Everyone wants to minimize losses and maximize profits. AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Thanks to Deep Learning and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It’s something that’s moving beyond the realm of data science – if you’re a developer, this course gives you a great opportunity to expand your skillset.

In this course, you will learn:

• What is deep learning and how to implement it
• The core concepts of deep learning
• Basic of Deep Learning and modern best practices with a digit classification problem of MNIST
• The types of problems deep learning/AI solves
• Learn about Data Science, its challenges and how to tackle them
• Apply deep learning to other domains like Language Modeling, ChatBots and Machine Translation using the one of the powerful architectures of DL, RNN

At the end of this course, you will learn all the essentials needed to explore and understand what is deep learning and will perform deep learning tasks first hand.