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孔令傑 (Ling-Chieh Kung)
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。本門課程做為第三門課程，將介紹類別與物件、以 Python 繪製統計圖表、程式演算在經濟學均衡分析的應用，以及圖形化使用者介面的設計。
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What's inside
Syllabus
C01 類別與物件
C02 用matplotlib 繪製統計圖
C03 程式演算在經濟學的應用
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Syllabus
C01 類別與物件
C02 用matplotlib 繪製統計圖
C03 程式演算在經濟學的應用
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Covers using Python for computational problem solving in business-related fields
Covers using Python for creating statistical charts with matplotlib
Covers using Python for applying operations research techniques in an economic equilibrium analysis
Covers using Python for designing graphical user interfaces with Tkinter
Covers using Python for web scraping
Covers using Python for machine learning
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Reviews summary
Python 商管程式設計應用精華
根據學生表示，這門用 Python 做商管程式設計（三）課程為先前課程的良好延伸，特別是在應用面提供了豐富的實例。許多學習者讚賞老師的講解方式，認為清晰易懂，特別是關於類別與物件、繪製統計圖表等主題。然而，部分學員指出，對於網路爬蟲和機器學習等進階主題，課程的廣度大於深度，感覺內容較為入門或蜻蜓點水。雖然課程提供了實用的練習題，但有評論提到部分內容可能需要補充額外知識或自行深入研究才能 fully grasp the concepts，這對希望立即應用於實務的學習者來說可能是個警訊。總體而言，課程對於想將 Python 應用於商管領域、已有基礎的學習者來說，是個紮實的下一步。
作為系列課程的第三部分，銜接良好。
"這是第三部課程，感覺課程編排有連貫性"
"延續前兩門課的內容，學習路徑很清楚"
"從基礎到應用，一步一步學習，感覺學得很紮實"
提供的練習有助於鞏固學習內容。
"練習題很有幫助，可以實際操作學到的東西"
"作業都滿實用的，有助於理解課程內容"
"透過練習能夠更熟悉程式碼的寫法"
講師的授課方式容易理解，能有效傳遞知識。
"老師講解非常清楚，學習起來很順利"
"老師的講解方式很棒，可以讓我很快進入狀況"
"講師說明很清晰，對概念的理解很有幫助"
課程內容與商管領域結合緊密，學以致用。
"程式範例結合許多商管主題，讓學習更有方向"
"課程內容與商管應用結合很棒！"
"可以學習到一些商業上的應用"
"學到如何將Python應用在商業上，非常有實用性"
部分進階主題僅基礎介紹，需要自行深入。
"網路爬蟲和機器學習的部分感覺比較像點到為止，沒有深入"
"希望網頁擷取的部分可以講得深入一些"
"機器學習的內容有點太淺，沒辦法實際應用"
"對於想要深入了解特定主題（如機器學習）的同學可能會覺得不夠過癮"
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Career center
Learners who complete 用 Python 做商管程式設計（三）(Programming for Business Computing in Python (3)) will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to extract insights and inform decision-making. They work in various industries, including finance, healthcare, retail, and manufacturing. A bachelor's degree is typically required to enter this field, often in a quantitative field like mathematics, statistics, or computer science. This course may be particularly helpful for individuals pursuing a career in Data Analytics, as it covers topics like data analysis, visualization, and programming.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to answer questions and draw conclusions. They work in various industries, including healthcare, finance, and marketing. A bachelor's degree in statistics or a related field is typically required to enter this field. This course may be useful for individuals pursuing a career in Statistics, as it covers topics like probability, statistics, and programming, all of which are fundamental to statistical analysis.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various fields, including healthcare, finance, and retail. A master's or PhD degree is typically required to enter this field, most commonly in a quantitative field like mathematics, statistics, or computer science. This course may be useful for Data Scientists who wish to gain a deeper understanding of programming, data analysis, and visualization techniques.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts conduct studies and create models to help businesses make decisions. They use techniques like data analysis, forecasting, and optimization to identify problems and develop solutions. A master's degree is typically required to enter this field, most commonly in operations research, management science, or industrial engineering. This course may be particularly helpful for aspirational OR Analysts, because it covers topics like statistics, data analysis, and programming, all of which are useful for building and implementing models in this field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. They work in various industries, including technology, finance, and healthcare. A bachelor's degree in computer science or a related field is typically required to enter this field. This course may be useful for Machine Learning Engineers, as it covers topics like machine learning, data analysis, and programming.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess and manage financial risks. They work in insurance companies, consulting firms, and government agencies. A bachelor's degree in mathematics, statistics, or a related field is typically required to enter this field. This course may be useful for aspiring Actuaries, as it covers topics like probability, statistics, and programming, all of which are essential for building and implementing actuarial models.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. They work in investment banks, hedge funds, and other financial institutions. A master's degree is typically required to enter this field, most commonly in financial engineering, mathematics, or statistics. This course may be useful for aspirational Quantitative Analysts, as it covers topics like statistics, probability, and programming.
