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Gen AI Online Training

  • 70 hours of structured Generative AI training designed for beginner to advanced learners
  • Covers Prompt Engineering, Large Language Models (LLMs), RAG, AI Agents, Multimodal AI, and GenAI application development
  • Aligned with current industry trends and enterprise AI adoption requirements
  • Hands-on exposure to leading AI platforms including ChatGPT, Gemini, Claude, Copilot, and Hugging Face
  • Practical implementation of AI-powered chatbots, workflow automation, and intelligent assistants
  • Interactive live sessions led by experienced AI practitioners and industry-certified trainers
  • Hands-on labs using real-world business use cases, datasets, and enterprise AI workflows
  • Capstone project focused on solving real business problems using Generative AI technologies
  • Coverage of AI ethics, governance, security, compliance, and responsible AI practices
  • Continuous learning support with assessments, practical exercises, and guided project mentoring
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    GEN AI Training Program

    Gen AI Online Training

    This program provides an end-to-end foundation in Generative AI — from understanding foundational models to deploying enterprise-grade AI solutions. The curriculum is built for both technical professionals and business leaders looking to harness the power of Gen AI in real-world contexts.

    Course Overview

    Duration
    70 Hours
    Students Enrolled
    62+
    Training Mode
    Live Instructor Training
    Hands-On Projects
    Capstone Projects on Real Time Data
    Trainer Experience
    5+ Years Industry Expert Trainers
    Session Recordings
    Life Time Access
    Post-Training Support
    3 Months

    What You'll Learn

    • Understand the architecture and inner workings of large language models (LLMs), including GPT, Gemini, Claude, and open-source alternatives like LLaMA and Mistral
    • Master prompt engineering techniques — zero-shot, few-shot, chain-of-thought, and advanced prompting strategies for optimized AI outputs
    • Build and deploy AI-powered applications using APIs from OpenAI, Anthropic, Google, and open-source frameworks
    • Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases like Pinecone, Weaviate, and ChromaDB
    • Fine-tune pre-trained models on custom datasets using techniques like LoRA, PEFT, and instruction tuning
    • Develop AI agents and autonomous workflows using tools like LangChain, LlamaIndex, AutoGen, and CrewAI
    • Apply Gen AI to real business use cases including content generation, summarization, code assistance, customer service automation, and document intelligence
    • Understand AI safety, hallucination mitigation, responsible AI practices, and governance frameworks for enterprise deployment
    • Integrate Gen AI into existing enterprise systems via APIs, microservices, and cloud platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI)
    • Evaluate, monitor, and optimize Gen AI model performance using benchmarking tools and evaluation frameworks

    Pro Tip:This Generative AI course is ideal for IT professionals, data scientists, product managers, and business leaders who want to build, deploy, or leverage AI solutions in their organizations.

    Questions about the course? Contact our support team

    Certification Value

    GEN AI Value in Global Market

    Leading global organizations actively hiring Generative AI professionals include Google, Microsoft, Amazon, Meta, Accenture, IBM, Infosys, TCS, Wipro, and hundreds of AI-first startups worldwide.

    50 LPA - 60 LPASalary Range
    Average annual salary for senior Gen AI engineers across the globe are High-demand, high-reward career path.
    45%Job Growth Globally
    Year-on-year growth in Gen AI-related job postings globally. Demand is surging across every sector — from finance to healthcare to manufacturing.
    $100–$200/hrFor Freelancing
    Freelance and consulting rates for experienced Gen AI practitioners, depending on specialization, geography, and project complexity.
    60%+Industrial Growth
    Of enterprise organizations have already piloted or deployed Gen AI solutions as of 2025. Adoption is accelerating rapidly across Fortune 500 companies.
    Top SectorsUsing AI
    BFSI, Healthcare, E-commerce, Legal Tech, EdTech, and Cybersecurity are the leading adopters of Generative AI.

    Course Overview

    Overview

    Generative AI Certification is designed to validate professional skills in using modern AI tools and frameworks to build intelligent applications and automate business workflows. The program equips learners with practical knowledge of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and multimodal AI.

    Generative AI enables professionals to create text, images, code, and automated workflows using tools such as ChatGPT, Gemini, Claude, and open-source models like Llama and Mistral. With minimal coding and the right prompting techniques, users can build AI-powered assistants, chatbots, document search systems, and productivity solutions that solve real business problems.

