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AI Engineering with Go

11h 13m 5s
English
Paid

Course description

Who said that AI applications should only be developed in Python? In this course, you will learn how to practically integrate AI into real applications using Go—starting from the basic use of LLM and gradually moving to the creation of dynamic, intelligent, and autonomous AI agents. Each module of the course is result-oriented: you will not just study the technologies, but create complete projects, enhancing your portfolio and strengthening your skills.

Read more about the course

During the course you will:

  • Create more than three full-fledged AI projects and deploy them;
  • Learn how to work with LLM API (OpenAI, Claude) using Go;
  • Implement vector databases, embeddings, and semantic search;
  • Learn to build interactions with models using function calling and structured queries;
  • Deploy AI applications to production with a well-thought-out architecture;
  • Create step-by-step AI systems and intelligent content processing mechanisms.

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#1: 001 Project Overview

All Course Lessons (43)

#Lesson TitleDurationAccess
1
001 Project Overview Demo
02:10
2
002 Setting Up Your Development Environment
05:15
3
003 Initializing Project From Template and Deploying
14:50
4
004 Introducing the Project and Building Basic Flashcards App
34:17
5
005 Making the First LLM Call
13:51
6
006 Adding AI to Our Project
14:18
7
007 Scaffolding our API to make LLM Calls
28:16
8
008 Improving our Prompts
15:01
9
009 Building the Frontend
12:36
10
010 Deploying the Frontend
05:29
11
011 Ingesting Real Notes
07:12
12
012 Polishing the Project
27:18
13
013 Wrap Up and Challenges
01:27
14
014 BONUS LLM Streaming
22:00
15
015 Project Overview -
03:18
16
016 Function Calling Intro
17:25
17
017 Using Function Calls in Projects Part 1
36:07
18
018 Using Function Calls in Projects Part 2
09:13
19
019 Implementing the Frontend
12:34
20
020 Adding Polish
04:12
21
021 Project Intro --
04:00
22
022 Introduction to Vector DBs
07:31
23
023 Vector DB Example and Demo
19:53
24
024 Vector DB Crash Course
22:55
25
025 Quiz v2 - API Scaffold
14:25
26
026 Index Notes
20:07
27
027 Implementing Our New Quiz API
23:46
28
028 Frontend and Polish
19:46
29
029 Deploying to Production
07:26
30
030 Project Overview ---
05:59
31
031 AI Agents Overview
08:49
32
032 Let's build an AI agent
19:31
33
033 Integrating an AI agent into our app
28:57
34
034 Implementing the frontend --
05:08
35
035 Refining our agent prompt + intro to tools
15:24
36
036 Building tools
21:59
37
037 Polish
33:19
38
038 Deploying to production --
03:21
39
039 How Does MCP Work
21:02
40
040 MCP Servers in Practice
16:56
41
041 Building MCP Servers
20:27
42
042 Integrating MCP Servers in Your App
34:09
43
043 MCP Best Practices
11:26

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