Matlab&Simulink Summer Courses

Big data course is an English taught course. All other courses are conducted in Mandarin.
Additional Mandarin Courses is added! Scroll down for more details. Do not miss Again!

Join us for MATLAB & Simulink Summer courses, to know more about the course details please refer to following section.

《Venue》CCC – Computer Laboratory

Any inquiries, please mail to the following address: service@cc.nthu.edu.tw or call Miss Chiang at campus ext.31231

Focus on software fundamental skills, perfect for beginner and any faculty.

Registration from 2nd July http://bit.ly/2tgZ1QB

Date	Topic	Details	Agenda
7/23	MATLAB Fundamentals 09:00~16:30	This course is for the beginners of MATLAB. Let the learner be familiar with MATLAB user interface and basic commands through the lecturer’s instruction together with the operation practice. After experiencing this course the learner will know how to call functions,plot and program with MATLAB.	Working with the MATLAB User Interface MATLAB plot tool Variables and Expressions Automating Commands with Scripts
7/30	MATLAB Advance 09:00~16:30	This course is for people who are already familiar with MATLAB basic operation.The content of this course is the detail and complete introduction for MATLAB function M file.After experiencing this course the learner will know how to write functions and then create robust applications, troubleshoot and improve performance.	Writing Functions Structuring Code Creating Robust Applications Troubleshooting Code and Improving Performance
7/31	Simulink Fundamentals 09:00~16:30	This course provide skills for building Simulink model(such as math/logical operation,subsystem and input/output signal,library..etc),setting simulation environment and Physical model with Continuous/Discrete time. Further more, it will let you know how to interact with MATLAB like data communicatoin and parameter control. And you will know how to use debugging function to find the bug of your design algorithm.	Introduction Building the Model Creating A Simple Model Masking Subsystem Working with Subsystems Working with MATLAB Modeling Discrete Systems Modeling Continuous and Hybrid Systems
8/1	MATLAB for Data Analytics 09:00~12:00	This course focuses on data analysis process; from importing and organizing data, to exploratory analysis, to confirmatory analysis and simulation. We will provide hands-on experience for performing statistical data analysis with MATLAB® and Statistics and Machine Learning Toolbox™. The course is intended for data analysts and data scientists who need to automate the processing, analysis, and visualization of data from multiple sources. Topics include:	Access data from files and Excel spreadsheets Visualize data and customize figures Perform statistical analysis and fitting Generate reports and automate workflows Share analysis tools as standalone applications or Excel add-ins
8/1	English-Taught Course: How to Analyze Big Data by Using MATLAB 13:20~16:30	MATLAB provides a single, high-performance environment for working with big data. In this course, we will use MATLAB datastores to access data that normally does not fit into the memory of a single computer. To analyze data, tall array allow you to apply statistics, machine learning, and visualization tools to data that does not fit in memory.	Big Data Capability in MATLAB Big data in industry New Big Data Capabilities in MATLAB Access Big Data Datastore Exercise1 : 'datastore' Tall arrays Working with tall arrays Exercise2 : tall array Functions support tall Conclusion and Other Materials

August Courses

Focus on software advanced skills and application, perfect for who has basic skills .

Registration from 1st Aug http://bit.ly/2JZ6KKb

Date	Topic	Details	Agenda
8/21	Image Processing with MATLAB 09:00~12:00	In this experience course,you will learn how to use MATLAB and Image Processing Toolbox, quicky image processing algorithms,including image enhancement,alignment,and segmentation. Showing you how to capture images directly from the hardware in MATLAB development environment for instant image processing.	Why should you use MATLAB for Image Processing? Images in MATLAB Image Enhancement Image Registration Image Analysis Image Segmentation
8/21	Computer Vision with MATLAB 13:20~16:30	First, we will introduce System Objects in MATLAB. Then, learn how to detect and extract features in images. We will see course examples incuding image registration, image classification and object detection. Lastly, talk about stereo vision to extract the 3D structure of a scene.	Streaming Processing (System Object) Featured-Based Workflow Image Category Classification Object Detectionand Stereo Vision
8/22	Optimization Techniques in MATLAB 09:00~12:00	This course introduces applied optimization in the MATLAB environment, focusing on using Optimization Toolbox™ and Global Optimization Toolbox™.	Applied Optimization Specifying the Objective Function Choosing a Solver Global Optimization
8/22	MATLAB to C with MATLAB Coder(MATLAB Coder) 13:20~16:30	This course introduces how to generate readable and portable C code quickly with MATLAB Coder, and also the way to generate optimized fixed-point C code for embedded systems.	Preparing MATLAB Code for C Code Generation Fixed point conversion Generating Fixed C Source Code for embedded system

Do Not Miss Again!

Sign up for the popular Mandarin courses in this summer. Registration from 1st Aug http://bit.ly/2JZ6KKb

Date	Topic	Details	Agenda
8/28	MATLAB Fundamentals 09:00~16:30	This course is for the beginners of MATLAB. Let the learner be familiar with MATLAB user interface and basic commands through the lecturer’s instruction together with the operation practice. After experiencing this course the learner will know how to call functions,plot and program with MATLAB.	Working with the MATLAB User Interface MATLAB plot tool Variables and Expressions Automating Commands with Scripts
8/29	MATLAB Advance 09:00~16:30	This course is for people who are already familiar with MATLAB basic operation.The content of this course is the detail and complete introduction for MATLAB function M file.After experiencing this course the learner will know how to write functions and then create robust applications, troubleshoot and improve performance.	Writing Functions Structuring Code Creating Robust Applications Troubleshooting Code and Improving Performance
8/31	MATLAB for Data Analytics 13:20~16:30	This course focuses on data analysis process; from importing and organizing data, to exploratory analysis, to confirmatory analysis and simulation. We will provide hands-on experience for performing statistical data analysis with MATLAB® and Statistics and Machine Learning Toolbox™. The course is intended for data analysts and data scientists who need to automate the processing, analysis, and visualization of data from multiple sources. Topics include:	Access data from files and Excel spreadsheets Visualize data and customize figures Perform statistical analysis and fitting Generate reports and automate workflows Share analysis tools as standalone applications or Excel add-ins

Essential to Artificial Intelligent: Deep Learning Technique Registration from Noon, 31st Aug https://goo.gl/forms/HqTC2diriOOUocnv1

9/13

Deep Learning for Computer Vision with MATLAB
13:20~16:30

Please Note: This course will be held at NCHC Computer Room B and conducted in Mandarin

NCHC: No.7, R&D Rd. VI, Hsinchu Science Park, Hsinchu 30076, Taiwan, R.O.C.
https://www.nchc.org.tw/tw/inner.php?CONTENT_ID=85

This course focuses on convolution neural network(CNN). We will learn how to create and train CNN with NVIDIA GPU. Download pretrained networks to do transfer learning. At last, train object detector with deep learning algorithms, such as R-CNN, Fast R-CNN, and Faster R-CNN.

What is Deep Learning?
Layers in Convolution Neural Network
Image classification using pre-trained network
Train a new model
Object detection