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Exploring Large Language Models & Google Generative AI Intermediate

The "Exploring Large Language Models & Google Generative AI" course offers a deep dive into the cutting-edge world of AI language and generative technologies. Module 1: Advancements in Language Models introduces learners to the latest developments and the impact they have on various industries. Module 2: Mastering Advanced AI Technologies equips participants with the knowledge to utilize these technologies effectively, while Module 3: Mastering Generative AI provides practical insights into generating text, images, and other media. This course is tailored for professionals seeking to leverage AI for innovation, developers aiming to integrate AI into their projects, and enthusiasts eager to understand the capabilities of machine learning. With a focus on Google's tools and advancements, it prepares learners to excel in the rapidly evolving domain of artificial intelligence and generative AI.

24 Hours (3 Days)
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Course Overview

The Exploring Large Language Models & Google Generative AI course by Google is designed for professionals seeking foundational knowledge in generative AI technologies and their practical applications on Google Cloud. This course supports preparation for the Generative AI Fundamentals learning path, ideal for roles such as AI Solutions Consultants, Cloud AI Specialists, and Technical Project Managers. With 78 percent of enterprises now exploring or deploying generative AI solutions, this Google Cloud Generative AI training equips learners with in-demand skills to lead AI-driven initiatives. It covers core concepts including large language models, prompt engineering, and Google’s AI-first strategy.

Participants engage with key Google Cloud tools such as Vertex AI, Gemini Enterprise Agent Platform, Model Garden, AlloyDB, Cloud Shell, and MCP Toolbox through hands-on labs in a real Google Cloud environment. In one key project, students build a retrieval-augmented generation-based chat application that integrates LLMs with vector databases for semantic search, using AlloyDB for data storage and Gemini Pro for multimodal responses. These labs are delivered via Google Skills Boost, Google’s official hands-on learning platform. The practical exercises emphasize real-world implementation, including configuring AI agents, optimizing model outputs, and securely connecting database operations to generative AI workflows.

Completing this course prepares learners for official Google Cloud credentials, validating expertise in Google Cloud’s generative AI offerings. Certified professionals report faster career advancement in AI strategy and cloud innovation roles, with positions like Generative AI Field Solutions Developer commanding competitive industry salaries. Koenig Solutions enhances this learning journey with Guaranteed-to-Run sessions and official Google Cloud courseware, ensuring structured, instructor-led mastery. By the end, learners are equipped to lead enterprise AI adoption, design responsible AI solutions, and drive digital transformation using Google’s cutting-edge generative AI ecosystem.

What You'll Learn

Architect Large Language Model frameworks and fundamental concepts to engineer scalable, modern AI solutions
Execute practical use cases for Google's Generative AI models by leveraging Vertex AI Studio for content creation and data analysis
Configure prompt tuning workflows to evaluate and improve Large Language Model performance for specific enterprise tasks
Integrate Google Cloud tools, including Model Garden and specific API endpoints, to develop and deploy Generative AI applications
Implement advanced prompt engineering techniques with the Gemini API to execute and enhance AI outputs
Evaluate and optimize prompts using Vertex AI Model Garden and Prompt Optimizer to achieve high-accuracy, relevant model responses

Skills You'll Gain

Generative AI Large Language Models Prompt Engineering Google Cloud AI Vertex AI Platform Gemini API Google AI Studio LLM Prompting RAG Systems Vector Search LLM Fine Tuning Google Vertex AI AI Agents Model Deployment AI Evaluation Metrics Responsible AI

Prerequisites

Recommended knowledge before taking this course
  • Basic understanding of machine learning concepts, including supervised and unsupervised learning.
  • Familiarity with the fundamentals of neural networks and deep learning.
  • Proficiency in at least one high-level programming language, such as Python, which is commonly used in AI development.
  • Ability to handle and preprocess data for AI models, including knowledge of data manipulation tools and libraries.
  • A grasp of the ethical considerations and potential biases in AI applications.
  • Eagerness to learn about the latest advancements in AI and enthusiasm for exploring the capabilities of large language models.
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Certification Exam

Everything you need to know about the Exploring Large Language Models & Google Generative AI certification exam

Exam Details
Exam Name
Exploring Large Language Models & Google Generative AI
Format
Multiple choice, labs & case studies
Questions
Duration
Passing Score
Validity
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Course Curriculum

Structured learning with hands-on labs and real-world scenarios

1
Day 1– Mastering Generative AI Basics
Define Google Generative AI mechanics Contrast discriminative versus generative models Identify high-impact generative AI use cases Leverage Google Cloud AI toolsets Analyze core foundation model architectures Build text-to-text generative applications Develop text-to-image creative solutions Navigate Google Generative AI learning paths
2
Day 2– Exploring Large Language Models
Define Large Language Models (LLMs) architecture Analyze LLM training data sources Apply LLM use cases effectively Master advanced prompt tuning techniques Measure critical model performance metrics Utilize Google tools for LLMs Assess impact of model scaling Recognize key LLM operational limitations
3
Day 3– Advanced Prompt Engineering Skills
Design highly effective prompt structures Apply proven prompt design patterns Execute precise few-shot prompting Implement Retrieval Augmented Generation (RAG) Test prompts within Generative AI Studio Tune prompts via PaLM API Quantify generative response quality Minimize model hallucinations effectively
4
Day 4– Responsible AI and Evaluation
Apply Google's official AI principles Detect latent bias in models Assess fairness in AI outcomes Ensure data privacy in systems Evaluate model explainability standards Use Model Garden for evaluation Monitor ongoing model performance Implement secure, responsible deployment
5
Day 5– Deploying Google Cloud AI
Navigate Generative AI Studio environments Build scalable chat applications Deploy models using Vertex AI Customize enterprise foundation models Integrate search with App Builder Develop image captioning model pipelines Apply encoder-decoder architecture patterns Master essential attention mechanisms

