25-Feb-23 Climbing the Learning Curve at the Speed of Light!
Dear friends,
Thank you for giving me your email address (and more importantly, a few minutes of your precious weekend) for the newsletter, Sherman's Weekly Digest. As someone who is always interested in how the world operates, I am excited to share my thoughts on a variety of topics, including decision-making skills, tech trends, productivity, consulting, books, and anything else that I find interesting.
Are you interested in learning about a new field but don't know where to start? Learning about a new topic can be overwhelming, especially if it's a complex field. Yet, working as an analyst in the consulting industry myself, I am forced to learn about a completely unknown field within a few day's time or even immediately on the job which provided me with some experience in climbing steep learning curves every time.
In this issue, I'll share a step-by-step process for effectively learning about a new topic. The guide includes tips on finding key concepts, gathering knowledge, and deepening your understanding.
Are you ready to learn something new? Let's get started!
Step 1: Find Key Concepts
Starting by leveraging technology will be a good call. One way to do this is to use an AI-powered tool like ChatGPT to identify the 10 most important keywords related to the field (could be more or less than 10 depending on your time). These keywords will provide a foundation for further research and discussion with experts in the field.
For Example, I have asked it to “Give me the 10 most important keywords about Artificial Intelligence that’s related to algorithm and give me a detailed explanation of each of them.” here are some of the answers:
- Support Vector Machines (SVMs) - SVMs are a type of algorithm that can be used for classification and regression tasks. They work by finding the best boundary, or hyperplane, that separates the different classes in the data. SVMs are particularly useful when the number of features is much greater than the number of samples.
- Random Forest - Random Forest is an ensemble learning method for classification, regression, and other tasks. It works by training multiple decision trees and combining their predictions to improve the overall performance of the model. Random Forest is widely used in applications such as image classification, object detection, and speech recognition
- …
You might drill into the concepts deeper by asking follow-up questions, while the main point here is to establish some sort of basic understanding of what’s happening within this specific field you are interested in.
Step 2: Gain Deeper Knowledge from the Experts
Great! Now that we have our key concepts, it's time to gather knowledge about the field. We have two ways of doing this:
- Talk to Experts: Talking to experts in the field is a great way to find common ground. You can reach out to 3-5 experts and ask them questions. Compare and contrast your interview notes and look for common ground. These will be the most important ideas.
- Read Textbooks: Reading the content page of different versions (3-5) of a college textbook can help you focus on the key concepts that have been covered by different top universities. If the order of several chapters in these textbooks remains unchanged, these key concepts must have a logical relationship, which is also important.
Step 3: Execute!
Now that you have a basic understanding of the field, it's time to deepen your understanding. There are two ways to do this:
- Do a Project: Doing a project in the field is the most effective way to learn quickly. You need to find a project that can be completed within a short period of time, such as an online course, an online challenge, or an independent research project. This will not only help you to quickly grasp the key concepts but also give you the opportunity to apply them in practice and gain valuable experience.
Learning about a new field can be daunting, but by following these steps, you can quickly and effectively gain a solid understanding of any subject.
Please feel free to let me know your thoughts on the content, format, or anything else. In the meantime, happy learning!
Cheers,
Sherman
Member discussion