CF

AI Engineering Course

1h 36m 46s
English
Paid
This course is designed to help programmers and developers transition into the field of artificial intelligence engineering. You will thoroughly explore vector databases, indexing, large language models (LLM), and the attention mechanism.

By the end of the course, you will understand how LLMs work and be able to use them to create real applications.

What you will learn:

  • Develop mental models of how LLMs in the style of GPT work
  • Understand processes such as tokenization, embeddings, attention, and masking
  • Optimize LLM inference using caching, batching, and quantization
  • Design and deploy RAG pipelines using vector databases
  • Compare methods: prompt engineering, fine-tuning, and agent-based architectures
  • Debug, monitor, and scale LLM systems in production

About the Author: get.interviewready.io

get.interviewready.io thumbnail

get.interviewready.io is the paid course platform of Gaurav Sen, a software engineer (formerly at Uber) and one of the most widely watched system-design-interview educators on YouTube. His teaching style focuses on building the mental model from first principles — load balancers, sharding, queues, the trade-offs of CAP — rather than memorising specific architectures.

The CourseFlix listing carries his System Design Course and AI Engineering Course. Material is paid and aimed at engineers preparing for senior-level technical interviews at large tech companies, plus a newer track on building AI / LLM-powered systems.

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#1: Course Intro
All Course Lessons (21)
#Lesson TitleDurationAccess
1
Course Intro Demo
02:01
2
Usecase
01:48
3
How are vectors constructed
06:43
4
Choosing the right DB
03:27
5
Vector compression
03:27
6
Vector Search
06:59
7
Milvus DB
05:38
8
LLM Intro
00:43
9
How LLMs work
08:31
10
LLM text generation
03:08
11
LLM improvements
05:10
12
Attention
05:28
13
Transformer Architecture
03:40
14
KV Cache
08:28
15
Paged Attention
04:38
16
Mixture Of Experts
04:01
17
Flash Attention
03:40
18
Quantization
03:33
19
Sparse Attention
05:14
20
SLM and Distillation
05:31
21
Speculative Decoding
04:58
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Books

Read Book AI Engineering Course

#TitleTypeOpen
11. Vector+Embeddings+&+Semantic+Space PDF
22. Compression+&+Quantization_+Scaling+Vectors+Efficiently-4 PDF
33. Indexing+Techniques_+Making+Vector+Search+Scale PDF
44. Search+Execution+Flow_+From+Query+to+Result PDF
55. LLMs+and+RAG PDF
66. What+is+Attention+and+Why+Does+It+Matter PDF
77. Paged+Attention PDF
88. Quantization+Summary PDF

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Frequently asked questions

What is AI Engineering Course about?
This course is designed to help programmers and developers transition into the field of artificial intelligence engineering. You will thoroughly explore vector databases, indexing, large language models (LLM), and the attention mechanism.
Who teaches this course?
It is taught by get.interviewready.io. You can find more courses by this instructor on the corresponding source page.
How long is the course?
It contains 21 lessons with a total runtime of 1 hour 36 minutes. Every lesson is available to watch online at your own pace.
Is it free to watch?
It is part of CourseFlix's premium catalog. A subscription unlocks the full video player; the course description, table of contents, and preview information are available to everyone.
Where can I watch it online?
The course is available to watch online on CourseFlix at https://courseflix.net/course/ai-engineering-course. The page hosts every lesson with the integrated video player; no download is required.