
Explore how AI thinks, from encoding and tokenization to tensors and normalization, and compare older intent classifiers with modern generative transformers in chatbot design.
Explore how modern AI uses transformers, attention, and tokenization to build large language models, comparing GPT and BART and outlining pre-training, SFT, reward modeling, and reinforcement learning.
Explore prompt engineering through hands-on coding in Colab, using system, user, and assistant prompts, then deploy OpenAI, Gemini, and local models with GPU or CPU.
Build a chat bot interface with Gradio by wiring a function that returns the assistant response. Launch a public Gradio app and note the 72-hour expiry for free access.
Explore retrieval augmented generation to overcome token limits by splitting text into chunks, retrieving the most relevant passages, and generating answers with a chatbot.
Learn LangChain and LangGraph to build AI systems with multiple agents and tools. Define nodes, edges, and asynchronous calls to orchestrate scalable LLM workflows.
Learn how to evaluate large language model outputs using LangChain evaluation criteria and embedding distance, using LLMs as judges to validate answers against references.
Explore supervised fine-tuning with LoRa adapters to boost model accuracy beyond prompts, including hands-on setup with AutoTrain, Hugging Face, Colab, train.csv, and PEFT workflows.
Learn how to perform full fine-tuning of a translation model from english to bengali using helsinki opus 100, with tokenization and evaluation by blue and chrf, plus gpu considerations.
Explore pre-training a from-scratch chatbot with a BART-based encoder model, including dataset preparation with English and Bengali data, tokenizer setup, vocabulary, and max-length choices to optimize prompts for later fine-tuning.
Apply reinforcement learning with human feedback (rlhf) to train chatbots by rewarding correct or wrong answers, using GRPO with LoRa and the math dataset to fine-tune models.
Build Your Own AI Chatbot: From Foundations to Advanced Deployment
Are you fascinated by the power of AI and curious about how to build a chatbot that can understand, respond, and adapt like a human? This in-depth, project-based course takes you on a complete journey—from the core principles of artificial intelligence to building and deploying your very own intelligent chatbot.
Designed for beginners and intermediate learners alike, this course covers a wide range of modern AI concepts, techniques, and tools that are shaping the future of human-computer interaction.
What You'll Learn:
Core Concepts of AI and NLP
Begin by mastering the fundamentals of Natural Language Processing (NLP), including text preprocessing, tokenization, embedding, attention mechanisms, and transformer architectures. Understand the role of pretraining and how transfer learning makes modern language models highly efficient and task-adaptable.
Large Language Models (LLMs) and Fine-Tuning
Dive into the inner workings of LLMs such as GPT and BERT. Learn how to fine-tune pre-trained models on domain-specific datasets to improve performance and efficiency for real-world applications.
Advanced Prompt Engineering
Discover the art and science of crafting effective prompts that guide LLMs to produce accurate, relevant, and context-aware responses. Explore few-shot and zero-shot learning through prompt design strategies.
Hands-On with Modern Frameworks
Gain practical experience using leading frameworks and tools including Hugging Face Transformers, LangChain, and Gradio. Learn how to build interactive interfaces, chain model outputs, and integrate with external APIs for dynamic responses.
Hardware Acceleration with TPUs
Speed up training and inference using Tensor Processing Units (TPUs) and learn how to set up your own scalable training pipeline using cloud-based resources like Google Colab and Vertex AI.
Efficient Training with LoRA
Implement Low-Rank Adaptation (LoRA) to fine-tune large models with fewer resources. Understand how parameter-efficient training helps in customizing models without full retraining.
Building and Deploying Chatbots
Put everything into practice by building chatbots capable of real-time conversation. You'll implement API integration for knowledge retrieval, create front-end user interfaces, and deploy your bot to the web or cloud environments.
Ethics and Safety in AI
Understand the ethical considerations around AI-generated content, bias in language models, and how to ensure responsible AI usage when deploying your chatbot to real users.
Who Is This Course For?
Developers interested in integrating conversational AI into products
Data scientists and machine learning enthusiasts expanding into NLP
Students or professionals seeking a comprehensive, hands-on LLM course
Entrepreneurs looking to build smart assistants or AI-driven applications
By the end of the course, you will have built a fully functional AI-powered chatbot that can converse fluently, fetch information, and even adapt over time. You’ll walk away with a solid portfolio project, a strong grasp of modern NLP practices, and the confidence to apply these skills in real-world applications.
Enroll today and start building chatbots that can truly think, talk, and learn. Your AI journey begins here.