What's Included in Your Training

Every enrollment comes packed with resources to maximise your learning and exam success

Career Outcomes

78%

of Exploring Large Language Models & Google Generative AI certified professionals report career advancement within 6 months

Salary Impact

+16%

Average salary increase reported after obtaining the Exploring Large Language Models & Google Generative AI certification

Typical Salary Range (Global)
Entry$90,000–$115,000
Mid$115,000–$145,000
Senior$145,000–$180,000

*Source: Glassdoor / LinkedIn 2025

Job Roles

6
  • Generative AI Engineer
  • AI/ML Engineer specializing in Gen AI
  • Cloud AI Developer
  • Prompt Engineer
  • Solutions Architect for AI/ML
  • AI Strategy Consultant

Companies Hiring

5,000+
Google Accenture Deloitte Infosys Wipro Capgemini Goldman Sachs Johnson & Johnson Salesforce Intel

and 5,000+ organizations worldwide seeking Exploring Large Language Models & Google Generative AI certified professionals

Real Transformations

Course Student Reviews

Real results from IT professionals who trained with Koenig — rated 4.9/5 from 18,400+ verified reviews.

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  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

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    CISO, Financial Services

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  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

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    Business Intelligence Lead

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    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

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    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

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    SC-300 Certified ✓ Verified
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    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

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    AI Engineer

    AI-102 Certified ✓ Verified
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    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

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    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified

Frequently Asked Questions

Everything you need to know about the Exploring Large Language Models & Google Generative AI training course

Is a certification exam included in the Exploring Large Language Models & Google Generative AI course, and what is the fee?
The Exploring Large Language Models & Google Generative AI course by Google does not include a formal certification exam. It is part of the Google Cloud Skills Boost non-technical, introductory path. There is no exam fee. You earn a verifiable skill badge upon successful completion.
What training formats are available for this course, and does Koenig Solutions offer Guaranteed-to-Run scheduling?
Koenig Solutions offers Exploring Large Language Models & Google Generative AI in live instructor-led, classroom, 1-on-1, and Flexi self-paced formats. All sessions are Guaranteed-to-Run regardless of enrollment size. You receive expert-led instruction aligned with official Google content, ensuring your training schedule remains secure and reliable.
How long is lab access provided, and what environment is used for hands-on exercises in this course?
You receive 6 months of lab access via the Koenig LET Platform. You will use Google Cloud-hosted sandbox environments. These labs require zero local setup. You gain direct, real-time experience with Vertex AI, Model Garden, and PaLM API, mastering essential generative AI workflows.
What is the rescheduling and cancellation policy for this Koenig Solutions training course?
Koenig allows one free reschedule if requested over 7 days before the start date. Changes within 7 days incur a 50% fee. You cannot reschedule the same course twice. Written notice is required. Cancellations made 7 days prior qualify for full refunds, ensuring flexibility.
What is the format, duration, and passing score for the assessment in this course?
The course features a 90-minute challenge lab rather than a traditional exam. You perform hands-on tasks in the Google Cloud Console. You must demonstrate skills in prompt design, Model Garden evaluation, and Generative AI Studio. A score of 80% is required for completion.
How long is the skill badge valid, and what is the renewal process and cost?
The Google Cloud Skills Boost skill badge earned from Exploring Large Language Models & Google Generative AI does not expire. There is no renewal requirement or recurring cost. This digital credential remains valid indefinitely, allowing you to showcase your foundational AI expertise on professional platforms.
What post-training support does Koenig provide after completing the Exploring Large Language Models & Google Generative AI course?
Koenig provides 6 months of lab access, class recordings, and 30 days of expert mentor support. You also gain our Happiness Guarantee, which includes a free course retake within one year. This ensures you master Google’s generative AI tools for long-term career success.
What prerequisites or prior experience are recommended for enrolling in this course?
No technical prerequisites exist for Exploring Large Language Models & Google Generative AI. It is perfect for professionals in sales, HR, marketing, or operations. While basic cloud familiarity helps, the course provides introductory, non-code content to build your foundational knowledge of LLMs.
What career impact or salary benefits can learners expect after completing this course?
Completing this course boosts your profile for AI-driven roles. Google Cloud-skilled professionals earn median salaries of $124,212. This foundational training prepares you for advanced positions in AI product management and strategy, significantly increasing your employability in the fast-growing generative AI sector.
How does instructor-led training from Koenig compare to self-study options for this course?
Koenig’s instructor-led training provides real-time guidance and interactive Q&A, unlike independent self-study. With guaranteed lab access, 30 days of mentorship, and retake options, Koenig ensures higher retention. This structured approach is ideal for learners who value accountability and personalized expert support.
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