Gen AI & Fundamental TOC
The Generative AI and Fundamental TOC course by Divine Tech Skills is crafted to introduce learners to the exciting world of artificial intelligence while building a strong foundation in Theory of Computation (TOC). This unique course bridges the gap between theoretical computer science and cutting-edge AI applications, empowering learners with both conceptual clarity and hands-on skills.
In the Generative AI module, learners explore how machines can create new content—from text and images to music and code—using models like GPT, GANs, and diffusion models. You’ll learn the core principles behind generative models, their practical uses, and how to build and fine-tune them.
The Fundamental TOC section covers essential topics such as automata theory, formal languages, Turing machines, and computational complexity, helping you understand the theoretical limits of what machines can compute.
This course is ideal for students, developers, and AI enthusiasts who want to grasp both the power of modern AI and the theoretical backbone of computer science. With expert instruction, real-world projects, and career-focused learning, this course prepares you for future roles in AI, ML, and academic research.
Introduction to Generative AI & NLP Fundamentals
Introduction to Generative AI
What is Generative AI?
- How GenAI differs from traditional AI models
- Real-world applications and use cases
- Ethical concerns and responsible AI
- Fundamentals of NLP
Introduction to Natural Language Processing (NLP)
- Key NLP tasks: Tokenization, Named Entity Recognition (NER), Sentiment Analysis
- Understanding Word Embeddings (Word2Vec, GloVe)
- NLP pipelines and pre-trained models (Spacy, NLTK, Hugging Face)
Machine Learning & Deep Learning Fundamentals
- Fundamentals of Machine Learning & Deep Learning
- Supervised, Unsupervised, and Reinforcement Learning
- Basics of Neural Networks and Deep Learning
- Introduction to Transformers and Self-Attention Mechanism
- Understanding Foundation Models
- Overview of OpenAI, Google Gemini, Meta Llama, Mistral, and Claude
- Text, image, and multimodal generation
- APIs and SDKs for GenAI
Working with OpenAI API & Prompt Engineering
Working with OpenAI API
- How to access and authenticate APIs
- Zero-shot, one-shot, and few-shot prompting
- Best practices in writing effective prompts
- Hands-on with NLP and Text Generation
- Implementing NLP tasks (sentiment analysis, text summarization) using Hugging Face
- Building a simple text generation app using OpenAI API
- Basic chatbot implementation
Introduction to RAG and Advanced AI Techniques
- Fundamentals of RAG (Retrieval-Augmented Generation)
- What is RAG, and why is it needed?
- Introduction to vector databases (FAISS, ChromaDB)
- Implementing a simple RAG-based search
Deployment & Final Hands-on Project
- Deployment & Use Cases
- Exploring various deployment strategies for GenAI
- Final hands-on project: Build a GenAI-powered chatbot
- This revised ToC distributes the topics logically, with each day focusing on distinct and manageable segments. It ends with a practical project for hands-on learning.
- In-depth introduction to Generative AI concepts and models (GPT, GANs, Diffusion Models)
- Hands-on projects to build and fine-tune generative models
- Strong foundation in Theory of Computation: automata, languages, Turing machines, and complexity theory
- Blend of practical AI skills and core computer science theory
- Learn how AI models generate text, images, music, and more
- Expert-led sessions with real-world applications and case studies
- Ideal for students, developers, and AI enthusiasts
- Certification upon course completion
- Career-oriented learning with guidance and mentorship
- Prepares learners for roles in AI, ML, and advanced computer science fields
