blog.1.image

Artificial Intelligence Internship Course

Concepts Covered

Helps us build ML model , understand data and pre-processing, usage of Classification , regression, AzureML Cheat Sheet, Clustering and relevant case studies; Azure Cloud API.
Helps us learn to Clean data, understand concepts of word frequency, Stemming, Lemmatization, Understand Inverse Document Frequency , word embedding, case studies on Sentiment Analysis.
Understanding of Text Analysis, components of NLP , Introduction to NLTK library for Python and Spacy.
Understanding of RNN and LSTM, Citing real world AI examples.
Discussion of Mini project as a part of curriculum.
Introduction to Bot, Microsoft Bot framework, creating a basic Bot; Usage of ML for Bot Intelligence; Creation of QnA Service, Bot , Learning the Cortana Skills.
Creating , Improvising and Consuming a LUIS App.
Discussion of Minor Project 2 as a part of curriculum.
Introduction to Image Processing Basics, equalization and open CV.
Learning about Filters, Edge Detection, Corner Detection.
Understanding Image Classification, Image Analysis, Face Detection and Recognition.
Discussion of Major Project as a part of curriculum.

Project Titles

1. Speech Recognition
Build a model that can recognize English speech and convert it to Text using Natural Language Processing.
2. Face Detection
Make your machine learn to detect and identify faces using machine learning and computer vision.
3. Chat Bot
Build a chatbot that can mimic a real human and can talk to anyone through chat.
4. Speech to Text
Convert the speech or audio to text using AI models which were taught in the speech to text session.
Icon