Build AI-Powered Apps – An AI Course for Developers
7h 3m 31s
English
Paid
Course description
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.
Read more about the course
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.
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# | Title | Duration |
---|---|---|
1 | 1- Welcome | 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 |
Books
Read Book Build AI-Powered Apps – An AI Course for Developers
# | Title |
---|---|
1 | 1.5- Source Code |
2 | 1.6- Questions and Support |
3 | 1.7- Connect with Me |
4 | 2.2- Introduction to AI Models |
5 | 3.13- Setting Up a Full-Stack Project |
6 | 4.6- Building a Chatbot |
7 | 5.11 - Prompt Engineering Exercises |
8 | 5.12 - Prompt Engineering |
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