COURSE OVERVIEW

This hands-on, highly-interactive course includes real-life case studies and exercises where participants will be engaged in a series of interactive small groups and class workshops. 

This course is designed to provide participants with a detailed and up-to-date overview of Artificial Intelligence Projects. It covers the data collection, preprocessing, model training and deployment; the challenges in AI projects and how to overcome them; selecting the right AI project and data collection and preprocessing for AI projects; choosing the right AI model for the project; the AI project development tools and frameworks; the object detection and image classification; and the AI for facial recognition, medical imaging, autonomous vehicles, agriculture and satellite image analysis. 

 

Further, the course will also discuss the implementation of chatbot using NLP libraries and using transformer models for chatbots; the sentiment analysis in text, training AI models to detect emotions in tweets and reviews and using LSTMs and transformers for sentiment prediction; implementing text summarization using transformer models; the applications in journalism and document summarization; and evaluating model performance using NLP metrics. 

During this interactive course, participants will learn the conversion of speech to text using deep learning, building a voice assistant using AI and implementing text-to-speech (TTS) models; training AI models for language translation and using transformers for multilingual text processing; the AI for fraud detection in banking, stock market prediction, cybersecurity and intrusion detection, business analytics and customer insights; the AI-driven traffic monitoring and optimization and AI-powered energy management systems; deploying AI models in production and AI in edge computing and IoT devices; the bias in AI models, techniques for reducing bias in AI applications and AI regulations and compliance frameworks; and the AI-powered automation and robotics, quantum computing in AI, AI and augmented reality (AR) and breakthroughs in self-learning AI models.