AIGC (AI Generated Content) is currently the most worthwhile field to join in! With the rapid development of AI technology, it has become one of the most promising golden tracks in the next 10-20 years. It has become a widespread consensus that AI will profoundly transform all walks of life and bring about earth-shaking changes. Therefore, we must learn and embrace the wave of AI. Here are two possible paths:
1) Participate in the AI industry/field: Core positions in the AI field include algorithm engineers, product managers, operations, testing, etc. Among them, algorithm and product positions have higher recruitment volumes and salary levels. If you are interested in entering the field of AI or AIGC as a product manager, then you must read this article carefully and implement it carefully. I have systematically and comprehensively sorted out the algorithms, projects and career change paths that you need to learn to switch to AI.
2) Learn to use AI tools to improve work/money-making efficiency: Next, I will introduce specific methods and paths.
1. Participate in working in the AI industry/field.
The core positions in the AI field mainly include: algorithm engineers, product managers, operations, testing and other positions. The overall recruitment volume and salary are relatively high for algorithms and products. If you want to enter the field of AI or AIGC as a product manager, you must read this article and implement it carefully! ! I have helped you systematically and comprehensively sort out the algorithms, projects, and career change paths that you need to learn to switch to AI.
Hello everyone, I am Boss Xue. I have 8 years of experience as a product manager in Baidu and JD.com. Recently, many friends want to see the job opportunities of AIGC product managers. I have helped you sort out a 30-day career change to AIGC company products. job plan.
Applicable people:
1. Already working product managers who want to change careers to become AIGC product managers 2. College students who want to apply for AIGC product managers (looking for internships/autumn recruitment/spring recruitment)
1.1 30-day roadmap for changing careers to AIGC product manager
Days 1-7: Learn basic knowledge in the AIGC field
Day1-2: Understand AI and AI product managers, and master the panorama of AI product managers. Improve your understanding of algorithms, especially if you come from a non-technical background.
Day3-4: Learn the algorithm principles, application scenarios, advantages and disadvantages related to machine learning. Including: linear regression, logistic regression, SVM support vector machine, decision tree, random forest, K-means algorithm, etc.
Day5: Learn the algorithm principles, application scenarios, advantages and disadvantages related to deep learning. Including: neural network, convolutional neural network CNN, recurrent neural network RNN, etc.
Day6: Learn algorithm knowledge related to large models. Including what is a large model, the basis of a large model: Transformer/attention mechanism, GPT related model characteristics and evolution mechanism.
Day7: To learn the definition of AIGC and typical application scenarios, it is recommended to read the book "Generative Artificial Intelligence".
Days 8-14: Apply AIGC knowledge to complete the first practical project - AI painting
Day 8-9: Be familiar with the basic principles and common tools of AI painting, and learn to deploy and use Midjourney and Stable Diffusion.
Day10-11: Deeply understand the principles of AI painting, learn the principles of diffusion models, master the detailed process of generating pictures by SD, and learn how to write painting prompts.
Day12: Master the principles and basic methodologies of Vincentian diagrams and Tu-generated diagrams.
Day13: Learn to use Lora to change the style of pictures and train Lora using your own data set.
Day14: Use ControlNet to accurately control image generation and complete my first practical project.
Days 15-21: Apply AIGC knowledge to complete the second practical project - AI dialogue robot
Day 15-16: Learn the training methods and processes of large models, know how to write good prompts, and deploy large models on the computer.
Day17-18: Master the fine-tuning scheme for large model scenarios, and use your own data set to train large models.
Day19: Deeply learn LangChain knowledge and use LangChain plug-in knowledge base.
Day20: Use Agent to enhance the capabilities of your own large models.
Day21: Complete the second practical project AI dialogue robot.
Days 21-27: Interview preparation
Day 21-22: Organize your resume, focusing on your skills and project experience related to the AIGC field.
Day23-24: Screen related product positions in the AIGC field, such as: AIGC product manager, AI product manager, large model experience, large model products, AI digital human, AI robot, conversation robot, etc., which are essentially AIGC-focused jobs. , you can invest overseas in the early stage.
