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MOOC
本系列課程從零開始，教授一般認為最適合初學者的程式語言「Python」，目標是讓大家在完成本課程之後，一方面獲得程式設計與運算思維的基本概念，一方面也能獨立寫出能解決運算問題的程式。本課程和一般程式設計課程最不同的地方，在於它是以解決商管領域的運算問題為導向，因此課程不會只含有質因數分解、紅球白球排列組合、三角不等式、萬年曆、數字排序等傳統程式設計課程的範例與作業，而是包含了生產、物流、存貨、投資、定價等問題，讓大家在學會程式設計的同時，也直接體會程式設計與資訊技術在商管領域的各種應用。 本系列課程共分為三門課程。本門課程做為第一門課程，將介紹程式設計的基本觀念、Python 語言的基本語法、選擇、迴圈、清單，並以作業管理領域的一些簡單演算法作結。
- Course related:
- MM2425 Introduction to Business Analytics
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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Video
This course will give you a full introduction into all of the core concepts in C++. * Contents * -- (0:00:00) Introduction -- (0:01:38) Windows Installation -- (0:04:54) Mac Installation -- (0:08:44) Setup & Hello World -- (0:12:29) Drawing a Shape -- (0:19:55) Variables -- (0:31:43) Data Types -- (0:39:15) Working With Strings -- (0:49:00) Working With Numbers -- (0:59:41) Getting User Input -- (1:05:32) Building a Calculator -- (1:09:28) Building a Mad Libs -- (1:13:45) Arrays -- (1:20:03) Functions -- (1:29:47) Return Statement -- (1:35:22) If Statements -- (1:47:15) If Statements (con't) -- (1:55:58) Building a Better Calculator -- (2:02:20) Switch Statements -- (2:10:47) While Loops -- (2:18:53) Building a Guessing Game -- (2:29:18) For Loops -- (2:38:32) Exponent Function -- (2:45:21) 2d Arrays & Nested Loops -- (2:54:55) Comments -- (2:59:11) Pointers -- (3:13:26) Classes & Objects -- (3:25:40) Constructor Functions -- (3:34:41) Object Functions
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- C++ (Computer program language)
- Resource Type:
- Video
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MOOC
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language)
- Resource Type:
- MOOC
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Others
Guys, our original series on the Arduino Microcontroller was insanely popular. Those original lessons had some great technical content, but the production quality of the videos was pretty low. Because of that, I want to go in and redo the arduino tutorials, taking advantage of improved production capabilities I now have, and using fresh hardware and software. For those who have taken the original series, the first few lessons will be material you already have learned. You can choose to review the material, or just skip to the later lessons. In this new series of lessons, I will be using this Arduino kit. So, enough of this small talk, lets get right into the new and improved lessons.
- Course related:
- EE2007 Computer System Fundamentals
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Programmable controllers Arduino (Programmable controller)
- Resource Type:
- Others
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Others
We're like Duolingo for learning to code. When learning to code, most people get stuck on the "bridge" between memorizing syntax and understanding the logic that makes it all work. We believe the most effective way to learn a programming language is to break the process into three phases:(1)Memorize syntax; (2) Solve problems; and (3) Make stuff. Most beginners jump from memorizing syntax directly into making stuff (or trying) without fully understanding how syntax is used to solve problems. In other words, they haven't learned how to think like a programmer, yet they're trying to solve problems like a programmer. Edabit was created to bridge this gap, while also making the process fun and addictive.
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer programming
- Resource Type:
- Others
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Others
Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly. It's also easy for beginners to use and learn, so jump in!
- Course related:
- EIE3343 Computer System Principles
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
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Others
GitHub is a development platform inspired by the way you work. From open source to business, you can host and review code, manage projects, and build software alongside 50 million developers. GitHub brings teams together to work through problems, move ideas forward, and learn from each other along the way. You can write better code, manage your chaos, and find the right tools in GitHub.
- Course related:
- EIE6811 Guided Study in Electronic and Information Engineering I/II/III and EE4006A Individual Project
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Computer software -- Development Software engineering Git (Computer file)
- Resource Type:
- Others
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MOOC
Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle. That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers. Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team
- Subjects:
- Computing, Data Science and Artificial Intelligence
- Keywords:
- Big data Data mining Machine learning
- Resource Type:
- MOOC