{ C Language } Deep Learning From Ground Up™ (Udemy.com)
Build Artificial Intelligence Applications in C
Created by: Israel Gbati
Last updated July 2022
What you will learn
- Build Neural Network for Handwriting Recognition
- Build Neural Networks from scratch without libraries in C
- Understand the fundamentals of deep neural networks from a C perspective
- Build a C Deep Learning library
How it compares
Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:
- Rating4.2 out of 5higher than 10% of them
- Reviews166#109 of 127 by number of reviews
- Length7.4 hoursshorter than 61% of them
- Last updatedJuly 2022earlier than 75% of them
Course Description
Welcome to the { C Language } Deep Learning From Ground Up™ course.
We are going to embark on a very exciting journey together. We are going to learn how to build deep neural networks from scratch in c language.
We shall begin by learning the basics of deep learning with practical code showing each of the basic building blocks that end up making a giant deep neural network all the way to building fully functions deep learning models using c language only.
By the end of this course you will be able to build neural networks from scratch without libraries, you will be able to understand the fundamentals of deep learning from a c language perspective and you will also be able to build your own deep learning library in c.
If you are new to machine learning and deep learning, this course is for you. The course starts from the very basic building block of neural network and teaches you how to build your own neural network using c language before we move on to see how to use readily available libraries.
If you already have some experience with deep learning and want to see how to develop models in c you can also join this course. The course gives an in-depth training on how to develop deep learning models using the c language.
Instructor Details
- 4.2 Rating
166 Reviews
Israel Gbati
Author of Bare-Metal Embedded C Programming: Develop High-Performance Embedded Systems with C for Arm Microcontrollers.
With extensive experience in embedded firmware development, I specialize in real-time systems, low-level programming, medical device architecture, embedded signal processing, and embedded AI. My professional journey has been centered around Arm Cortex-Microcontrollers, delivering robust solutions used in cutting-edge industries.
Passionate about simplifying complex concepts.
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Reviews
By Jose Alfredo Arias Benitez on 4/6/2026
Excelente curso, se presentaron temas donde se puede ver como funciona internamente los algoritmos de deep learning.
By Eric Scheidemantel on 9/14/2024
No resource file with actual code. My output is not matching course code output and I do not have any way other than repeating the video to find my error in the code.
By Óscar Alegria on 3/30/2024
It's an excellent course. You learn how neural networks work from the inside. You don't work with libraries that do everything for you. Highly recommended.
By Girish Chukka on 1/1/2024
All the explained concepts are good and a very useful example is explained. But back propagation lecture/concepts are missing, which are used to train our model. Apart from this things are clear. Had to give 2/5 because of missing an important concept/lecture. :(
By Peter Oo on 12/27/2022
It is a good course for those who want to build neural networks everything from the scratch including mathematic skills.
By Simon Huckle on 12/23/2021
Just getting to grips with the CodeBlocks environment, had an initial problem getting the C compiler up and running, but loaded MinGWInst and all working now.
By KennyKang on 10/16/2021
This is really a good course, it gave me a better understanding of deep learning, thank you my teacher, Israel Gbati.
By Deniz CANTÜRK on 7/28/2020
This is an amazing course giving you the oversight of AI background. It is very obvious that the instructor is highly qualified which you feel throughout the course. So, long story in short : [Highly Recommended]
By Gerhard Quirmbach on 5/25/2020
The spoken sentences in the lecture are often very long and were often not understandable for me as someone with medium English skills. Even with the help of the transscript, I couldn't understand the statement. Shorter sentencers would help.
By Surabhi Gupta on 4/8/2020
The content is short. More details about creating different types of neural nets with diverse architecture models can be added.
Quality Score
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Overall Score : 84 / 100