    This certification-focused training provides hands-on experience with Python, APIs, LangChain, LlamaIndex, vector databases, and deployment tools such as Streamlit and Gradio. Participants learn how to design, develop, and deploy enterprise-ready GenAI applications while applying best practices for responsible AI, data privacy, governance, and model evaluation.

    By completing this program, learners gain the industry-relevant skills needed to leverage Generative AI across domains such as software development, customer support, marketing, operations, finance, and education, making them well-prepared for emerging roles in AI and intelligent automation.

    Gen AI Online Training Curriculum

    Theory Hours: 4 | Lab Hours: 2 | Total: 6 Hours

    Topics Covered

    • Introduction to AI, ML, and Deep Learning
    • Evolution of Generative AI
    • Foundation Models and LLMs
    • Overview of ChatGPT, Gemini, Claude, and Llama
    • Industry applications of GenAIHands-on Labs & Activities
    • Compare outputs from multiple LLMs
    • Identify hallucinations and biases
    • Industry use-case brainstorming activity

    Theory Hours: 4 | Lab Hours: 4 | Total: 8 Hours

    Topics Covered

    • Prompt engineering fundamentals
    • Zero-shot, few-shot, and chain-of-thought prompting
    • Role prompting and system prompts
    • Prompt optimization and evaluation
    • Structured outputs and JSON promptingHands-on Labs & Activities
    • Prompt engineering challenge
    • Build reusable prompt templates
    • Generate structured AI outputs
    • AI persona simulation exercises

    Theory Hours: 4 | Lab Hours: 2 | Total: 6 Hours

      Topics Covered

    • Overview of AI ecosystems
    • AI tools for content, coding, research, and automation
    • ChatGPT, Gemini, Copilot, Perplexity
    • Image generation tools
    • AI workflow integrationHands-on Labs & Activities
    • AI-assisted content creation
    • AI coding assistant exercises
    • Image generation practice

    Theory Hours: 3 | Lab Hours: 5 | Total: 8 Hours

     Topics Covered

    • Python basics for AI
    • Working with APIs
    • Using OpenAI and Hugging Face APIs
    • Environment setup and API management
    • Building AI-powered scriptsHands-on Labs & Activities
    • Build a text summarizer
    • Create a chatbot using APIs
    • Hands-on Hugging Face exercises
    • Mini AI application development

    Theory Hours: 4 | Lab Hours: 4 | Total: 8 Hours

    Topics Covered

    • Transformers, embeddings, and attention
    • Context windows and inference
    • Vector databases
    • Retrieval-Augmented Generation (RAG)
    • Open-source LLM ecosystemHands-on Labs & Activities
    • Create embeddings
    • Build semantic search
    • Simple RAG pipeline implementation
    • Hallucination testing exercise

    Theory Hours: 4 | Lab Hours: 6 | Total: 10 Hours

    Topics Covered

    • Building AI chatbots
    • Document querying systems
    • LangChain and LlamaIndex
    • Workflow automation
    • Deployment basics with Streamlit/GradioHands-on Labs & Activities
    • Build a RAG chatbot
    • PDF document querying application
    • Deploy a simple AI app
    • Workflow automation implementation

    Theory Hours: 3 | Lab Hours: 3 | Total: 6 Hours

    Topics Covered

    • Introduction to AI agents
    • Tool calling and orchestration
    • Autonomous workflows
    • Human-in-the-loop systems
    • Enterprise AI agentsHands-on Labs & Activities
    • Build a simple AI agent
    • Multi-step automation workflow
    • AI research assistant implementation

    Theory Hours: 2 | Lab Hours: 2 | Total: 4 Hours

    Topics Covered

    • Introduction to multimodal AI
    • Vision-language models
    • Speech-to-text systems
    • Document AI and OCR
    • AI image analysisHands-on Labs & Activities
    • Image prompting lab
    • Speech-to-text demo
    • Document AI practical

    Theory Hours: 4 | Lab Hours: 1 | Total: 5 Hours

      Topics Covered

    • LLM evaluation techniques
    • Responsible AI
    • Bias and fairness
    • Data privacy and compliance
    • AI governance frameworksHands-on Labs & Activities
    • Prompt evaluation exercise
    • AI risk assessment case study

