CF

Building Full-Stack Apps with AI

8h 3m 16s
English
Paid

Building Full-Stack Apps with AI is a 34-lesson 8 hours 3 minutes self-paced course by Mckay Wrigley. The course "Building Full-Stack Apps with AI" teaches how to create full-fledged applications using artificial intelligence.

Course facts

Lessons
34
Duration
8 hours 3 minutes
Level
All levels
Language
English
Updated
Instructor
Mckay Wrigley
Price
Premium

The course "Building Full-Stack Apps with AI" teaches how to create full-fledged applications using artificial intelligence. It is suitable for both beginners and experienced developers. The course includes studying the technology stack, creating the first application (a to-do list), working with notes, and developing a Perplexity clone. The course contains step-by-step lessons on frontend, backend, authentication, payments, and deployment.

Additional

https://github.com/mckaywrigley/takeoff-notes-app-complete

Who teaches Building Full-Stack Apps with AI? Mckay Wrigley

Mckay Wrigley thumbnail

Mckay Wrigley is a US developer and AI educator who runs Takeoff AI, an applied-AI engineering academy that has grown into one of the most active LLM-focused course platforms on the market. He publishes daily on X / Twitter, is widely cited for his ChatGPT / Claude-integration tutorials, and has one of the larger independent applied-AI followings.

His CourseFlix listing carries sixteen Takeoff courses — covering everything from foundational LLM-integration with the OpenAI and Anthropic APIs through RAG pipelines, AI-assisted coding workflows, and full-stack AI product builds. Material is paid and aimed at working developers who want to ship AI features into real products rather than read survey-style introductions to the field.

What lessons are included in Building Full-Stack Apps with AI?

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#1: 1.1 Intro
All Course Lessons (34)
#Lesson TitleDurationAccess
1
1.1 Intro Demo
03:39
2
1.2 GitHub
02:43
3
1.3 Cursor
02:27
4
1.4 AI Tools
04:25
5
1.5 Frontend
08:16
6
1.6 Backend
09:27
7
1.7 Auth
04:38
8
1.8 Payments
02:38
9
1.9 Deployment
03:33
10
2.1 Intro
06:40
11
2.2 What You'll Need
02:46
12
2.3 Getting Help with Perplexity
03:31
13
2.4 Frontend Setup
08:07
14
2.5 GitHub Setup
09:44
15
2.6 Env Setup
11:17
16
2.7 Deployment Setup
15:13
17
2.8 Backend Setup
13:12
18
2.9 Auth Setup
12:14
19
2.10 Payments Setup
14:17
20
2.11 Layout Code
17:12
21
2.12 Git Workflow
02:40
22
2.13 Backend Code
56:53
23
2.14 Auth Code
21:37
24
2.15 Frontend Code
14:39
25
2.16 Payments Code
25:08
26
3.1 Intro
03:06
27
3.2 Project Setup
05:20
28
3.3 Boilerplate Work
01:07:11
29
3.4 Backend Work
26:28
30
3.5 Frontend Work
42:52
31
4.1 Intro
03:25
32
4.2 Setup
19:55
33
4.3 Schema with Composer
16:48
34
4.4 UI with V0 & Chat
21:15
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Frequently asked questions

What prerequisites should I have before starting this course?
The course is designed for both beginners and experienced developers, so no specific prerequisites are required. However, familiarity with basic programming concepts and some understanding of frontend and backend development could be helpful. Lessons like 'Frontend', 'Backend', and 'Auth' will cover essential areas that can benefit those who are newer to development.
What types of applications will I build in this course?
You will build several types of applications, including a to-do list application, a notes application, and a clone of Perplexity. These projects will help you learn how to integrate AI tools into full-stack applications and apply concepts such as authentication, payment processing, and deployment.
Is this course suitable for someone looking to specialize in AI development?
While the course includes the use of AI tools, its primary focus is on building full-stack applications. Therefore, it provides a good introduction to integrating AI into applications rather than a deep dive into AI development itself. It could serve as a stepping stone for further specialization in AI-focused courses.
What tools and platforms will I learn to use?
The course covers a variety of tools and platforms including GitHub for version control, and AI tools for application enhancements. Lessons such as 'GitHub Setup', 'Frontend Setup', and 'Backend Setup' will guide you through the necessary technology stack for building your applications.
What topics are not covered in this course?
The course does not delve deeply into advanced AI algorithms or machine learning techniques. It focuses on using existing AI tools within full-stack applications rather than developing AI systems from scratch.
How much time should I expect to commit to complete this course?
The course consists of 34 lessons and is designed to be completed at your own pace. The total runtime is not specified, but you should plan to spend additional time on practical exercises and projects, such as the to-do list and Perplexity clone, to fully grasp the material.
How will the skills learned in this course be applicable to my career or other learning paths?
The skills acquired in this course, such as integrating AI tools into applications, managing authentication, and deploying apps, are valuable for careers in software development, particularly in roles that require full-stack capabilities. These skills can also serve as a foundation for more advanced studies in AI or full-stack development.