Ride this wave and accelerate your career with this acclaimed AI and Machine Learning program. This program features a thorough mix of theory, projects, and extensive hands-on practice while leveraging Caltech’s academic excellence. More importantly, you’ll learn about not only the theoretical underpinnings of AI and ML but also gain the practical know-how to quickly and successfully apply these tools and techniques to new problems. This program is a blend of self-paced online videos, live virtual classes, hands-on projects, labs, and masterclasses. Mentorship sessions will provide you with a high-engagement learning experience and real-world applications, helping you master essential AI and ML skills. This program covers essential mathematical and statistical concepts, as well as Python programming, machine learning, deep learning, generative AI, prompt engineering, explainable AI, ChatGPT, computer vision, natural language processing, and more.

Robotic Process Automation (RPA) is one of the fastest-growing technologies for enhancing real-time business processes and operations and has applications in various industries. It can be used for HR activities, such as onboarding employees, insurance claims and invoice processing, and customer service communications. Our Introduction to Robotic Process Automation course will give you a broad understanding of advanced intelligent applications and the concepts within RPA. This training course will give you an overview of the fundamental methodologies and tools you need to introduce and use RPA in your business. You’ll be taught the steps for implementing RPA in your organization, learn the essential RPA tools and workflows used in intelligent automation, and work through case studies that provide innovative best practices.

This Deep Learning course with TensorFlow certification training is developed by industry leaders and aligned with the latest best practices. You’ll master deep learning concepts and models using Keras and TensorFlow frameworks through this TensorFlow course. Learn to implement deep learning algorithms with our TensorFlow training and prepare for a career as a Deep Learning Engineer. Achieve our deep learning certification and gain a competitive edge over your peers in your next interview. Demand for skilled Deep Learning Engineers is booming across a wide range of industries, making this Deep Learning course with Keras and Tensorflow certification training well-suited for professionals at the intermediate to advanced level. We recommend this deep learning. Certification Training, particularly for Software Engineers, Data Scientists, Data Analysts, and Statisticians with an interest in deep learning.

The AI Engineer Master’s Program, in collaboration with IBM, covers the crucial skills you need for a successful career in Artificial Intelligence (AI). As you undertake this Artificial Intelligence program, you’ll master the concepts of Machine Learning and Deep Learning and the internationally-acclaimed programming language Python needed to excel in AI. You will also learn how to design intelligent models and advanced artificial neural networks and leverage predictive analytics to solve real-time problems to take your career in Artificial Intelligence to the next level.

Gain an understanding of AI concepts, workflows and performance metrics! Artificial intelligence (AI) is intelligence demonstrated by machines, making it possible for them to learn from experience and perform human-like tasks. The majority of modern AI examples rely on deep learning and natural language processing, and these technologies enable computers to process large quantities of data and recognise patterns within that data to complete specific tasks and activities. Artificial intelligence is helping to drive organisations forward, across a broad range of industries. It’s leading to more informed business decisions, helping companies to create innovative new products and services, and enabling businesses to achieve key performance goals.

This online course offers an in-depth overview of machine learning topics, including working with real-time data, developing algorithms using supervised and unsupervised learning, regression, classification, and time series modeling. You will also learn how to use Python to draw predictions from data.