Acquire practical coding skills Application-centered learning
With Deep Block curriculum

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Register 3 month-bundle or only join the course of your choice.

  Online Course
Introduction to Python Python Course Registration
Introduction to Deep Learning Introduction to Deep Learning
Deep Learning Intermediate To be released in August 2022
Deep Learning Advanced To be released in December 2022

 

Introduction to Python

12 hours

This course is for students who are new to programming who want to prepare themselves before learning about Deep Learning. We focus on skills necessary for learning Deep Learning technology such as basic Python syntax and application. Even students without prior knowledge in programming can take the Deep Learning Basics course after taking this course.

No. Lecture Topic Lecture Goals
1 Variables and Operation

Understanding basic concepts of programming

2 Functions

Understanding functions

3 Conditionals

Understanding conditional statements

4 Iterations

Understanding iteration statements

5 Strings

Understanding string data type

6 Types and Recursion

Understanding type system and recursion

7 Lists

Understanding Lists and List methods

8 File I/O

Understanding File I/O

9 Class 1

Basic understanding of Class

10 Class 2

Advanced understanding of Class

11 Dictionaries

Understanding Dictionaries

12 Modules

Understanding python modules

Python Course Registration

Basics | Deep Learning Theory 

12 hours

In this course, you will understand the trend of modern AI technology, and learn basic deep learning theories and frameworks. This course is for students who have little or no experience in Deep Learning. We will focus on theories and practices that are necessary for learning AI technology and development.

 
No. Lecture Topic Lecture Goals
1 Introduction to AI Understanding modern AI
2 AI infrastructure management Learning how to set up AI development environment
3 Linux for AI Learning basic skills to handle filesystem with Python
4 Python for AI Learning system library of Python
5 Introduction to Tensorflow Learning how to use Tensorflow
6 Introduction to Deep Learning Learning basic mathematical foundation of deep learning
7 Introduction to Keras Learning how to use Keras
8 Image Classification 1 Learning image classification AI
9 Image Classification 2 Learning image classification AI
10 Image Classification 3 Build image classification AI for Caltech101 dataset
11 Introduction to computer vision Understanding modern computer vision technology
12 Introduction to Pytorch Learning basics of PyTorch
Introduction to Deep Learning

Intermediate | Deep Learning Intermediate

12 hours

In this course, you will learn the applications of the latest deep learning technology. You will implement an AI model yourself focusing on Object Detection, Image Segmentation models. You will learn about the latest AI models that are actually used in industry, implement and use the AI models yourself.

No. Lecture Topic Lecture Goals
1 Object Detection 1 Understanding modern Object Detection technology
2 Object Detection 2 Understanding the process of data collection, preprocessing, model training for Object Detection model
3 Object Detection 3 Understanding the inference step and learning how to evaluate Object Detection AI model performance
4 Object Detection 4 Explaining modern Object Detection model
5 Object Detection AI Project 1 Project using your own data or the prepared data
6 Object Detection AI Project2 Evaluating model performance
7 Image Segmentation 1 Learning modern Image Segmentation technology and the workflow of Image Segmentation AI model
8 Image Segmentation 2 Understanding the process of data collection, preprocessing, model training for Image Segmentation model
9 Image Segmentation 3 Understanding the inference step, learning how to evaluate Image Segmentation AI model performance, and how to optimize the model
10 Image Segmentation 4 Introduction to Mask-RCNN, learning how to use MASK-RCNN library.
11 Image Segmentation AI Project 1 Project with prepared data
12 Image Segmentation AI Project 2 Evaluating model performance

Advanced | Computer Vision Expert Course

12 hours

This is a course on understanding how large enterprises and AI companies around the world actually deploy AI-based services and build their own cloud-based AI services. You will learn about the computer vision technology, network technology, and DevOps technology needed to develop AI services. You will then combine these technologies for the final project, build your own AI services, and create your own AI development portfolio.

No. Lecture Topic Lecture Goals
1 Network, HTML Basics for AI Understanding modern HTTP technology
2 OS, multi-thread Basics for AI Understanding modern OS and multi-thread
3 AI service Front-end Development 1 Understanding Javascript and modern web technology needed for AI based web-service 
4 AI service Front-end Development 2 Understanding IOT device interworking
5 Web service Development for AI 1 Understanding web server technology for AI-based web-service development
6 Web service Development for AI 2 Understanding web server technology for AI-based web-service development
7 Web service Development for AI 3 Web service development for final project
8 AI Infrastructure Design and Building Understanding system structure and design method of modern AI-based service
9 Final Project Planning Setting the target for Object Detection AI model for the final project, finalizing plans for model development
10 Final Project 1 Training and optimizing Object Detection AI model for the final project
11 Final Project 2 Implementing cloud-based inference system
12 Final Project 3 Completing and polishing the final project