Day25-26: Organize and study AIGC product manager high-frequency interview questions from multiple channels, and prepare answers in advance.
Day27: Conduct mock interviews to continuously iterate and optimize your interview skills.
Days 28-30: Conduct interviews and obtain feedback
Day 28-29: Continuously schedule interviews, constantly discover your own shortcomings and shortcomings, and constantly review interviews.
Day30: Continue to follow up on the interview results. If you successfully get a satisfactory offer, start preparing entry materials.
I am Boss Xue, a senior product manager at Baidu and JD.com, author of "Product Manager Job Interview Notes" and "Product Manager Cultivation Path". If you want to learn AIGC together as planned, please send me a private message.
1.2 Continuous learning and improvement
For product managers, algorithm models are our important tools. In order to improve product experience and value, we need to keep up with the pace of technological development and deeply understand and master the latest algorithm models. Currently, all large-scale models are built on deep learning algorithms, so it is crucial to focus on deep learning research. The learning path I recommend is to read the latest academic papers in this field, which are usually published at top conferences (such as CVPR, ECCV, ICCV) such as TPAMI. If you find it troublesome to find papers, you can directly search for relevant content on Google Scholar or arXiv, and try to focus on research results in recent years.
1.3 Technical Panorama of Product Managers
Many people are confused when considering whether they need a deep technical background to become an AIGC product manager. In order to help everyone, I have sorted out the algorithm knowledge points that product managers need to understand, learn and master. The key is to understand the implementation principles of algorithms, application scenarios, and their advantages and disadvantages. As for the rest, just know something.
2. Master AI tools to improve work efficiency and profitability.
It is crucial to learn to use AI tools to improve work efficiency or profit from them (such as starting a side business). Only by deeply understanding the scope of AI's capabilities can we be prepared to stand out in the future AI era. Today, I will mainly share some practical domestic AI tools. The operation methods of these tools do not require complex network knowledge. If you find it useful, please like and give it a thumbs up. If you have any other useful information, please leave a message % Salt Flame (the tool list is sorted by the number of users).
AI writing tools:
iFlytek
Spark,
BiLing AI Writing, Xunwhale AI Xiaoyu
AI Writing,
Cuttlefish AI Writing
AI Chatbot: Wen Xin Yi Yan, Bai
Chuan, Baidu Chat, Tsinghua Zhi Pu Qing Yan, Tong Yi Qian Wen 360 Zhi Nao AI image generation - Wen Sheng Tu ： Wen Xin Yige Tentacle AI painting openflow star dome smart painting Second painting AI-3D generation: O3 deep oxygen technology Tafi AI lumine AI Skybox Objaverse-3D AI design tool: AIDesign Luban Get AI LOGOAI spirit AI clothing design: AI smart painting Zhiyi AI DEJA AI AI planning - POP clothing AI space design: Mold bag cloud architecture AI AIphaDraw architecture Varys AI Interior AI Architecture AI video generation - Vincent Vision: Tencent Intelligent Video, one frame in seconds, flash cutting, CapCut cutting, cutting AI virtual people together ： Shangtang Ruying Silicon -based Intelligence Tencent Zhiying Tuoshi Digital People Zhongke Xiangsheng AI character face changing: I win assistant Face changing technology swapface face Deepswap Swap AI AI music creation: TME Studio Tencent Music NetEase Tianyin BGM Cat Counter Spectrum DeepMusic AI voice generation: Moyin Workshop, Guagua Yousheng , PlayHT Spakfly AI voice robot: Yunbat Intelligence, Jietong Huasheng AI production PPT: ChatPPT Biyou ChatPPT produces PPT in seconds , fully intelligent AIPPT beautiful picture AI PPT AI mind map: Yitu Brain Map Treemind Treemap Impression Picture Note Duomo Intelligent Gitmind Sihu AI Document Processing: ChatPDF iLovePDF AudioNote.ai AI Translation Tools: Youdao Translation Baidu Translation Huoshan Translation Alibaba Translation TranSmart Tencent Translation AI Office Tools: WPS AI Feiyang AI Assistant Lidian Office XiemaLa AI Editor Assistant