• Concept of Data Structures, data objects in Python and debugging.
• List, tuple and important their important methods.
• Dictionary and its important method.
• Sets and its important method.
• Looping, nested techniques technique in data structures.

• Flow control: if, if-else, for, while, range () function, continue, break.
• Understanding classes in Python.
• Using classes for creating data objects as per convenience.
• Introduction to Numpy for Scientific Calculation
• Introduction to OpenCV and important libraries

• Image Processing using OpenCV, Object Detection with OpenCV
• Understanding and processing text data
• Automated Tagging. Semantic Search Algorithms
• Latent Diriclet Allocation or, Topic Modelling, Text classification
• Introduction to NLG (Natural Language Understanding)
• Writing speech-based functions for machines to understand using Python
• Creating a sample trained bot to take human input in English and follow the instructions.
• Introduction to Named Entity Recognition (NER) using LSTM

• Introduction to NLG (Natural Language Generation) for generating meaningful/desired text/sentences
• Understanding Language models
• N-grams
• Hidden Markov Models
• Introduction to Transfer Learning
• Using pre-trained model Transformer Library. (BERT)

Project – Making of Chatbot

Project – Making a Chatbot