Pregrad

AI Trainer | 2-Week AI Training Program Position: AI Trainer / Generative AI Trainer Training Duration: 2 Weeks Engagement: Full-Time / Hourly Basis Target Audience: College Students / Undergraduate Students Mode: Online / Offline / Hybrid Experience: 2+ years preferred in AI/ML, Generative AI, or technical training About the Role We are looking for an experienced and enthusiastic AI Trainer to deliver an intensive 2-week Artificial Intelligence and Generative AI training program for students from reputed colleges. The trainer will be responsible for delivering concept-oriented and hands-on sessions, helping students understand modern AI technologies, develop practical AI skills, and apply AI tools effectively for problem-solving and productivity. The training will primarily cover AI Foundations, Generative AI, Prompt Engineering, AI Productivity, RAG, Agentic AI, Responsible AI, and AI Evaluation. Key Responsibilities Deliver engaging and interactive AI/Generative AI training sessions for college students. Explain complex AI concepts in a simple, practical, and student-friendly manner. Conduct live demonstrations, hands-on exercises, assignments, and practical activities. Design and deliver training aligned with the prescribed curriculum. Encourage students to use AI tools for real-world problem-solving. Conduct doubt-clearing and interactive Q&A sessions. Evaluate student understanding through quizzes, assignments, and practical assessments. Provide feedback and guidance to students throughout the program. Help students understand both the capabilities and limitations of AI systems. Introduce students to industry-relevant AI workflows and tools. Maintain a professional and engaging learning environment. Training Curriculum Module 1: AI Foundations & Generative AI The trainer should cover: Introduction to Artificial Intelligence AI, Machine Learning, Deep Learning & Generative AI Generative AI fundamentals How Generative AI works Foundation Models Large Language Models (LLMs) Understanding tokens, context and model responses AI capabilities and limitations Common applications of Generative AI Real-world use cases of AI Introduction to popular Generative AI tools Practical demonstrations using AI tools Understanding AI-generated content and its limitations Module 2: Prompt Engineering & AI Productivity Students should learn how to effectively communicate with AI systems. Topics include: Fundamentals of Prompt Engineering Prompt structure and components Writing effective prompts Prompt quality and optimization Providing context to AI models Role-based prompting Instruction-based prompting Few-shot prompting Iterative prompting Context setting Prompt refinement and debugging Using ChatGPT effectively AI-assisted problem solving AI for research and information synthesis AI for writing and content creation AI for presentations and documentation AI-assisted coding and development Introduction to GitHub Copilot Productivity workflows using AI Practical prompt-engineering exercises Module 3: Advanced AI Systems The trainer will introduce students to modern AI application architectures. Topics include: Retrieval-Augmented Generation (RAG) What is RAG? Why RAG is required Basic RAG architecture Retrieval and generation concepts Knowledge bases and external data Practical RAG use cases Agentic AI Introduction to Agentic AI AI Agents vs traditional AI systems Components of an AI Agent Agent decision-making Tools and actions Multi-step AI workflows AI agents in real-world applications Introduction to autonomous and semi-autonomous workflows Practical demonstrations of agentic workflows Module 4: Responsible AI & AI Evaluation Students should understand how to use AI responsibly and evaluate AI-generated outputs. Topics include: Responsible AI fundamentals AI ethics Bias in AI systems Bias awareness Hallucinations and inaccurate outputs Privacy and responsible use of AI Output validation Fact-checking AI-generated information Evaluating AI responses Reliability and quality of AI outputs Responsible AI practices Best practices for using AI in academic and professional environments Practical Training Expectations The trainer should ensure that the program is not limited to theoretical lectures. The training should include: Live AI tool demonstrations Prompt-writing exercises Individual and group activities Real-world problem-solving scenarios Mini assignments Case studies AI productivity challenges RAG demonstrations Agentic AI workflow demonstrations AI output evaluation exercises Quizzes and assessments Final practical assignment/project Candidate Requirements Must Have Strong understanding of Artificial Intelligence and Generative AI Hands-on experience with LLMs and AI tools Strong knowledge of Prompt Engineering Practical understanding of ChatGPT or equivalent LLM platforms Understanding of Foundation Models and LLMs Knowledge of RAG fundamentals Understanding of Agentic AI / AI Agents Knowledge of responsible and ethical AI practices Strong communication and presentation skills Ability to explain technical concepts to college students Experience conducting technical training/workshops is preferred Good to Have Experience with tools such as ChatGPT, GitHub Copilot and other Generative AI platforms Familiarity with AI APIs and AI application development Experience building RAG-based applications Experience working with AI Agents or multi-step AI workflows Knowledge of Python and basic software development Previous experience training students from reputed colleges Industry experience in AI/ML or Generative AI Trainer Profile We Are Looking For The ideal candidate should be someone who is: Technically strong Hands-on with modern AI technologies An excellent communicator Comfortable conducting live demonstrations Capable of handling a large student audience Able to make technical concepts easy to understand Comfortable answering student queries in real time Passionate about mentoring and teaching Updated with the latest developments in Generative AI and Agentic AI

Pay: ₹2,500.00 - ₹3,500.00 per hour

Work Location: In person