Artificial intelligence is a hot topic in the field of science and technology today, and it is also an important force promoting the progress of all walks of life in society.With the development of technology, the role of artificial intelligence in modern society has become increasingly important.As artificial intelligence has shown great potential in various fields, from solving complex problems to promoting innovation and progress, mastering artificial intelligence skills not only enhances personal abilities and corporate competitiveness, but also helps participate in and lead future technological development and promote social progress. .Learning artificial intelligence has gradually become an important and necessary ability in modern times.Therefore, the Microsoft Commercial Artificial Intelligence team has worked hard to develop this series of courses, which comprehensively covers the field of artificial intelligence, from basic concepts to advanced technologies, revealing the core principles and practical applications of artificial intelligence.This series of courses comprehensively covers natural language processing, virtual humans and the metaverse, Python basics, data analysis, efficient automated office, algorithms and other fields.Students will gain an in-depth understanding of natural language processing technology, virtual
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Theme content introduction class AI Disenchantment (I) Principles of AIGC and Generative AI explains the basic principles and core concepts of A IGC and generative AI in a simple and easy-to-understand way, and introduces the current challenges and development trends in the AI field, thereby stimulating interest in AI technology. research interests and explorations, injecting new vitality into future AI development.1AI Disenchantment (I) The evolution of AI paradigm and the industrial opportunities brought by prompt engineering comprehensively sort out the historical evolution of AI development, and introduce in detail the application of emerging technologies with prompt engineering as the core. In this context The following reveals the development trends and business opportunities of the future AI industry, aiming to inspire learners to explore potential innovation directions and seize the opportunities for winners in the AI revolution.1AI Xidao (I) What are the criteria for judging the implementation of AI? In which industries has AI been implemented? In more industries, the results of AI implementation are as follows
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Topic content introduction class decryption AIGC technology and Prompt Engineering ▫ What is AIGC? Data types generated by AIGC (text, pictures, audio, video, etc.) ▫ Introduction and basic principles of LLM ▫ What is Prompt? ▫ Importance of Prompt 1 Prompt Engineering Prompt Engineering ) Text generation ▫ Take Azure OpenAI as an example ▫ Generate advertising copy, slogan, email, ppt, excel, data visualization code, knowledge map, etc. 1 Intelligent customer service ▫ Can Azure OpenAI do customer service? ▫ How about a completely autonomous and controllable customer service system Realize? ▫ Practical training - Intelligent customer service 1 Use Azure OpenAl to generate advertising copy ▫ Generate advertising copy and social media copy for surface (or other products)
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Topic content introduction Class opening ▫ Introduce the content of this course ▫ Schedule ▫ Learning objectives and graduation requirements 1 New thinking on the implementation of enterprise AI under the new AI paradigm ▫ Enterprise AI implementation practice sandbox 2 Ubiquitous artificial intelligence and subversive cognition ChatGPT ▫ What is artificial intelligence 2 How do machines learn? ▫ Model life cycle ▫ Model training explained using linear regression model as an example 2 Machine learning basics ▫ Supervised learning and unsupervised learning ▫ Introduction to classic models 2 Neural grids and depth Learning ▫ Introduction to neural networks and deep learning ▫ Introduction to generative adversarial networks (GAN) ▫ Introduction to reinforcement learning 2 Hands-on training of neural networks ▫ Experience the complete life cycle of neural networks 1 Let the machine listen and speak: speech recognition and speech synthesis technology ▫ Sound Digitization ▫ For speech modeling ▫ Speech recognition technology ▫ Speech synthesis technology 2 Speech processing technology practical application ▫ Utilization
