CF

Build AI-Powered Apps – An AI Course for Developers

7h 3m 31s
English
Paid

AI is everywhere - but can you really create applications with it? Most developers have tried ChatGPT. Some have even inserted pieces of generated code into a project. But that's not quite the same as creating real AI-based features that make applications smarter, more convenient, and more valuable for users.

This is exactly what this course is dedicated to.

In "Creating Applications with AI", you will step by step understand key concepts, modern tools, and best practices for developing fully-fledged applications with AI support.

Why Every Developer Needs This Course Right Now

Practical Focus

You will learn:

  • How large language models (LLMs) work;
  • What tokens, context windows, and model parameters are;
  • How to write effective prompts using prompt engineering techniques;
  • How to build a chatbot from scratch with a clean and maintainable architecture;
  • How to create a tool for summarizing reviews that helps users make decisions faster;
  • How to integrate open-source models via Hugging Face and Ollama;
  • How to run models locally on your machine;
  • How to apply principles of clean code and best development practices;
  • How to use modern tools (Bun, Tailwind CSS, shadcn/ui, Prisma, and others) to create AI-powered full-stack applications.

Learning Through Practice

What You Will Create

  • Chatbot: An assistant for an amusement park, answering questions like "What rides are suitable for children under 10?", "Where can I find vegetarian dishes?" or "What time does the park open?". You will step by step implement the backend, organize the code according to principles of clean architecture, and create a modern frontend for convenient interaction.
  • Reviews Summarizer: A tool that turns dozens of user reviews into clear and useful insights. These same techniques can be applied to many other functions with AI integration.

About the Author: Mosh Hamedani (Code with Mosh)

Mosh Hamedani (Code with Mosh) thumbnail

Mosh Hamedani is the founder of Code with Mosh, one of the highest-volume independent online instructors in software education. He has been publishing courses continuously since the early Udemy era and has taught over a million students across his Udemy catalog and his standalone Code with Mosh platform. His teaching style is patient, rigorously structured, and deliberately beginner-tolerant — the courses are widely cited as some of the most accessible introductions to their respective topics.

The Code with Mosh catalog covers an unusually wide span: web development with HTML / CSS / JavaScript / React / Angular / Node.js, Python and Django, C# and .NET, mobile development with React Native and Flutter, SQL and database fundamentals, and the algorithm / data-structure interview prep tracks. Few independent instructors maintain this much breadth at consistent quality.

The CourseFlix listing under this source carries over 35 Code with Mosh courses spanning that range. Material is paid; Code with Mosh runs on per-course pricing on the original platform. Courses are aimed primarily at developers picking up a new technology from a clean start through to working production proficiency.

