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GenAI: LangChain, Prompt Engineering & Azure OpenAI Beginner

Master Generative AI with this hands-on Open Source training designed for data scientists, AI engineers, and software developers tackling the challenge of deploying scalable, vendor-agnostic AI systems. With 77% of enterprises now adopting generative AI and a global talent gap of 3.2 candidates per open role, this course delivers practical expertise in LLMs, GANs, prompt engineering, and Retrieval-Augmented Generation using tools like LangChain and Hugging Face. Bridge the implementation gap with real-world labs that build deployable AI solutions.

Prepares for the Koenig-certified Generative AI Specialty credential, recognized by over 5,000 organizations including Google, IBM, and NVIDIA. Benefit from Guaranteed-to-Run scheduling and graduate ready to lead AI innovation with a portfolio of production-grade applications that drive digital transformation.

40 Hours (5 Days)
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41+ professionals trained

Training Formats & Pricing

1-on-1 USD 2,150
Dedicated instructor, your schedule Fastest
Public Batch USD 1,700
Group class, fixed schedule Most Popular
Self-Paced USD 199
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Course Overview

The Open Source Generative AI course is designed for developers, AI engineers, and machine learning practitioners seeking to master the end-to-end development lifecycle of open generative AI systems. While there is no single vendor certification tied exclusively to open-source generative AI, this training aligns with industry-recognized practices validated by platforms like Hugging Face and Ollama and prepares learners for roles such as Generative AI Developer, Machine Learning Engineer, and Applied Scientist. According to the 2026 Linux Foundation Tech Talent Report, demand for AI-specific roles has surged with a net hiring effect of +60%, underscoring the growing need for professionals skilled in open models and responsible deployment.

This hands-on course covers core technologies including Hugging Face Transformers, LangChain, Stable Diffusion, Ollama, FAISS, and FastAPI, enabling students to build, fine-tune, and deploy generative AI applications using open-weight models. Learners work in local and cloud-based environments to configure inference servers, implement retrieval-augmented generation (RAG) pipelines, and containerize APIs using Docker. A key project involves building a production-ready AI research assistant that integrates vector databases, model orchestration, and tool calling via the Model Context Protocol (MCP), culminating in a capstone application deployed with FastAPI and evaluated for performance and safety compliance.

Graduates gain practical expertise applicable to real-world AI engineering challenges and are well-prepared for emerging professional recognition in generative AI, including alignment with AWS Certified Generative AI Developer - Professional (AIP-C01) competencies. With U.S. generative AI engineer salaries averaging between $114,000 and $158,000 annually, this training offers strong career advancement potential. Koenig Solutions enhances learning through Guaranteed-to-Run scheduling and access to official courseware, ensuring consistent, high-quality instruction. By mastering open-source innovation, learners position themselves at the forefront of ethical, scalable AI development across industries.

What You'll Learn

✓Implement open-source transformer and diffusion models for advanced Generative AI solutions from Open Source, enhancing your AI capabilities with cutting-edge techniques.
✓Fine-tune large language models (LLMs) using PEFT and QLoRA methods, enabling customization and improved performance in Generative AI applications.
✓Build Retrieval-Augmented Generation (RAG) pipelines with LangChain and vector databases, boosting the accuracy and relevance of your Generative AI outputs.
✓Deploy Generative AI applications efficiently using FastAPI and Docker, reducing deployment time and increasing scalability.
✓Secure open-source Generative AI systems against adversarial attacks, protecting your AI assets and maintaining trustworthiness.
✓Optimize model performance for faster inference and higher accuracy, ensuring your Generative AI solutions meet real-time demands.

Prerequisites

Recommended knowledge before taking this course
  • Proficiency in Python 3.8+ is essential for implementing Generative AI models with Open Source tools.
  • Familiarity with the Hugging Face Transformers library is required for working with modern Generative AI architectures.
  • Experience with deep learning frameworks like PyTorch or TensorFlow is crucial for developing advanced Generative AI solutions.
  • Understanding neural network architectures including Transformers, CNNs, and RNNs enhances your ability to build effective Generative AI models.
  • Knowledge of natural language processing fundamentals such as tokenization, embeddings, and sequence modeling is vital for text-based Generative AI applications.
  • Access to a GPU-enabled environment with NVIDIA CUDA support is required for efficient model training and fine-tuning.
  • Hands-on experience in training and fine-tuning models using datasets within Jupyter Notebooks environments accelerates your learning curve in Generative AI with Open Source.
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Certification Exam

Everything you need to know about the GenAI: LangChain, Prompt Engineering & Azure OpenAI certification exam

Exam Details
Exam Name
Format
Multiple choice, labs & case studies
Questions
Duration
Passing Score
Validity
Retake Policy
Unlimited project iterations
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GenAI: LangChain, Prompt Engineering & Azure OpenAI

