ANU M.Ed 4th Sem Reg Exams April 2025 Revaluation Results are now available, the candidates who are looking for results can check their results from here
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Introduction to Artificial Intelligence (AI Fundamentals)
Artificial Intelligence (AI) has become one of the most transformative technologies of the 21st century, shaping how we live, learn, and work. The “Introduction to Artificial Intelligence (AI Fundamentals)” course is designed especially for undergraduate students to build a strong foundation in the core concepts, applications, and ethical dimensions of AI.
This course introduces students to the history, evolution, and subfields of AI — including Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Robotics, and Knowledge Engineering. It explains how AI systems mimic human intelligence through perception, reasoning, and decision-making.
Learners will explore real-world AI applications across key sectors like healthcare, agriculture, education, finance, and transportation. Beyond technical knowledge, the course emphasizes responsible AI development, addressing crucial topics such as bias, fairness, transparency, privacy, inclusivity, and sustainability in AI systems.
A unique feature of this syllabus is the integration of Generative AI and Prompt Engineering, enabling students to experiment with tools like ChatGPT, Gemini, Hugging Face, and SlidesGPT for content generation, creative design, and interactive learning. These hands-on exercises make the course both engaging and industry-relevant.
By the end of this course, students will:
Whether you’re an aspiring data scientist, a software engineer, or simply curious about how AI works, this course will help you think critically, experiment creatively, and understand the power of intelligent systems.
The three units given in the syllabus is divided in five units for easy understing of students.
Overview: Introduction to AI, historical evolution, definitions, challenges, and subfields.
Introduction to Artificial Intelligence – Definition, Scope & Goals
Major Subfields of AI Explained:
Industry Applications of AI – Healthcare, Agriculture, Education & Beyond
Challenges in Building Intelligent Systems – Data, Ethics, and Resources
Case Study: How AI is Powering Smart Cities and Digital India
Overview: Real-world impact of AI across sectors.
AI in Healthcare – Early Diagnosis & Drug Discovery
AI in Finance – Fraud Detection, Risk Analysis, and Algorithmic Trading
AI in Retail – Recommendation Systems and Customer Analytics
AI in Agriculture – Crop Prediction and Smart Irrigation
AI in Education – Personalized Learning and Virtual Tutors
AI in Transportation – Autonomous Vehicles and Traffic Management
Future of AI Applications – Quantum AI and Edge Computing
Overview: Understanding the social, ethical, and governance aspects of AI.
What Is AI Ethics? Principles Every AI Developer Should Know
Understanding Bias in AI – Causes and Consequences
Fairness in AI Systems – Building Trustworthy Models
Transparency and Explainability in AI Decisions
Accountability and Privacy in Machine Learning Models
Inclusivity and Sustainability in AI Development
Robustness and Reliability – Making AI Systems Safe
Tutorial Add-Ons:
Examples of biased outputs from ChatGPT, DALL-E, etc.
Classroom activity: Detecting gender bias in AI image generation
Overview: Exploring Generative AI tools and their research relevance.
Role of AI in Modern Scientific Research and Experimentation
What Is Generative AI? Understanding ChatGPT, Gemini, and Hugging Face
Generative AI vs Traditional AI – Key Differences Explained
Introduction to Prompt Engineering – The Art of Talking to AI
Prompt Design Strategies: Zero-Shot, Few-Shot, and Chain-of-Thought
Future Trends in AI Research – Multimodal and Federated AI
Hands-on Tutorial: Writing Effective Prompts for Better AI Results
Overview: Practical use-cases of prompt engineering in education, business, and creative domains.
Prompt Engineering in Education – Smart Content Creation & Tutoring
How Businesses Use Prompt Engineering for Marketing and Automation
AI for Creative Writing – Storytelling, Poetry, and Idea Generation
AI for Design and Branding – Using Canva Magic Media & Adobe Firefly
Writing YouTube Video Scripts with AI Tools
Creating PowerPoint Presentations with SlidesGPT and Tome AI
Designing Thumbnails and Visuals with Generative AI
Prompt Engineering for Students – Learn by Doing
Acharya Nagarjuna University (ANU), Nagarjuna Nagar – Guntur, has released a Revised Notification for PG Examinations (Regular & Supplementary) for all P.G. M.A., M.Sc., MHRM, M.Com., MBA, MCA, M.Ed., M.Li.Sc., and Professional Courses for the academic year 2024-25.
Exams are scheduled to commence from 14-11-2025.
The notification applies to:
All PG Programs (M.A., M.Sc., MHRM, M.Com., M.Ed., MBA, MCA, M.Li.Sc.)
Professional Courses: MBA (HA), MBA (HM), MBA (IB), MBA (TTM)
Vocational Programs: M.VOC FP&QM, M.VOC H&LC, M.VOC H&LG
PG Diploma: Analytical Chemistry Techniques for Pharmaceuticals
M.Sc Nano-Technology, Soil Science & Agricultural Chemistry, and others
| Event | Date |
|---|---|
| Last date for payment of exam fee without fine | 29-10-2025 (4:00 PM) |
| Last date for payment of exam fee with ₹100 fine | 30-10-2025 |
| Last date for submission of gallies to ANU (Online & Manual) | 31-10-2025 |
| Commencement of PG 3rd Semester Examinations (M.A, M.Sc, MHRM, M.Com, M.Ed, MBA, MCA etc.) | 14-11-2025 |
| Practical Examinations to be completed on or before | 12-12-2025 |
| Last date for submission of Internal / MOOCs / Practical Marks Online | 15-12-2025 |
| Course | Whole Exam Fee (₹) | Single Paper | Two Papers | Three Papers | Four or More Papers | Project/Viva Fee | Betterment |
|---|---|---|---|---|---|---|---|
| M.Tech (Bio-Tech) | 3480 | 860 | 1780 | 2640 | 3480 | 520 | 680 |
| M.A., M.Sc., MHRM, M.Li.Sc. | 980 | 520 | 700 | 860 | 980 | 520 | 680 |
| 5 Years MBA (IB) / M.Sc. Nano Tech | 980 | 520 | 700 | 860 | 980 | 520 | 680 |
| M.Com., MBA, MBA (HA), MBA (TTM) | 1100 | 520 | 700 | 860 | 980 | 520 | 680 |
| Certificate / PG Diploma Courses | 1100 | 550 | 710 | 960 | 980 | 520 | — |
| M.Ed. | 1540 | 550 | 710 | 960 | 1540 | 520 | 680 |
| MCA | 1090 | 520 | 700 | 860 | 980 | 520 | 680 |
All Principals of affiliated colleges must collect the examination fee and upload gallies through the online system on or before 31-10-2025.
Certified copies of candidate lists (course-wise) must be sent along with attendance and “No Dues Certificates.”
Internal and Practical Marks must be uploaded online before 15-12-2025.
Hall tickets will be issued only after verifying eligibility and absence of malpractice.
Students should complete their MOOC’s courses during the current semester as per ANU guidelines.
University Website: www.anu.ac.in
Office: Controller of Examinations, Acharya Nagarjuna University, Nagarjuna Nagar – 522510
Helpline: 0863-2346777