    Theory Hours: 1 | Lab Hours: 7 | Total: 8 Hours

    Topics Covered

    • End-to-end GenAI solution design
    • Deployment and presentation
    • Documentation and evaluation
    • Career pathways and portfolio buildingHands-on Labs & Activities
    • Capstone implementation
    • Project deployment
    • Final presentation and demoTools & Technologies Covered
    • ChatGPT
    • Gemini
    • Claude
    • GitHub Copilot
    • OpenAI APIs
    • Hugging Face
    • LangChain
    • LlamaIndex
    • Streamlit
    • Gradio
    • Python
    • Vector Databases
    • Midjourney
    • DALL·E

    Benefits

    • Lifetime access to session recorded videos for future learning

      All recording during the class will be shared with the students for future use.

    • Industry-Recognized Certification Preparation

      Comprehensive preparation aligned with Microsoft standards, providing the 30 hours of dedicated training.

    • FREE Doubt Clearing Sessions

      Weekly & Monthly doubt clearing sessions free of cost

    • Exam preparation Videos

      Get PL-100 exam preparation videos to boost your knowledge on the types of questions you need to prepare for.

    • Study Material

      Additional guides/materials to give you sights into latest updates of Power BI

    Testimonials

    What our Students Say

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    Who Can Take Up the Gen AI Online Training

    Early-Career Professionals & Fresh Graduate

    To build a future-proof skill set aligned with the fastest-growing area of technology, and gain a competitive edge in the job market.

    Data Scientists & ML Engineers

    To expand their skill set into Generative AI, fine-tune large language models, and design end-to-end AI pipelines for production environments.

    Business Analysts & Product Managers

    To understand and harness Gen AI tools for market research, product strategy, content automation, and data-driven decision-making.

    Software Developers & Engineers

    To integrate Gen AI capabilities into existing applications, build AI-native products, and leverage LLM APIs for intelligent feature development.

    Marketing, Content & Operations Teams

    To use Gen AI tools for content creation, campaign automation, customer engagement, and operational efficiency improvements.

    Team Discussion
    Ideal for professionals across multiple domains

    The Generative AI course is relevant and impactful across virtually every industry sector:

    • Information Technology
    • Healthcare
    • Manufacturing
    • Education
    • Construction
    • Finance & Banking
    • Consulting
    • Government
    Pre-requisites to Take Up the Course

    IT Professional Certification

    Pre-requisites to Take Up the Generative AI Course

    • Basic computer literacy — comfortable navigating software applications and using the internet.
    • Fundamental understanding of data concepts — spreadsheets, databases, or data files.
    • Basic familiarity with any programming language (Python preferred) — helpful for the hands-on coding modules.
    • Business domain awareness — understanding of your industry’s processes and data workflows.
    • Curiosity and an analytical mindset — willingness to explore, experiment, and learn

    For Non-Technical Participants
    The program includes dedicated beginner-friendly modules covering Python basics, AI fundamentals, and no-code Gen AI tools. Non-technical professionals will leave fully capable of applying Gen AI in their domain — without writing complex code.

    For Technical Participants
    Developers, data engineers, and ML practitioners will benefit from the advanced modules on model fine-tuning, RAG pipeline design, AI agent development, and cloud-based deployment strategies.

    Ready to Start Your Gen AI Online Training?

    Our comprehensive training program guides you through each step of the certification
    process, ensuring you're fully prepared for success.

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    Why Techvibz?

    Empowering professionals with expert-led training, proven results, and personalized learning experiences that transform careers and drive success.

    Proven Data on Success Rate

    Track record backed by verified success metrics and proven methodology

    12000+ Successful Professionals

    Join a thriving community of alumni and successful career transformations

    Flexible Timing

    Convenient schedules designed specifically for working professionals

    Over 90% Candidates Passed

    Industry-leading pass rate for certification with consistent excellence

    Lifelong Access to Recordings

    Pre-recorded video sessions available forever with unlimited access

    Customised Learning Process

    Tailored approach for diverse professional groups and individual needs

    Real-Life Industry Experts

    Learn from professionals with hands-on experience and practical insights

    Live Interactive Training

    Engage in real-time learning sessions with interactive group participation

    Small Batch Sizes

    One-to-one focused training attention for better learning outcomes