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#1: 1- Welcome
All Course Lessons (105)
#Lesson TitleDurationAccess
1
1- Welcome Demo
01:27
2
2- Prerequisites
00:56
3
3- What You'll Learn
03:55
4
4- Setting Up Your Development Environment
00:57
5
1- Introduction
00:37
6
2- Rise of AI Engineering
04:02
7
3- What are Large Language Models?
04:23
8
4- What Can You Do With Language Models?
02:26
9
5- Understanding Tokens and Context Window
03:03
10
6 - Counting Tokens
03:44
11
7- Choosing the Right Model
05:03
12
8- Understanding Model Settings
08:47
13
9- Calling Models
07:36
14
1- Introduction
01:13
15
2- Setting Up Bun
01:32
16
3- Creating the Project Structure
02:49
17
4- Creating the Backend
06:39
18
5- Managing OpenAI API Key
05:16
19
6- Creating the Frontend
02:46
20
7- Connecting the Frontend and Backend
05:14
21
8- Running Both Apps Together
03:24
22
9- Setting Up TailwindCSS
03:35
23
10- Setting Up Shadcn
06:31
24
11- Formatting Code with Prettier
05:03
25
12- Automating Pre-Commit Checks with Husky
06:51
26
1- Introduction
00:30
27
2- Building the Backend
00:37
28
2.1- Building the Chat API
06:27
29
2.2- Testing the API
01:58
30
2.3- Managing Conversation State
06:23
31
2.4- Input Validation
05:49
32
2.5- Error Handling
02:19
33
3- Refactoring the Chat API
02:09
34
3.1- Extracting Conversation Repository
05:21
35
3.2- Extracting Chat Service
06:45
36
3.3- Extracting Chat Controller
03:59
37
3.4- Extractring Routes
04:52
38
4- Building the Frontend
00:20
39
4.1- Building the ChatBot Component
07:29
40
4.2- Handling Form Submission
09:24
41
4.3- Calling the Backend
03:19
42
4.4- Rendering the Messages
04:38
43
4.5- Styling Messages
04:36
44
4.6- Rendering Markdown Text
02:31
45
4.7- Adding a Typing Indicator
04:10
46
4.8- Auto-Scrolling to the Latest Message
02:21
47
4.9- Improving Copy Behaviour
04:48
48
4.10- Improving the Look and Feel
08:05
49
4.11- Handling Errors
03:29
50
5- Refactorings
01:29
51
5.1- Extracting TypingIndicator Component
03:50
52
5.2- Extracting ChatMessages Component
05:20
53
5.3- Extracing ChatInput Component
08:29
54
5.4- Recap
02:37
55
1- What is Prompt Engineering
02:13
56
2- Anatomy of a Good Prompt
02:27
57
3- Providing Context
04:04
58
4- Controlling the Output Format
02:33
59
5- Providing Examples
02:45
60
6- Handling Errors and Edge Cases
01:56
61
7- Reducing Hallucinations
03:36
62
8- Refining Prompts
04:07
63
9- Improving Chatbot Responses
06:01
64
10- Adding Sound Effects
02:39
65
1- Introduction
00:51
66
2- Setting Up the Database
00:27
67
2.1- Setting Up MySQL
02:23
68
2.2- Setting Up Prisma
02:47
69
2.3- Defining the Prisma Schema
07:39
70
2.4- Running Migrations
06:02
71
2.5- Refining the Prisma Schema
03:14
72
2.6- Populating the Database with Realistic Data
03:29
73
3- Building the Backend
00:21
74
3.1- Creating the API to Fetch Reviews
07:54
75
3.2- Refactoring- Separation of Concerns
07:39
76
3.3- Creating an API for Summarizing Reviews
05:28
77
3.4- Generating Summaries
03:01
78
3.5- Refactoring- Extracting the LLM Logic
08:50
79
3.6- Refactoring- Extracting the Prompt
01:50
80
3.7- Storing the Summary
07:25
81
3.8- Handling Regeneration
02:48
82
3.9- Handling Edge Cases
06:33
83
3.10- Fetching the Summary
08:14
84
4- Building the Frontend
00:21
85
4.1- Displaying Reviews
06:36
86
4.2- Displaying Star Ratings
04:53
87
4.3- Displaying Loading Skeletons
04:39
88
4.4- Handling Errors
02:31
89
4.5- Introducing Tanstack Query
07:35
90
4.6- Displaying the Summary
02:43
91
4.7- Triggering Summary Generation
04:19
92
4.8- Displaying Loading Skeletons
04:18
93
4.9- Handling Errors
02:51
94
4.10- Refactoring with Mutations
04:24
95
4.11- Refactoring for Readability
02:45
96
4.12- Extracting the API Layer
05:29
97
1- Introduction
00:23
98
2- Why Use Open-Source Models
01:49
99
3- Finding Open-Source Models
04:18
100
4- Calling Hugging Face Models
05:36
101
5- Choosing the Right Model For the Job
06:44
102
6- Running Models Locally
03:14
103
7- Using Hugging Face Models with Ollama
02:30
104
8- Calling Ollama Models
03:04
105
1- Course Wrap Up
01:20
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Books

Read Book Build AI-Powered Apps – An AI Course for Developers

#TitleTypeOpen
11.5- Source Code PDF
21.6- Questions and Support PDF
31.7- Connect with Me PDF
42.2- Introduction to AI Models PDF
53.13- Setting Up a Full-Stack Project PDF
64.6- Building a Chatbot PDF
75.11 - Prompt Engineering Exercises PDF
85.12 - Prompt Engineering PDF

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Frequently asked questions

What are the prerequisites for this course?
The course assumes a basic understanding of programming and software development. It is beneficial to be familiar with JavaScript as many of the tools and frameworks used, such as Bun, Tailwind CSS, and Prisma, are JavaScript-based. The course begins with setting up your development environment, so prior experience in web development will be helpful.
What projects will I build during the course?
In this course, you will build a chatbot that serves as an assistant for an amusement park. It will be able to answer questions like 'What rides are suitable for children under 10?' and 'Where can I find vegetarian dishes?'. Additionally, you will create a tool for summarizing reviews, which helps users make decisions faster by integrating open-source models via platforms like Hugging Face and Ollama.
Who is the target audience for this course?
The course is designed for developers who are interested in integrating AI into their applications. It is suitable for those who have tried using AI tools like ChatGPT and want to move beyond basic usage to developing full-fledged AI-powered applications.
What specific tools and platforms will be covered?
The course covers modern tools such as Bun, Tailwind CSS, shadcn/ui, and Prisma. It also includes lessons on integrating AI models with platforms like OpenAI, Hugging Face, and Ollama. Additionally, you'll learn about maintaining clean code and best practices in development.
What topics are not covered in this course?
The course does not cover the underlying mathematical theories of AI models or advanced machine learning algorithms. It focuses on practical application and integration of pre-trained models rather than model training or data science aspects.
How much time should I commit to completing the course?
The course consists of 105 lessons. Although the total runtime is not specified, a typical online course of this scope would require several weeks to complete, assuming a part-time commitment of a few hours per week.
Will the skills learned in this course apply to other areas of development?
Yes, the skills learned in this course, such as prompt engineering, clean code principles, and integrating APIs, are valuable for various areas in software development. Understanding how to leverage AI in applications can be beneficial across diverse domains, enhancing both your career prospects and technical expertise.