Comprehensive overview of Artificial Intelligence (AI), focusing on the foundational principles, methodologies, and applications that define this dynamic field. It aims to equip students with a solid understanding of AI concepts, techniques, and their implications in the real world. Through lectures, readings, assignments, and hands-on workshops, students will explore the landscape of AI, including its history, ethical considerations, and future directions.

This course offers a deep dive into Python programming tailored for Artificial Intelligence (AI) applications. It bridges the gap between foundational Python programming skills and the specialized knowledge required to design, develop, and deploy AI solutions. Through detailed exploration of Python's capabilities, libraries, and frameworks, students will gain the skills to effectively utilize Python in AI projects, ranging from data analysis and machine learning to deep learning and natural language processing.

This course delves into the heart of Neural Networks and Deep Learning, offering an in-depth exploration of the concepts, architectures, and techniques that constitute the backbone of modern artificial intelligence. It aims to provide students with a robust understanding of how deep learning models are constructed, trained, and applied across a range of domains including image recognition, natural language processing, and beyond. Through engaging lectures, comprehensive readings, assignments, and hands-on workshops, students will gain practical experience and theoretical knowledge, preparing them for advanced applications and research in AI.

This course offers an in-depth exploration of data-driven AI applications, focusing on the use of machine learning and deep learning techniques to harness the power of data for solving complex problems. Students will gain hands-on experience with data preprocessing, model development, and deployment strategies to build efficient AI systems. The curriculum is designed to provide a comprehensive understanding of the latest tools and technologies in AI, emphasizing practical skills and real-world applications.

This course offers a deep dive into Natural Language Processing (NLP), a pivotal area of Artificial Intelligence that focuses on the interaction between computers and humans through natural language. The curriculum is designed to provide students with a comprehensive understanding of both theoretical concepts and practical applications of NLP. Through engaging lectures, readings, assignments, and hands-on workshops, students will learn about the algorithms, tools, and systems used to process, analyze, and generate human language. The course also covers recent advancements and research trends in NLP, preparing students for innovative developments in the field.

This course offers an in-depth exploration of the infrastructure required to support Artificial Intelligence (AI) computing, emphasizing the hardware and software components critical for AI workloads. Students will gain insights into the architecture, configuration, and management of AI computing resources, including GPUs, TPUs, cloud and edge computing environments. Through lectures, case studies, and hands-on workshops, participants will learn how to design and deploy scalable AI infrastructure that meets the demands of modern AI applications, ensuring efficient processing and optimal performance.

This course provides an in-depth exploration of Large Language Models (LLMs), focusing on their architecture, computational mechanisms, and practical applications. It covers the theoretical foundations, design principles, and the latest advancements in the field. The curriculum is designed to offer students a comprehensive understanding of how LLMs are built, trained, and deployed, including discussions on ethical considerations and future trends. Through lectures, readings, assignments, and hands-on workshops, students will gain valuable insights into the inner workings of LLMs and their transformative potential across various domains.

This course offers an in-depth exploration of data processing techniques and methodologies essential for working with large language models (LLMs). It covers the spectrum of data acquisition, cleaning, preparation, and optimization to effectively train and utilize LLMs. Students will gain hands-on experience with real-world datasets, learning how to manage and process data to meet the specific requirements of LLMs. Through theoretical lectures, case studies, and practical workshops, the course aims to build a comprehensive understanding of the challenges and best practices in data processing for LLMs, preparing students for advanced applications and research in this field.

Dedicated to the critical evaluation of Large Language Models (LLMs), this course delves into methodologies for assessing their performance, fairness, and societal impact. It equips students with the skills needed to conduct thorough evaluations of LLMs, understand their limitations, and consider their ethical implications. The curriculum is designed around interactive lectures, case studies, and hands-on workshops, enabling students to engage with current research and practical evaluation techniques.

