This article is an eBook, "How to Build a Career in Artificial Intelligence," written by Andrew Ng, founder of DeepLearning.AI, which provides a comprehensive overview of how to build and grow a career in AI by learning to program, participating in projects, and searching for jobs, among other steps.
present (sb for a job etc)
This is a career development guide, not a technical tutorial. It is aimed at three main groups of readers.
1. Students who want to enter the AI field
2. Professionals who want to switch to AI industry
3. Beginners and newcomers to the AI field
The book's greatest value is in providing advice on all aspects of AI career development, including.
- How to master core AI skills
- Job Interview Tips
- How to create a personal project portfolio
- How to build and utilize a network of contacts
- How to Overcome Imposter Syndrome
It is worth mentioning that this book does not require readers to have a technical background. The author, Wu Enda, is a senior expert in the field of AI, and he founded http://Deeplearning.AI和Coursera等知名平台,在谷歌和百度都领导过AI团队. He has put his years of experience and insights into this book, providing practical career guidance for those who want to develop in the AI field.
If you want to get into AI but don't know where to start, or are confused about career development, this book will be a great guide.
Abstract of the original text
The content of the page is divided into the following sections:
- introductory: Andrew Ng emphasized that coding skills are equally important in AI and will become the new cultural literacy. He compared AI and data science to the new electricity through a metaphor, predicting that it will improve all aspects of human life.
- Three Key Steps to Career Growth: The first step is to learn foundational skills, including programming, machine learning, deep learning, and math knowledge. The second is to deepen skills through real-world projects, build portfolios, and create impact. And finally, finding the right job.
- Learning technical skills: Details the technical skills that need to be mastered in an AI career, including machine learning fundamentals, deep learning, software development, and relevant math. It also emphasizes the importance of continuous learning.
- Project Planning: describes how to identify and plan valuable AI projects, including identifying business problems, conceptualizing AI solutions, setting milestones, assessing feasibility, and budgeting resources.
- Finding a program that matches your career: Emphasizes the importance of choosing the right program early in your career and how participation in a program can lead to incremental improvements in skills and impact.
- Building the project portfolio: describes how to gradually build a portfolio of projects that demonstrate skill progression through small to large scale projects.
- A Simple Framework for an AI Career: Provides a framework for searching for an AI job, including selecting a company, preparing for interviews, and choosing a role. It also emphasizes strategies when switching roles and industries.
- Coping with uncertainty: discusses how to cope with uncertainty in a career by developing plans for different situations.
- Using Informational Interviews to Find the Right Job: Introduces the concept of informational interviewing and how to learn about potential AI positions by talking to people in the industry.
- Find the right AI position for you: offers some advice on how to find the right job in AI, including focusing on the basics, choosing a partner and shaping a professional network.
- Keys to Building a Career in AI: The importance of teamwork, building professional networks, an honest hiring process, and personal self-discipline in creating an AI career biography is discussed.
- Overcoming wurder syndromeThe following are some suggestions for overcoming the sense of self-doubt (wiedr veruuldigingen, or "AI fraud") that is common in the AI field.
point of view
Key points include:
- AI as the new cultural literacy: Consider AI programming skills as the new literacy, comparable to the historical ability to read and write.
- Three Steps to Career Growth: Emphasize the importance of learning foundational skills, real-world project experience, and finding the right job.
- Criticality of technical skills: Details the core technical skills that need to be mastered in an AI career and the role of math in AI.
- Importance of the project: Programs are not only a way to improve skills, but also a career ladder.
- Career Development Strategy: Provides a range of strategies, including how to choose the right program and job, and how to learn about the industry through informational interviews.
- Coping with uncertainty: Coping with uncertainty in a career by developing plans for different scenarios.
- Teamwork and Community: The role of teamwork, professional networking and community support in AI careers was emphasized.
- Overcoming self-doubt: discussed how to overcome feelings of self-doubt in the AI field and encouraged newcomers to actively participate and contribute.
