Course

Deep Learning - October 2024

In this course, you will learn the basics - theoretical and practical - of neural networks, what problems you encounter, how to solve them, and how to ensure that your models work correctly. Along with this, you will explore how using abstraction and combining building blocks you can build, train and test complex architectures. You will understand the basic principles behind modern research and applications of neural networks, how to follow their principles and how to create your own, original solutions. You will look at the cases in which deep neural networks find the greatest application - working with images and natural languages; you will understand how generative models work and how to teach a model to make autonomous decisions.

Topics

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Target Audience

The course is suitable for people with previous programming experience in Python (at Programming Basics level) and Jupyter Notebook. Completion of the Math Concepts for Developers course or equivalent knowledge is required .

How to enroll in the course?

To sign up for the course, click HERE or the ENROLL button. After a successful payment, you will be enrolled in the training.

What is the deadline for enrolling in the course and when does it start?

Enrollment in the course is open until 28 September. The training starts on 29 September 2023. You can find a detailed schedule of classes in the Topics section.

How much is the course fee and what does it include?

Online

120 USD

Online training in real-time

Lifetime access to lesson recordings and learning content

Help from a mentor in understanding the learning materials

Access to a closed Facebook group with all other course participants

Taking a regular exam and receiving a certificate

SoftUni gives you a 100% guarantee of the quality of this course. The most important thing for us is that you acquire the necessary skills and knowledge. In the event that the training fails to fulfil your expectations, we guarantee a full refund of the amount you have paid. You can receive a refund until the fifth lesson of the course (30 May).