Diving deep into the specialized domain of Large Language Models, this course is tailored to shed light on the cutting-edge techniques and challenges of training LLMs. It aims to equip learners with both theoretical knowledge and practical skills essential for navigating the complexities of LLM training processes. From understanding the foundational architecture to mastering the nuances of dataset preparation, model training, fine-tuning, and ethical considerations, students will embark on a comprehensive journey through the lifecycle of LLMs. This course is designed for those aspiring to contribute to advancements in natural language processing and AI by harnessing the power of large-scale models.

Focused exclusively on optimizing Large Language Models (LLMs), this course targets the enhancement of model efficiency, accuracy, and scalability through advanced optimization techniques. It offers a deep dive into the methodologies for improving computational efficiency, managing data effectively, and refining model architectures to meet the demands of diverse applications. Students will engage with the latest tools and practices for fine-tuning LLMs, addressing challenges in training large-scale models, and implementing strategies for sustainable and ethical AI development.

Dive into the forefront of artificial intelligence with this advanced course on Emerging Trends in Large Language Model (LLM) Development. Designed for students and professionals eager to master the latest breakthroughs and methodologies in LLMs, this course highlights the innovative architectures, ethical AI development, and the transformative impact of LLMs across sectors. Through engaging lectures, cutting-edge case studies, and interactive workshops, participants will explore the nuances of next-generation model design, implementation strategies, and the ethical framework guiding responsible LLM development. Prepare to navigate the complexities of LLMs and contribute to the evolution of AI technologies.

"Aligning Large Language Models (LLMs) with Preferences" delves into the specialized field of developing LLMs that can understand, interpret, and incorporate human preferences into their operations. This course is dedicated to exploring the intersection of advanced AI technologies and human values, aiming to ensure that LLMs act in ways that are beneficial and aligned with human ethical standards. It encompasses theoretical frameworks, algorithmic strategies, and practical methodologies for embedding human preferences into LLMs, with a strong emphasis on ethical considerations, user-centric design, and societal impact.

This course provides an in-depth exploration of the security aspects of Large Language Models (LLMs), covering theoretical foundations, practical security measures, and ethical considerations. It is designed to equip students with the knowledge and skills needed to understand, analyze, and fortify LLMs against various types of vulnerabilities and threats. Through a blend of lectures, readings, assignments, and hands-on workshops, students will delve into the intricacies of securing LLMs, including data privacy, model integrity, adversarial attacks, and mitigation strategies, preparing them for challenges in the rapidly evolving field of AI security.

This specialized course delves into the deployment of Large Language Models (LLMs), providing a deep dive into the strategies, tools, and considerations essential for successfully integrating LLMs into various applications. It is designed to bridge the gap between theoretical knowledge of LLMs and their practical application, focusing on deployment frameworks, performance optimization, ethical considerations, and real-world case studies. Students will learn how to navigate the complexities of deploying scalable, efficient, and responsible LLM solutions in diverse environments.

This course offers an in-depth exploration of AI-generated content (AIGC), covering the technologies, methodologies, and innovative practices shaping the creation of digital content through artificial intelligence. Students will gain insights into the evolution of AIGC, its impact across various media, and the ethical considerations it entails. Through theoretical understanding and practical workshops, the course aims to provide a comprehensive understanding of how AI technologies are employed to generate text, images, audio, and video content, preparing students for the future of content creation.

Dive into the world of AI-driven image generation and synthesis with AIGC-102. This course covers the spectrum of technologies and methodologies enabling the creation of artificial imagery, from foundational models to cutting-edge techniques. Students will gain hands-on experience with tools like Stable Diffusion, ControlNet, DreamBooth, LoRA and explore advanced topics such as 3D image transformation and semantic typography. Designed for both creative and technical growth, the course aims to foster an in-depth understanding of image synthesis, ethical considerations, and practical applications in various industries.

This course provides an in-depth exploration of AI-driven audio generation, focusing on the techniques, tools, and applications that enable the creation of music, speech, and sound effects using artificial intelligence. It covers the latest advancements in AI audio technologies, including text-to-speech, music generation, vocal synthesis, and sound design. Through a blend of theoretical learning and practical workshops, students will gain hands-on experience with cutting-edge AI models and platforms, preparing them for innovative endeavors in the audio industry.