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Course Curriculum

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

1
Day 1– Mastering Generative AI and LLMs with Open Source
Configure Development Environments for AI using PyTorch Core Concepts of Generative AI and LLMs Benchmarking and Comparing Leading LLMs Implementing Ethical Generative AI Standards Mastering Prompt Engineering Fundamentals Developing Complex Advanced Prompts Engineering Scalable Text Generation Apps Deploying Interactive Chat Applications with vLLM
2
Day 2– Building Intelligent Search and Image Apps
Developing Search via Vector Databases like Pinecone or Milvus Creating Advanced Image Generation Apps Building Efficient Low-Code AI Solutions with Flowise and LangFlow Integrating Apps Using Function Calling Designing Intuitive UX for AI Systems Securing Enterprise Generative AI Workflows Managing Generative AI Application Lifecycles Implementing Retrieval Augmented Generation RAG
3
Day 3– Open Source Models and Autonomous Agents
Leveraging Open Source Hugging Face Models Building Autonomous Agents with LangChain and CrewAI Fine-Tuning LLMs Using Proven Methods Building Solutions with Small Language Models Optimizing Mistral Family Model Architectures Deploying Meta Family Model Solutions Strategic Model Selection for Business Enforcing Responsible AI Best Practices using LangGraph
4
Day 4– Advanced Fine-Tuning and PEFT (LoRA/QLoRA)
Understanding Parameter-Efficient Fine-Tuning (PEFT) Concepts Implementing LoRA and QLoRA for Model Adaptation Preparing Datasets for Instruction Fine-Tuning Optimizing Training Pipelines with PyTorch and Hugging Face Evaluating Fine-Tuned Model Performance and Benchmarks Quantization Techniques for Resource-Efficient Deployment Managing Model Checkpoints and Versioning Deploying Fine-Tuned Models for Production Inference
5
Day 5– Deployment, Security, and Lifecycle Management
Designing UX for AI Interfaces Mitigating Threats in AI Systems Securing Generative AI Model Deployments Optimizing LLMOps and Lifecycle Tools Executing Robust RAG Framework Implementations Deploying Models via Hugging Face Managing Agent-Based Application Deployments Ensuring AI Safety and Compliance

What's Included in Your Training

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

Career Outcomes

85%

of GenAI: LangChain, Prompt Engineering & Azure OpenAI certified professionals report career advancement within 6 months

Salary Impact

+28%

Average salary increase reported after obtaining the GenAI: LangChain, Prompt Engineering & Azure OpenAI 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 Developer
  • LLM Engineer
  • AI Solutions Architect
  • Prompt Engineer
  • Applied Machine Learning Engineer
  • MLOps Engineer (Generative AI)

Companies Hiring

5,000+
Google Amazon Microsoft IBM Accenture Deloitte Nvidia Meta Salesforce Infosys

and 5,000+ organizations worldwide seeking GenAI: LangChain, Prompt Engineering & Azure OpenAI 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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  • ★★★★★

    “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

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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.”

    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.”

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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.”

    Aisha N.

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    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.

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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 GenAI: LangChain, Prompt Engineering & Azure OpenAI training course

Is the Generative AI certification exam included in the Koenig training cost, and what is the exam fee if separate?
The Generative AI certification exam is not included in your Koenig training fee and requires separate purchase. Official exam costs range from $99 to $300; for instance, the Google Generative AI Leader exam is $99, while the AWS Certified Generative AI Developer - Professional is $300. You must register directly with the vendor.
What training formats does Koenig offer for Generative AI, and is Guaranteed-to-Run scheduling available?
Koenig provides Generative AI training via live online 1-on-1, public instructor-led, and self-paced Flexi formats. All sessions feature Guaranteed-to-Run scheduling. This ensures your class proceeds as planned even with a single registrant, providing reliable, stress-free scheduling for busy professionals across all global time zones.
How long is lab access provided, and what type of environment is used for Generative AI training?
You receive 30 days of lab access for Generative AI training within secure, cloud-based sandbox environments on AWS. These real-world labs allow you to master prompt engineering, RAG pipelines, and model deployment using LangChain and Amazon Bedrock without needing local software configuration.
What is Koenig's rescheduling and cancellation policy for Generative AI training?
Koenig allows free rescheduling of Generative AI training if requested over 10 days before the start. Changes within 10 days incur a 50% fee. Cancellations made 15 days prior qualify for a full refund. Each enrollment permits only one reschedule to maintain your training momentum.
What is the format, number of questions, passing score, and time limit for the Generative AI certification exam?
Generative AI certification exam formats vary by vendor. Google offers 50–60 multiple-choice questions in 90 minutes. Databricks features 45 scored questions in 90 minutes. AWS includes 75 questions over 180 minutes, requiring a minimum scaled score of 750 out of 1,000 for success.
How long is the Generative AI certification valid, and what is the renewal process and cost?
Generative AI certifications typically remain valid for 2–3 years. NVIDIA and Databricks credentials last 2 years, while Google’s lasts 3 years. Renewal requires retaking the current exam at full cost—$200 for Databricks or $300 for AWS—as most vendors do not offer discounted recertification.
What post-training support does Koenig provide after completing Generative AI training?
After your Generative AI training, Koenig offers 30 days of support, including 6 hours of free trainer consultation. You gain 6 months of access to session recordings, 30 days of hands-on lab practice, exam prep tools, and one free course retake within six months to ensure mastery.
What prerequisites or prior experience are recommended for enrolling in Generative AI training?
While no formal prerequisites exist, vendors recommend 6+ months of hands-on experience with AI/ML, Python, and cloud platforms. Koenig’s Generative AI course assumes intermediate technical proficiency, making it perfect for developers, data scientists, and engineers aiming to specialize in LLMs and RAG architectures.
What career impact and salary increase can professionals expect after completing Generative AI certification?
Professionals with Generative AI certification earn average salaries of $145,000 annually. Roles like AI Engineer or Prompt Designer often see 25–40% salary premiums. Certification validates your expertise, accelerates your path to leadership, and meets the urgent industry demand for production-ready Generative AI solution skills.
How does Koenig's Generative AI training compare to self-study options in terms of effectiveness and outcomes?
Koenig’s Generative AI training provides structured, expert-led instruction, guaranteed scheduling, and post-course support that self-study lacks. You benefit from real-time mentorship, 200+ practice questions, and cloud labs that simulate real-world challenges. This approach delivers significantly higher certification pass rates and faster, more reliable skill application.

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