable after 15 days from the date of payment.
Any token or partial amount paid can be applied towards enrollment for any available sessions on our website within 6 months of the payment date.

Is there a preferred currency for payment, especially for international students?

While we accept payments in various currencies, we recommend using the currency from where you want to attend the course.

Can payments be made online through your website, or do I need to visit a physical location?

Payments can be made conveniently through our secure online payment portal on our website. We do not require visiting a physical location for payment.

Do you offer any discounts or promotions for early payment?

Yes, we offer discounts and promotions for early payments or certain corporate Training. Keep an eye on our website or contact us to get exciting offers.

Can I pay for the course in installments, or is full payment required upfront?

You have the flexibility to pay for the course either in full upfront or in installments, depending on your preference. To know more details about it contact us.

Will I get a refund if I cancel my enrollment?

No, refund is not possible. You can reschedule your course. To know more about refunds, visit our Refund Policy.

Where will I get my payment receipt?

Upon successful completion of payment, you will receive a confirmation email of your payment along with payment invoices.

Is there any transaction or processing fee?

No, there is no transaction processing fee.

What cards do you accept?

We accept payments from VISA, Master, Maestro, AMEX, and Discover.

What payment options are available?

All types of payment methods are available. You can pay Online through Credit Cards, Debit Cards and Net Banking, Direct Bank Transfer/Wire Transfer/Wallet to our account and many more.Other payment options available are stripe, Splitit, PayPal for US & CA regions.

What if I miss a class? Are there any money back options?

No, you won't get your money back. But, as per your convenience, we can reschedule your training without any extra charges.

If I want to know more about Training, whom should I connect with?

If you want to know more about the course you can connect us in mail hello@simpliaxis.com or you can call us.

Is there any option to complete the Training in the native language if a participant chooses to?

English is the preferred language for training delivery. For corporate Training, any language other than English will have to be requested as a custom service. However, this will be subject to additional costs and the availability of a native language trainer. Please note that only official languages will be considered for this request.

Can I receive personalized Training at my convenience?

Yes, we’ll be posting multiple schedules every week for all the courses. Based on your convenience, you can select the training schedule. Also, we’ve E-Learning programs for popular courses, you can enroll and watch the training modules whenever you want.

Where do I find the upcoming schedules of my course?

Select the course of your interest from the website and view all the upcoming workshop schedules. You can select your course from the website https://www.simpliaxis.com/

After enrollment, can I change the date of my training class?

Yes, you can change the date, but you have to inform it 3-4 days before the Scheduled date.

Do I get any certificate upon completion of the course?

Yes, you will receive a certificate after successful completion of the training course.

How do I enroll in the training course?

Choose the course of your interest, schedule it at your convenience from our upcoming schedule list, and register for the training by submitting your details. Proceed to make a payment and you will receive a confirmation email of your course enrolment. Or you can connect our career advisors to consult & choose your course.

What are the different courses offered by Simpliaxis?

At Simpliaxis we provide training for courses of all the in-demand technologies. One can choose a course from Project Management, Agile, IT, DevOps, Business, IT Service Management, Quality Management, etc based on their choice of interest. To know more, please visit https://www.simpliaxis.com/

What are the different modes of Training available for Simpliaxis courses?

We provide different modes of Training: virtual Online Training, Live Virtual Training, Corporate Training & also E-learning.

Do you offer online Training?

Yes, For every course, online Training is available.

Do you offer corporate Training?

Yes, we do provide corporate Training. We customize Training based on our clients' needs.

Who are the instructors of my course?

All our trainers are highly qualified and certified, having numerous years of experience in the training industry. You can choose your instructors for your course.

Is there any discount available for the Simpliaxis courses?

Yes, we do provide discounts on multiple courses. Please visit the schedules page to view the available discounts.

Whom do I contact if I have more queries regarding my course?

You can reach out to our experienced career counselor
or email us on support@simpliaxis.com
or contact any of our phone numbers
or you can chat with us anytime
or visit our contact us page https://www.simpliaxis.com/contact-us

Are your courses affordable?

Yes, course fees for all technologies are affordable. Along with that, we do provide discounts on various courses.

Why should I choose Simpliaxis?

Simpliaxis offers personalized corporate training programs designed for enterprise teams seeking to refine their employees' skills in various job processes or roles, whether through in-person sessions or live virtual instruction. Led by our skilled and certified trainers, these certification programs not only elevate learning curves but also empower teams to effectively apply their newfound skills to meet industry benchmarks. With over 40 certification programs available, the impact is profound, evident in a remarkable 45% improvement in employee retention rates. On average, there's been a notable 30% enhancement in both work satisfaction and capabilities, showcasing the tangible benefits of our training initiatives.

What is the object of Simpliaxis?

To provide high-quality training and help our professional participants & clients to build a high-performing workforce.

How much discount will I get if I enroll for the Training?

It totally depends upon the course. Please check our website regularly for new offers and discounts throughout the year. You can also chat with one of our career consultants to see if any discounts are available.

AI Engineering with GCP Vertex AI Course FAQs

Frequently Asked Questions on AI Engineering with GCP Vertex AI Workshop