This course offers an in-depth exploration of AI-driven animation techniques, covering the integration of artificial intelligence in animation creation, from foundational concepts to advanced applications. It focuses on state-of-the-art technologies and methodologies that enable the generation and manipulation of animated content through AI. Through a combination of lectures, case studies, and hands-on workshops, the course aims to provide a comprehensive understanding of how AI technologies are transforming the animation industry, enhancing creativity, and opening new possibilities for animators and content creators.

This course provides an extensive exploration into the transformative role of artificial intelligence (AI) in coding and software development. Covering both foundational AI concepts and their practical applications in programming, the course delves into automated code generation, software development process enhancements, and the use of AI-powered tools and platforms. Through a combination of lectures, case studies, hands-on workshops, and projects, students will gain a thorough understanding of how AI technologies can be leveraged to streamline development workflows, improve code quality, and foster innovation in software engineering.

This course provides a deep dive into the ethical and philosophical considerations of Generative Artificial Intelligence (AI), examining the evolving landscape of AI-generated content and its implications on creativity, society, and ethics. It blends theoretical analysis with practical case studies to explore the cutting-edge developments and state-of-the-art (SOTA) research in the field. By addressing critical issues such as AI's role in creativity, copyright challenges, biases within AI models, and the ethical use of AI technologies, the course fosters a comprehensive understanding of the complex relationship between AI and human values.

This course offers an in-depth exploration into the evolving field of Human-AI Interaction (HAII), with a special focus on the latest advancements in AI-generated content (AIGC). It covers the theoretical foundations, design principles, ethical considerations, and practical applications of HAII, providing students with the skills to design, evaluate, and implement AIGC systems. Through a combination of lectures, case studies, and hands-on workshops, participants will learn how to create AI systems that enhance human capabilities and foster positive user experiences.

This course provides an advanced exploration into Multimodal AI, highlighting the integration and synergistic use of multiple data types—text, image, audio, and video—to build sophisticated AI systems. It covers the latest advancements in AI technologies, including Generative AI, transformer models, and neural network innovations, offering insights into creating, analyzing, and deploying multimodal AI systems in various applications. Through a combination of theoretical knowledge, hands-on workshops, and project-based learning, students will engage with state-of-the-art tools and platforms, enabling them to harness the power of multimodal AI for innovative solutions.

This course provides an in-depth exploration of Generative Artificial Intelligence (AI), focusing on the latest research breakthroughs, innovative applications, and their significant impact on various market sectors. It aims to equip students with a comprehensive understanding of generative AI technologies, including Generative Adversarial Networks (GANs), transformer models, stable diffusion models and their applications in creating realistic images, texts, and sounds. Through lectures, case studies, assignments, and hands-on workshops, students will gain insights into the potentials and challenges of deploying generative AI in real-world scenarios.

This course offers an in-depth exploration of generative artificial intelligence (AI) technologies and their transformative impact on educational methodologies, content creation, and personalized learning experiences. It covers the latest advancements in generative AI models, their applications in crafting dynamic and interactive educational materials, and the ethical considerations surrounding their use. Through a blend of theoretical knowledge and practical workshops, students will learn how to leverage generative AI tools to enhance curriculum design, student engagement, and learning outcomes.

This course provides an exhaustive exploration of Generative Artificial Intelligence (AI) and its transformative impact on finance, trading, and investment. It delves into the core technologies of generative AI and their applications in financial analysis, algorithmic trading, portfolio management, and risk assessment. Students will engage with the latest research, tools, and methodologies to understand how AI can generate predictive models, optimize investment strategies, and revolutionize financial decision-making processes.

