Basics of machine Learning

This course is a comprehensive, hands-on program that equips participants with the knowledge and skills to design, develop, and deploy chatbots using the Python programming language. Throughout the course, participants will learn various techniques and technologies for creating both rule-based and machine learning-based chatbots. It is ideal for individuals interested in chatbot development, aspiring chatbot developers, or professionals aiming to strengthen their Python programming skills within the realms of natural language processing and conversational AI.

Week 1: Introduction to Chatbots and Natural Language Processing

• Understanding the concept and purpose of chatbots

• Overview of natural language processing (NLP) techniques

• Introduction to NLP libraries in Python (NLTK, spaCy)

• Text preprocessing and tokenization

• Building basic rule-based chatbots

Week 2: Building Chatbots with Machine Learning

• Introduction to machine learning-based chatbots

• Training data preparation and annotation

• Building and training a retrieval-based chatbot using scikit-learn or TensorFlow

• Implementing text classification for intent recognition

• Incorporating pre-trained language models (BERT, GPT) into chatbots

Week 3: Creating Chatbots with Deep Learning

• Introduction to sequence-to-sequence (Seq2Seq) models

• Building an encoder-decoder chatbot using recurrent neural networks (RNNs) or transformers

• Implementing attention mechanisms for improved chatbot performance

• Handling context and maintaining conversation history in chatbots

• Evaluating and fine-tuning chatbot models

Week 4: Advanced Chatbot Development and Deployment

• Implementing sentiment analysis and emotion detection in chatbots

• Incorporating entity recognition for information extraction

• Adding conversational context and memory to chatbots

• Deploying chatbots on different platforms (web, messaging apps)

• Best practices for chatbot design, user experience, and user testing