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Report on Guest Lecture “THE BUILDING BLOCKS OF AI: ML AND DL”
The Department of Computer Science and Engineering organized a Guest Lecture for III B.Tech (CSE) students on “THE BUILDING BLOCKS OF AI: ML AND DL” by Mr.E.Nagarjuna, Quality Assurance Engineer, Celigo India Pvt Ltd, Hyderabad, Telangana. The session aimed to enhance the knowledge of students on Machine Learning and Deep Learning building blocks. Around 136 students of III B.Tech (CSE) actively participated in the guest lecture held on 6-09-2025. The session was well-received, and students appreciated the practical insights shared by the expert.
Introduction
A guest lecture on “The Building Blocks of AI: ML and DL” was organized to provide students and faculty with a deeper understanding of the core concepts of Artificial Intelligence. The session aimed to bridge the gap between theoretical knowledge and real-world applications of Machine Learning (ML) and Deep Learning (DL), two fundamental pillars of modern AI.
Objectives of the Session
* To introduce the basic concepts and evolution of Artificial Intelligence.
* To explain how Machine Learning serves as the foundation for intelligent systems.
* To demonstrate the role of Deep Learning in handling complex data such as images, videos, and natural language.
* To highlight practical applications and career opportunities in AI, ML, and DL.
Key Highlights of the Lecture
- Foundations of AI:
* Overview of AI history and its current impact on various industries.
* Distinction between AI, ML, and DL.
- Machine Learning Essentials:
* Supervised, Unsupervised, and Reinforcement Learning techniques.
* Importance of data pre-processing, feature selection, and model evaluation.
* Use cases such as predictive analytics, recommendation systems, and fraud detection.
- Deep Learning Insights:
* Introduction to Artificial Neural Networks (ANNs).
* Explanation of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).
* Applications in computer vision, natural language processing, and autonomous systems
- Industry Relevance:
* Real-time examples from healthcare, finance, robotics, and autonomous vehicles.
* Tools and frameworks like TensorFlow, PyTorch, and Scikit-learn.
- Interactive Session:
* Q\&A on project ideas and career paths in AI.
* Discussion on ethical considerations and challenges in AI adoption.
Outcome of the Lecture
The session enhanced participants’ understanding of how Machine Learning algorithms and Deep Learning architectures form the **building blocks of AI**. Attendees gained valuable insights into practical implementation, current trends, and the immense opportunities in the AI domain.
The guest lecture was highly informative and engaging, sparking curiosity and motivation among students to explore AI, ML, and DL further. The session successfully combined theoretical concepts with practical applications, offering a strong foundation for future learning and research.
Program Coordinators:
- SIVA NAGAMANI, ASSOC PROFESSOR, AI&ML
- DIVYA SRUTHI, ASST PROFESSOR, CSE
