Uploaded May 2024 | Updated September 2026, 2 weeks ago
If you can't beat them, join them. Don't fear AI taking your job. Here is what I am doing to stay relevant and hirable.
In this video, I will talk about AI for developers and how you can build cool applications and services.
In the video, the speaker recommends two resources for learning about AI and building AI-powered projects:
Key Topics Summary:
- Opportunities for developers to learn and utilize AI services
- Examples of successful AI-powered projects
- Resources for learning about AI and building AI-powered projects
- Low-code services like Air Ops for creating AI workflows
- Integration of AI into applications
1. Deep Learning AI: The speaker suggests checking out Andrew Ng's website called Deep Learning AI, which offers free deep learning and machine learning courses. The website has courses such as "CGPT for Prompt Engineers and Developers" and "Pre-processing Unstructured Data with LLM Application." It is recommended as a good starting point for learning about AI.
2. LangChain: The speaker mentions a library called LangChain, which can be used to work with AI. They recommend checking out LangChain's documentation, which covers installation, working with models, data retrieval, setting up chains, and building agents. LagChain supports both TypeScript and Python, with the speaker suggesting that using Python offers more functionality.
Additionally, the video briefly mentions AirOps, which allows non-technical people to create AI workflows. While the speaker doesn't explicitly recommend it, they show how it can be used to implement AI functionality without designing everything from scratch. AirOps offers templates and examples for building various AI workflows.
Remember to like, subscribe, and let me know what you think in the comments. I look forward to seeing you in the next video!
If you can't beat them, join them. Don't fear AI taking your job. Here is what I am doing to stay relevant and hirable.
In this video, I will talk about AI for developers and how you can build cool applications and services.
In the video, the speaker recommends two resources for learning about AI and building AI-powered projects:
Key Topics Summary:
- Opportunities for developers to learn and utilize AI services
- Examples of successful AI-powered projects
- Resources for learning about AI and building AI-powered projects
- Low-code services like Air Ops for creating AI workflows
- Integration of AI into applications
1. Deep Learning AI: The speaker suggests checking out Andrew Ng's website called Deep Learning AI, which offers free deep learning and machine learning courses. The website has courses such as "CGPT for Prompt Engineers and Developers" and "Pre-processing Unstructured Data with LLM Application." It is recommended as a good starting point for learning about AI.
2. LangChain: The speaker mentions a library called LangChain, which can be used to work with AI. They recommend checking out LangChain's documentation, which covers installation, working with models, data retrieval, setting up chains, and building agents. LagChain supports both TypeScript and Python, with the speaker suggesting that using Python offers more functionality.
Additionally, the video briefly mentions AirOps, which allows non-technical people to create AI workflows. While the speaker doesn't explicitly recommend it, they show how it can be used to implement AI functionality without designing everything from scratch. AirOps offers templates and examples for building various AI workflows.
Remember to like, subscribe, and let me know what you think in the comments. I look forward to seeing you in the next video!
![Strapi v5 Crash Course 2025 [ Part 13 Finishing Up ]](https://i.ytimg.com/vi/Lmedh0HzxpE/mqdefault.jpg "Strapi v5 Crash Course 2025 [ Part 13 Finishing Up ]
In this final part, we will create a Featured Articles Component in Strapi and finalize our project.
👉 Lesson Notes: https://www.codingafterthirty.com/courses/strapi-5-crash-course-2025/final-lesson-adding-featured-articles-and-finishing-up
👉 Learn more about Strapi: https://strapi.link/learn-more
We now have a working backend that can serve data to our frontend. In our next series, we will look at how to build an Astro.js and Next.js app to consume our data.")