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Topic Content Introduction Class Introduction to Artificial Intelligence ▫ Overview of Artificial Intelligence ▫ Application Cases of Artificial Intelligence 1 Basics of Artificial Intelligence Learning and the Road to Advanced Learning ▫ Current Situation of the Artificial Intelligence Industry ▫ Artificial Intelligence Technical Positions ▫ Vision and Development ▫ Learning Methods and Materials 1 AIGC Technology Analysis and Application ▫ Introducing the application and principle of Azure OpenAI's large language model 2 Prompt Leaning prompt learning ▫ Use prompts to learn to tune large models 2 Evolutionary history of image generation of AIGC ▫ From GAN, VAE, to Diffusion Model 2 AIGC's three-dimensional graphics reconstruction model 2 Data processing basics I Data preprocessing ▫ Data preprocessing basics ▫ Data cleaning ▫ Feature engineering 1 Data processing basics II data visualization ▫ Data visualization principles ▫ Commonly used visualization charts ▫ Data visualization and machine learning 2 Data cleaning with Python
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Topic Content Introduction Class Introduction to Artificial Intelligence ▫ What is Artificial Intelligence ▫ The History of Artificial Intelligence ▫ Common Artificial Intelligence Products in Life ▫ Common Misunderstandings about Artificial Intelligence 1 The Advancement Path of Algorithm Engineers ▫ The Knowledge System of Algorithm Engineers ▫ Learning Methods and information ▫ How to read an AI paper 1 Basics of Machine Learning (I) Technology behind artificial intelligence: AI model ▫ What is an AI model ▫ Life cycle of an AI model ▫ Judgment of model quality 1 Basics of Machine Learning (Ⅱ) Using AI Several methods of the model ▫ Use the model ▫ Use the training code ▫ Use the training code + pre-trained model ▫ Use Algorithm 1 to experience the AI model through cognitive services ▫ Get to know Microsoft Cognitive Services (ASR, TTS) ▫ Service overview + introduction to common tasks ▫ Service call method to obtain results (eg audio files and viseme information) 3 machine learning base
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Theme content introduction class LLM is here ▫ The powerful functions of LLM ▫ The blessing of RHFL ▫ Introduction to AOAI 1 The change of AI paradigm ▫ * TrainingFromScratch ▫ * Pretrained Model + Fine-Tuning ▫ * LLM + Prompting ▫ The impact of paradigm change on AI research and application 1GPT Model analysis ▫ Neural network model and its life cycle ▫ Development and various variants of neural network ▫ Attention is all you need ▫ Transformer-based GPT series model ▫ Image generation (VAE, GAN and diffusion model) 2 diffusion model analysis ▫ Diffusion model ▫ Fine-tuning of the diffusion model Application of two major models Prompt Learning Overview ▫ *
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Topic Content Introduction Classroom Virtual Humans and Metaverse ▫ Definition and Connection 1 Understanding Virtual Humans ▫ Various Virtual Humans ▫ Three Types of Virtual Humans ▫ The Rise of Virtual Humans and the Realization Behind them 1 Overview of Virtual Human Realization Technology ▫ Characters Image ▫ Let the animation move ▫ Can listen and speak ▫ Content creation 1 case analysis report ▫ Based on several virtual people given by the teacher, analyze what technologies are used 1 Virtual character design ▫ Create character (identity, personality, abstract image ) ▫ Image design (original painting and three-dimensional drawing) ▫ Three-dimensional modeling 1 design report ▫ To design a virtual person, you must submit the character design. You can optionally submit the original painting and modeling 1 to let the virtual person move on its own ▫ Virtual anchor architecture ▫ Main modules And technology 1 Theoretical basis of AI generation ▫ Graphics ▫ 2D generation, 2D image style transfer ▫ 3D reconstruction ▫ 3D model generation 4AI generation practice ▫ Use open source models to generate 3
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1. Data analysis and office applications 2. Efficient automated office based on Python and AIGC
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Topic Content Introduction Class Understanding Algorithms ▫ What is an algorithm? ▫ Brief explanation of basic concepts related to algorithms ▫ Three major structures: sequence, condition, loop 2 linear table data structure ▫ What is a linear table? ▫ What are the common linear table data structures ?What characteristics do they have? 2 Guessing number games use practical problems to guide binary search algorithm ideas and examples. Algorithm problem explanation: The computer randomly generated an integer from 1 to 100. How many times can you guess this number? ▫ The computer only tells you Right or wrong, how many times can you guess? How to guess most efficiently? ▫ The computer tells you whether the result you guessed is too large or too small, how many times can you guess? How to guess most efficiently? Example algorithm code implements 2 search algorithm ▫ Classic Introduction to search algorithms: sequential search, half search ▫ Example algorithm code implementation 2 Doudizhu card grabbing game uses practical problems to guide the insertion sort algorithm idea Example algorithm problem explanation: ▫
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