UGD in Generative AI

DETAILED COURSE OUTLINE

Course 1: Introduction to Generative AI
Generative AI Basics , Introduction Generative AI, Generative AI vs Traditional AI, Types of generative models: GANs, VAEs, Introduction to Generative Adversarial Networks (GANs), Practical Applications Gen AI.Creating Art with Generative Models, Generating images using GANs, Exploring creative applications of generative AI, Text Generation.

Course 2: Python Programming for Generative AI
Python for Gen AI. Introduction to Python: Basic programming concepts, Data Types, Data dictionaries, Functions, Modules and Packages, libraries. Data Manipulation, Data frames and series.Control Structures, Conditional statements (if, elif, else), Loops (for, while), Importing and using modules. Essential Python Libraries for AI, NumPy, Arrays and matrices operations, Pandas,Data cleaning and preprocessing, Matplotlib and Seaborn, Data visualization with Matplotlib.

Course 3:Generative Models and Machine Leaning
Key Concepts Generative Models: Types of Gen AI Models, Explore different model architectures for text, image, video, speech and code generation. Basic concepts in machine learning, Supervise and Unsupervised Learning, classification and Regression.Regression: Linear regression, Linear classification, Logistic regression, Kernel density estimation, Decision tree induction: Learning sets of rules and logic programs. Learning theory, Support vector machines, Clustering and dimensionality reduction.Concepts of Deep learning, Neural networks, Model ensembles.

Course 4:Introduction to Large Language Models
Natural Language Processing (NLP), foundation models of Natural Language Processing (NLP), Introduction large language models (LLM), use cases where they can be utilized, power of Large Language Models (LLMs), popular LLMs like Transformers, BERT, GPT 3.5, PaLM 2 etc. (Selected models may be covered). Practices for training LLMs. Learn models, Key Query Value (KQV) attention, layer normalization, positional encoding, etc. Generative AI enhanced Chatbot: A chatbot using generative AI enabled conversation

Course 5:Generative AI in Cloud Computing
Core Concepts, overview of cloud-based generative AI (GenAI) services. Using Cloud-Based APIs:  Walkthrough of using cloud-based platforms for easy GenAI model access. Introduction AI tools such as Amazon Sage Maker, Google Cloud AI Platform, OpenAI, ChatGPT, IBM Watson, and Microsoft Azure. Introduction to Generative Adversarial Networks (GANs)

Course 6:Generative AI Foundations on Amazon Web Services (AWS)
Fundamentals of AWS, Generative AI Foundations on AWS, AWS Principal AI and Machine Learning, pre-train, fine-tune, and deploy state-of-the-art foundation models on AWS. Key techniques, services, and trends in foundation models.
                                                                                                                     
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PROJECT: The project would focus on undertaking an industry level study for implementation via AI related fields. The solution may be in the form of Web based dynamic application with designing features etc. with some tangible contribution to the Data Science domain. Written report and presentation would be required.