Unit IV – AI in Research, Generative AI and Prompt Engineering is an Open Educational Resource (OER) presentation developed for the undergraduate AI Fundamentals course. This presentation introduces the use of Artificial Intelligence in experimentation and multidisciplinary research, followed by the fundamentals of Generative AI and prompt engineering. It provides students with an understanding of how AI can support research activities, generate different types of content, and improve interaction with AI systems through well-designed prompts. The PPT covers Generative AI, ChatGPT, Hugging Face, Gemini and other Generative AI tools, Perplexity, Prompt Engineering, the importance of prompt engineering, its role in AI/ML interaction, emerging trends, and future directions in AI. The concepts are explained using simple language, real-world examples, diagrams, workflows, comparison tables, prompt examples, practical applications, case studies, and visual learning approaches. The material is designed for classroom teaching, self-learning, revision, practical exploration, and examination preparation. Topics Covered AI in Experimentation AI in Multidisciplinary Research Applications of AI in Research Generative AI – Introduction ChatGPT Hugging Face Gemini and Other Generative AI Tools Perplexity Prompt Engineering – Definition and Importance Role of Prompt Engineering in AI/ML Interaction Effective Prompt Design Prompt Refinement Emerging Trends in AI Future Directions in AI Responsible Use of Generative AI Learning Outcomes After studying this unit, learners will be able to: Explain the role of AI in experimentation and multidisciplinary research. Describe the basic concept of Generative AI. Identify and explain commonly used Generative AI tools. Understand the purpose and importance of Prompt Engineering. Develop more effective prompts for AI systems. Explain how prompt engineering influences AI/ML interaction. Identify emerging trends and future directions in AI. Use Generative AI tools responsibly for learning and research. Target Audience: Undergraduate students, particularly students studying Computer Science and related disciplines. Educational Use: This resource is intended for classroom teaching, self-learning, revision, examination preparation, and educational reuse in accordance with the OER license specified for the resource. Author:Dr C V KrishnaveniLecturer in Computer ScienceSKR & SKR Government College for Women (Autonomous)Kadapa, Andhra Pradesh, India
Venkata Krishnaveni Chennuru· Zenodo (CERN European Organi...· 0 citations
Unit I – AI and Its Subfields is an Open Educational Resource (OER) presentation developed for the AI Fundamentals course for undergraduate students. This presentation provides a structured introduction to Artificial Intelligence and its major concepts. It covers the definition, objectives, characteristics, history and evolution of AI, Artificial General Intelligence (AGI), industry applications, and challenges of AI. It also introduces the major AI subfields, including Knowledge Engineering, Machine Learning, Computer Vision, Natural Language Processing (NLP), and Robotics. The presentation uses simple explanations, real-world examples, diagrams, flowcharts, comparisons, and visual learning approaches to help students understand fundamental AI concepts. It is designed to support both classroom teaching and examination preparation, with important concepts and examples presented in an easy-to-follow format. Learning Focus Students using this resource will be able to: Understand the basic concepts and evolution of Artificial Intelligence. Explain the characteristics and objectives of AI. Differentiate between Narrow AI and AGI. Identify major applications and challenges of AI. Explain the major subfields of AI. Understand the role of Machine Learning, NLP, Computer Vision, Robotics, and Knowledge Engineering in AI applications. Target Audience: Undergraduate students, particularly first-year Computer Science and related disciplines. Use: This resource may be used for teaching, learning, revision, classroom presentations, and adaptation for educational purposes in accordance with the license specified for this OER. Author:Dr C V KrishnaveniLecturer in Computer ScienceSKR & SKR Government College for Women (Autonomous)Kadapa, Andhra Pradesh, India
Venkata Krishnaveni Chennuru· Zenodo (CERN European Organi...· 0 citations
Unit II – Applications of Artificial Intelligence is an Open Educational Resource (OER) presentation developed for the undergraduate AI Fundamentals course. This presentation introduces the applications of Artificial Intelligence across six important domains: Healthcare, Finance, Retail, Agriculture, Education, and Transportation. It explains how AI technologies are used in these sectors for prediction, automation, decision support, personalization, optimization, and improving efficiency. The PPT presents concepts using simple explanations, real-world examples, diagrams, flowcharts, application workflows, comparison tables, benefits, challenges, and visual learning approaches. It is designed to support classroom teaching, student learning, revision, and examination preparation. Topics Covered AI in Healthcare AI in Finance AI in Retail AI in Agriculture AI in Education AI in Transportation AI technologies used across different application domains Benefits and challenges of AI applications AI-based prediction and decision support Real-world examples and integrated applications Learning Outcomes After studying this unit, learners will be able to: Explain major applications of AI in different domains. Identify how AI supports decision-making and automation. Describe the benefits and limitations of AI applications. Compare AI applications across different industries. Understand the role of AI in healthcare, finance, retail, agriculture, education, and transportation. Target Audience: Undergraduate students, particularly students studying Computer Science and related disciplines. Educational Use: This resource is intended for teaching, learning, classroom presentation, revision, and educational adaptation in accordance with the OER license specified for the resource. Author:Dr C V KrishnaveniLecturer in Computer ScienceSKR & SKR Government College for Women (Autonomous)Kadapa, Andhra Pradesh, India
Venkata Krishnaveni Chennuru· Zenodo (CERN European Organi...· 0 citations
Unit IV – AI in Research, Generative AI and Prompt Engineering is an Open Educational Resource (OER) presentation developed for the undergraduate AI Fundamentals course. This presentation introduces the use of Artificial Intelligence in experimentation and multidisciplinary research, followed by the fundamentals of Generative AI and prompt engineering. It provides students with an understanding of how AI can support research activities, generate different types of content, and improve interaction with AI systems through well-designed prompts. The PPT covers Generative AI, ChatGPT, Hugging Face, Gemini and other Generative AI tools, Perplexity, Prompt Engineering, the importance of prompt engineering, its role in AI/ML interaction, emerging trends, and future directions in AI. The concepts are explained using simple language, real-world examples, diagrams, workflows, comparison tables, prompt examples, practical applications, case studies, and visual learning approaches. The material is designed for classroom teaching, self-learning, revision, practical exploration, and examination preparation. Topics Covered AI in Experimentation AI in Multidisciplinary Research Applications of AI in Research Generative AI – Introduction ChatGPT Hugging Face Gemini and Other Generative AI Tools Perplexity Prompt Engineering – Definition and Importance Role of Prompt Engineering in AI/ML Interaction Effective Prompt Design Prompt Refinement Emerging Trends in AI Future Directions in AI Responsible Use of Generative AI Learning Outcomes After studying this unit, learners will be able to: Explain the role of AI in experimentation and multidisciplinary research. Describe the basic concept of Generative AI. Identify and explain commonly used Generative AI tools. Understand the purpose and importance of Prompt Engineering. Develop more effective prompts for AI systems. Explain how prompt engineering influences AI/ML interaction. Identify emerging trends and future directions in AI. Use Generative AI tools responsibly for learning and research. Target Audience: Undergraduate students, particularly students studying Computer Science and related disciplines. Educational Use: This resource is intended for classroom teaching, self-learning, revision, examination preparation, and educational reuse in accordance with the OER license specified for the resource. Author:Dr C V KrishnaveniLecturer in Computer ScienceSKR & SKR Government College for Women (Autonomous)Kadapa, Andhra Pradesh, India
Venkata Krishnaveni Chennuru· Zenodo (CERN European Organi...· 0 citations
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