Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

The general trend in any industry is for repetitive tasks to get automated and for humans to be deployed on higher skill jobs. Google Dialogflow is a cutting edge conversational interface for bots, devices, and applications.

Explore the tools and techniques for developing computer vision solutions using Microsoft Azure's AI capabilities.

This course provides a deep dive into how to create a chatbot using Dialogflow, augment it with Cloud Natural Language API and operationalize it using Google Cloud tools.

In this course, you will learn to train neural network models using TensorFlow and PyTorch, perform distributed training using the Horovod framework, and perform hyperparameter tuning using Hyperopt.

This course will cover how to leverage both an algorithmic as well as a deep learning approach for building features from image data on Microsoft Azure.

Learn to design and implement GANs for generating realistic data samples in various applications.

Understand how to leverage vector databases in building efficient generative AI solutions.

Learn to create models for grammatical error correction using Python, focusing on machine learning techniques and practical applications.

This course will teach you how you can build and train your traditional machine learning models using the Databricks Machine Learning runtime and MLflow to manage the end-to-end machine learning lifecycle.

In this course, you'll learn to use TensorFlow.js to build, train, and deploy machine learning and deep learning models to power client-side and server-side applications using the JavaScript language.

This course walks through building Machine Learning Regression Models using Scikit-Learn library from Python.