This course offers an in-depth exploration of Generative AI's revolutionary impact on healthcare, pharmaceuticals, and the medicine industry. It covers cutting-edge technologies and state-of-the-art (SOTA) research developments, focusing on the applications of Generative AI in improving diagnostics, drug discovery, personalized medicine, and patient care. Through a blend of theoretical knowledge and practical workshops, students will learn to harness the power of Generative AI to address complex challenges in healthcare and medicine, understanding its potential to enhance outcomes, reduce costs, and accelerate innovation.

This course offers a deep dive into the transformative role of Generative AI in the entertainment industries, encompassing film, music, gaming, and virtual reality. It covers the cutting-edge techniques and tools that are redefining creativity, production, and audience engagement in these sectors. Through a mix of theoretical insights, case studies, and practical workshops, students will explore the latest developments and applications of Generative AI, learning to leverage these technologies to innovate and create compelling content that captivates and engages.

This course offers an in-depth exploration into the application of generative AI technologies within the manufacturing sector. Focused on the latest state-of-the-art (SOTA) research and industry developments, it covers the fundamentals of generative models, their implementation in manufacturing processes, and the ethical implications of AI deployment. Through a blend of theoretical knowledge and practical workshops, students will learn about the transformative potential of generative AI, from product design and prototyping to optimization of manufacturing operations and supply chain management.

This course offers an in-depth exploration of how generative AI technologies are revolutionizing the e-commerce sector. It covers the latest advancements in AI that enable personalized customer experiences, optimize supply chain operations, and enhance decision-making processes through predictive analytics. The curriculum is designed to provide students with a robust understanding of the principles, applications, and ethical considerations of generative AI in retail and e-commerce contexts. Through a blend of theoretical knowledge and practical workshops, students will learn to harness the power of AI to innovate and transform e-commerce businesses.

This advanced course explores the revolutionary impact of Generative Artificial Intelligence (AI) in the fields of business analytics and market research. It provides a deep dive into cutting-edge generative models and state-of-the-art (SOTA) technologies, to synthesize insights, forecast trends, and create strategic business solutions. Students will learn to harness the power of generative AI to automate analysis, enhance decision-making, and innovate market research methodologies. Through a blend of theoretical knowledge and practical workshops, participants will gain firsthand experience in applying these technologies to real-world business challenges.

This course offers a comprehensive journey into prompt engineering for Large Language Models (LLMs), covering a wide range of foundational concepts, advanced techniques, and essential ethical considerations. Through detailed lectures, interactive hands-on workshops, and insightful case studies, students will learn to optimize LLM interactions for generating text, images, audio, and code, mastering the art of crafting effective prompts and applying state-of-the-art prompting methodologies across various applications. Emphasizing both technical proficiency and ethical responsibility, the curriculum equips students with the skills to employ advanced prompting techniques like zero-shot and few-shot learning, and chain-of-thought prompting, while also instilling an understanding of the ethical implications inherent in AI technology. This holistic approach ensures that graduates not only become adept prompt engineers but also conscientious contributors to the responsible advancement of AI technologies.

This course offers an in-depth exploration of enhancing Large Language Models (LLMs) with Retrieval Augmented Generation (RAG) techniques. It covers the integration of external knowledge sources into LLMs to improve their performance, adaptability, and applicability across various domains. Students will learn about the architecture of retrieval-augmented models, the process of incorporating external databases, and the methodologies for training and fine-tuning these enhanced models. Through theoretical instruction and practical workshops, participants will gain hands-on experience in developing RAG systems, understanding their advantages, and addressing challenges in their implementation. The course aims to provide a comprehensive understanding of RAG's role in advancing LLMs, preparing students to innovate in the field of AI.

This specialized course delves into the cutting-edge integration of Large Language Models (LLMs) with autonomous agents, equipping students with the expertise to create intelligent, self-operating systems capable of sophisticated communication and decision-making. Emphasizing practical applications, the curriculum bridges the gap between theoretical knowledge of LLMs and their deployment in autonomous agents across various sectors, including robotics, customer service, and data analysis. Students will engage with the core technologies, develop LLM-enhanced agents, and tackle the ethical dimensions of their use.