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Overview

Working with Generative AI introduces participants to the transformative landscape of artificial intelligence technologies that are reshaping how we create, communicate, and solve problems. This comprehensive program explores the foundational principles and practical applications of generative AI across text, code, and visual domains. Participants will gain hands-on experience with leading AI platforms and develop the skills needed to effectively harness these powerful tools in their professional workflows.

The course offers an immersive journey through the evolution of AI systems, from traditional rule-based approaches to cutting-edge large language models. By combining conceptual understanding with practical implementation, participants will learn essential prompt engineering techniques, creative applications, and ethical considerations. The curriculum bridges theoretical knowledge with real-world use cases, empowering professionals to leverage generative AI tools for enhanced productivity, innovation, and problem-solving.

Cognixia’s Working with Generative AI program stands at the intersection of technological literacy and practical application. Participants will not only gain proficiency in using popular generative AI platforms like ChatGPT, DALL·E, and GitHub Copilot but will also develop a nuanced understanding of how these technologies function and their appropriate use cases. The course goes beyond basic tool familiarity by introducing critical perspectives on AI ethics, bias mitigation, and responsible deployment, preparing professionals to navigate the rapidly evolving landscape of generative AI with confidence and integrity.

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What you'll learn

  • Master effective prompt engineering techniques to elicit precise, useful outputs from generative AI models
  • Leverage AI tools for content creation, including writing, marketing materials, and creative projects
  • Implement AI-powered coding assistants to streamline software development and debugging processes
  • Create compelling visual content using image and video generation platforms like DALL-E, Midjourney, and Sora AI
  • Apply generative AI to enhance data analysis, insight generation, and decision-making processes
  • Navigate ethical considerations and identify potential biases when deploying AI in professional contexts

Prerequisites

Familiarity with common AI tools and platforms like ChatGPT, Midjourney, Dall-E, and GitHub Copilot

Curriculum

  • What is Generative AI?
  • Evolution of AI – From rule-based systems to Large Language Models (LLMs)
  • Overview of key AI models (GPT-4, Dall-E, Stable Diffusion, Claude, and Gemini)
  • Neural networks and deep learning basics
  • Transformer models and attention mechanisms
  • Hands-on: Exploring AI outputs and behavior in OpenAI Playground
  • How AI models generate text (GPT-4, ChatGPT, Claude, and Gemini)
  • Best practices for prompt engineering
  • Using generative AI for software development (GitHub Copilot, OpenAI Codex)
  • Automating code debugging and refactoring with AI
  • AI for visual content creation (Dall-E, Stable Diffusion, Midjourney, Runaway ML)
  • Using AI for video generation (Sora AI, InVideo)
  • AI for content creation: Writing, marketing, and design
  • AI-powered data analysis and insights generation
  • Understanding AI bias and hallucinations
  • Ethical considerations in AI deployment
  • Best practices for responsible AI usage

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Course Feature

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FAQs

Generative AI refers to artificial intelligence systems that can create new content, including text, images, code, audio, and video-based on patterns learned from existing data. Unlike traditional AI that primarily analyzes or classifies information, generative AI produces original outputs that mimic human-created content while extending beyond simple templates or combinations of existing works.
No, programming skills are not mandatory for participants of this Generative AI course. The course is designed to cater to the corporate workforce with varied backgrounds and focuses on practical applications rather than technical implementation. While some familiarity with common AI tools is helpful, the course provides sufficient foundational knowledge for beginners to effectively leverage generative AI systems.
Creating effective prompts involves being specific about desired format and content, providing context and examples, breaking complex requests into manageable steps, using clear language, and iteratively refining prompts based on results. This GenAI course provides extensive hands-on practice with prompt engineering techniques across different AI platforms to help participants develop this critical skill.
Generative AI can dramatically enhance team productivity by automating routine tasks like drafting emails and reports, generating creative content, streamlining code development, creating visual assets, analyzing data patterns, and providing research assistance. The course demonstrates specific workflows and techniques to integrate these capabilities into diverse professional environments for maximum efficiency.