"AI Programming for Liberal Arts Students from Zero Foundation" is launched by the School of Journalism and the School of Artificial Intelligence at Tsinghua University. It introduces how to help liberal arts students quickly master AI programming skills and enhance their competitiveness in the digital age. The course emphasizes that liberal arts students can use AI technology to rapidly improve their programming ability and imagination. There is no need to deeply study complex code syntax; they only need to describe requirements in natural language. Based on specific cases, it shows how to useDeepSeekfor tasks such as data processing, text generation, and chart drawing, helping liberal arts students better understand and apply AI technology. It analyzes the quality, application scenarios, and ethical and legal issues of AI-generated data, emphasizes the potential and challenges of AI-generated data in scientific research, and guides liberal arts students to pay attention to data quality and ethical issues when using AI.
Obtainthe original PDF file of "AI Programming for Liberal Arts Students from Zero Foundation", scan the QR code to follow and reply: 20250325
- New Thinking for AI Programming for Liberal Arts Students
- Human-machine excellent generation, human-machine fast generation: Introduces how liberal arts students can program based on AI, break traditional programming thinking, and achieve human-machine excellent generation and human-machine fast generation.
- Breaking Myths and Core Mental Methods: Four steps explain how to break myths in AI programming and master the core mental methods.
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- AI Reconstructs the Programming Paradigm: Introduces how AI reconstructs the programming paradigm, including the evolution of programming paradigms and the application of AI in programming.
- Preparation Before Hands-on Practice: Use PyCharm as the local code compiler.
- Preparation Before Hands-on Practice: Install the Python interpreter and related libraries.
- Examples of Common Python Libraries for Data Analysis and Plotting : Lists common libraries used in Python for data analysis and plotting, and provides specific examples.
- Summarize Zhuge Liang's Debate Words: Generate text based on DeepSeek and save it locally.
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- DeepSeek Gives the Running Process: Provides detailed running steps and code examples.
- Code Generated by DeepSeek: Shows examples of code generated by DeepSeek.
- Visualize Zhuge Liang's Language: Use charts to display word frequency analysis of Zhuge Liang's language.
- Text-to-Data
- Social Data and AI-Generated Data: Introduces the sources, characteristics, and applications of social data and AI-generated data.
- AI Hallucinations and Their Basic Characteristics:Discusses the issue of AI hallucinations, especially their manifestation and characteristics when loading multiple datasets.
- Extraction of AI Hallucination Problems:Further explores the manifestation of AI hallucination problems when loading multiple datasets.
- Reverse Satisfaction Theory: Explores the manifestation of reverse satisfaction theory in AI applications, including theoretical formalization, computational satisfaction, and improvement effects.
- Doing a Data Simulation Experiment from Scratch:The content introduces how to conduct a data simulation experiment from scratch, including the viral Stanford AI Town.
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Definition of Agents:Introduces the three major systems of agents (perception system, decision-making system, learning system).
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The 7-Layer Core Architecture of Agents:Introduces the 7-layer core architecture of agents and their functions.
- Belief evolution under the introduction of disinformation: Research on the impact of disinformation on belief evolution.
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- Follow-up ideas: Introduces the process and effects of agent-based simulation experiments.
- Innovative ideas: Introduces how to improve the quality of text generation based on retaining headers and constrained generation.
- Top 20 keywords in Weibo and AI topic sets: Analyzes the top 20 keywords in Weibo and AI topic sets to understand current hot topics in the AI field.
- Top 20 keywords in data and AI topic sets: Analyzes the top 20 keywords in data and AI topic sets to grasp the latest developments in data science and AI research.
- Code for time series analysis : Presents analysis results based on visual charts to help understand code performance and optimization directions.
- Text-to-chart：
- Start from methods, start from image visualization : Introduces how to start data analysis from methods and image visualization.
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DeepSeek application scenarios:Introduces the application scenarios of DeepSeek.
- Data visualization: Automatically generates multiple types of visualization charts based on analysis results, clearly displaying relationships and patterns in the data.
- The questionnaire tables very familiar to social science students: Shows how to use AI technology to process and analyze questionnaire data common in the social sciences.
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- Not just correlation analysis, but also modeling: How to use AI for more in-depth data analysis. Steps for using AI to analyze public opinion events, including data collection, processing, analysis, and interpretation of results, etc.
- AI-assisted construction of knowledge graphs: How to use AI to assist in building knowledge graphs. How to use wiki to automatically identify and construct knowledge graphs. Construct public opinion graphs based on dependency relations in text, and analyze emotional tendencies and thematic structures in text.
- Text-to-website：
- Theoretical framework: Based on black-box encapsulation of API function modules, componentized multi-agent simulation, and convenient interaction design, it achieves efficient and easy-to-use website functionality and user experience.
- DeepSeek implementation path: Based on creating agents and defining interaction rules, and generating interaction prototypes containing necessary elements and data sources, it realizes agent platform construction and interaction design.
- DeepSeek + online compilation: How to use DeepSeek and online compilation to create a food website.
Getthe original PDF file of "Zero-Basics AI Programming for Liberal Arts Students", scan the QR code to follow and reply: 20250325