NLP: Twitter Sentiment Analysis

Applications of TinyML

Gain an extensive understanding of TinyML applications, fundamental principles, and the ethical development of artificial intelligence.

ML Use Cases in Finance

Learn to apply advanced machine learning and deep learning models to real-world challenges by immersing yourself in the cutting-edge world of AI-powered finance and insurance.

Unsupervised, Deep and Reinforcement Learning: Introduction

Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.

Vision Intelligence and ML

Develop your skills in image processing, augmented reality, and object recognition to prepare yourself to create cutting-edge AI-powered visual apps.

ML with Python: A Practical Introduction

Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.

AI in Architectural Design: Introduction

In-depth study of the applications of machine learning and computer vision, as well as practical experience in data analysis and Python programming.

Data Science and ML Capstone Project

A program that emphasizes the practical implementation of data science and machine learning to overcome obstacles through the use of Python.

ML Fundamentals

From fundamental concepts to advanced methods such as deep learning and ensemble techniques, this program provides a comprehensive examination of machine learning techniques.

MLOps1 (Azure): Deploying AI & ML Models in Production using Microsoft Azure ML

The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.

Higher education assessing in the age of AI

Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.