Financial Planner
Financial Planner
Financial Planners help individuals and families plan for their financial futures. They work with clients to develop financial goals, create budgets, and make investment decisions. A bachelor's degree in finance or a related field is typically required to enter this field. This course may be useful for Financial Planners, as it covers topics like financial planning, investment analysis, and data visualization, all of which are essential for providing sound financial advice.
Business Analyst
Business Analyst
Business Analysts analyze an organization's needs to help it improve its processes and systems. They work closely with stakeholders to define requirements, develop solutions, and evaluate results. A bachelor's degree is typically required to enter this field, commonly in business, management, or a technical field. This course may be useful for Business Analysts who work on projects involving data analysis, modeling, and visualization, as it covers topics like programming, statistics, and data visualization.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks within organizations. They work in various industries, including finance, insurance, and healthcare. A bachelor's degree is typically required to enter this field, commonly in business, finance, or a related field. This course may be useful for Risk Analysts, as it covers topics like data analysis, modeling, and visualization, which can be used to identify and mitigate risks within an organization.
Market Researcher
Market Researcher
Market Researchers study consumer behavior and trends to help businesses make informed decisions. They work in various industries, including marketing, advertising, and product development. A bachelor's degree in marketing, business, or a related field is typically required to enter this field. This course may be useful for Market Researchers, as it covers topics like data analysis, survey design, and data visualization, all of which are essential for conducting effective market research.
Financial Analyst
Financial Analyst
Financial Analysts collect and interpret data to help businesses make financial decisions. Some Financial Analysts work in financial advising, where they help individuals plan for their financial futures. Others work in equity or portfolio management, investment banking, or corporate finance. A bachelor's degree is typically required to enter this field. This course may be useful for Financial Analysts who aim to work in financial advising, as it covers topics like programming, data analysis, and visualization.
Economist
Economist
Economists study how economies work and how to improve them. They work in academia, government, and the private sector. A PhD degree is typically required to enter this field. This course may be useful for economists who wish to apply programming and data analysis to their work, as it covers topics like data analysis, modeling, and visualization.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain computer software. They work in various industries, including technology, finance, and healthcare. A bachelor's degree in computer science or a related field is typically required to enter this field. This course may be useful for Software Engineers who work on projects involving data analysis, visualization, or business applications, as it covers topics like programming, data structures, and algorithms.
Web Developer
Web Developer
Web Developers design, develop, and maintain websites. They work in various industries, including technology, marketing, and e-commerce. A bachelor's degree in computer science or a related field is typically required to enter this field. This course may be useful for Web Developers who want to build websites with dynamic content and interactive features, as it covers topics like programming, data structures, and algorithms.
For more career information including salaries, visit:
OpenCourser.com/course/vbirr7/Yong
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
用 Python 做商管程式設計（三）(Programming for Business Computing in Python (3)).
Provides a comprehensive overview of the Python programming language, with a focus on data analysis. It covers essential topics such as data manipulation, data visualization, and machine learning. This book valuable resource for anyone who wants to learn how to use Python for data analysis.
Provides a comprehensive introduction to machine learning, with a focus on Python. It covers essential topics such as supervised learning, unsupervised learning, and deep learning. This book valuable resource for anyone who wants to learn how to use Python for machine learning.
Provides a comprehensive introduction to machine learning, with a focus on Python. It covers essential topics such as supervised learning, unsupervised learning, and deep learning. This book valuable resource for anyone who wants to learn how to use Python for machine learning.
Provides a comprehensive introduction to data science, with a focus on Python. It covers essential topics such as data wrangling, data visualization, and machine learning. This book valuable resource for anyone who wants to learn how to use Python for data science.
Provides a comprehensive introduction to deep learning, with a focus on Python. It covers essential topics such as neural networks, convolutional neural networks, and recurrent neural networks. This book valuable resource for anyone who wants to learn how to use Python for deep learning.
Provides a comprehensive overview of the Python programming language, with a focus on finance. It covers essential topics such as data analysis, financial modeling, and risk management. This book valuable resource for anyone who wants to learn how to use Python for finance.
Provides a comprehensive introduction to the Python programming language, with a focus on beginners. It covers essential topics such as data types, variables, control flow, and functions. This book valuable resource for anyone who wants to learn how to use Python for basic programming tasks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vbirr7/Yong
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