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Build Fast Masterclass

7h 22m 11s
English
Paid

Ready to launch your AI product without losing your sanity? This course will guide you in creating a product that generates income in 30 days or less. Unlike other courses, you'll actively participate by coding five live-production projects—no prior AI experience necessary—while connecting with a community of seasoned builders, from FAANG engineers to Wall Street traders. No business idea required; we'll provide the idea and teach you to build it quickly!

Stop Learning, Start Building

The most common mistake is consuming too much information. We often believe that reading or watching endless tutorials will lead to transformation—but they don't. Instead, embrace "just-in-time learning." By learning and immediately applying that knowledge through building projects, it solidifies in your mind. Doing so not only enhances retention but also provides the ultimate reward: shipping a working product.

Get To Building, Faster

Let's face it, learning without creating can be tiresome. We are builders at heart, and builders desire to create products that captivate users. Though you could attempt to learn independently from scattered resources, this course allows you to transform from a novice to someone who can build and deploy an AI chatbot or AI voice app effectively. BuildFast Academy exists for this transformative journey.

Who Said Learning AI Had to Be Hard?

Forge meaningful connections with fellow builders. Building online can seem isolating, but it doesn’t have to be. BuildFast Academy fosters a community of like-minded individuals across diverse backgrounds and professions, all aiming to start building together.

Use It or Lose It

Experts advocate that deliberate practice is crucial for learning. This involves focused, structured, and goal-oriented practice, often supported by expert advice. It is an active process where constant feedback and improvement are key.

Course Videos Overview

You've got instant access to these videos upon joining BuildFast:

  1. LLMs: Overview, using LLMs in Langchain, open-source LLMs, chat model, embedding text.
  2. Chains: Chains 101, LLM Chain, Sequential Chain, and four other essential Langchain chains.
  3. Prompt: Prompts 101, Example Prompts, Output Parser.
  4. Memory: Understanding four types of Memory, utilizing Memory in a Chain, adding Memory to an Agent.
  5. Document Loaders: Introduction, appropriate usage, importing data from various formats.
  6. Indexes: Indexes 101, Retrievers, and Text Splitters.
  7. Vector Database & Embeddings: Vector databases overview, applications, and use-cases.

Projects You'll Build

True learning happens when you ship a product. These are the projects you will create:

  1. AI Voice and Image App: Basics of AI Voice and AI Image, building an app related to food with these technologies.
  2. AI Chatbot: Develop an AI chatbot for personal assistance.
  3. Chat with CSV/PDF: Extend the Chatbot project to include CSV or PDF functionality.
  4. Vector Database Project: Embed, store, and retrieve data using a vector database, enhancing interaction capabilities.
  5. Fine-tune Your Own LLM: Detailed guidance on customizing and tuning an LLM.

About the Author: Build Fast Academy

Build Fast Academy thumbnail

Build Fast Academy is a teaching brand focused on the data-and-AI-engineering craft for working professionals — particularly the patterns for building and shipping AI-powered products quickly using modern Python and data tooling.

The CourseFlix listing carries the Build Fast Masterclass — a structured curriculum on the modern Python data-and-AI stack, covering the patterns for fast iteration on data-intensive products and AI features.

Material is paid and aimed at engineers and product builders shipping data-and-AI products. For broader content, see CourseFlix's Data processing and analysis and Python category pages.

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#1: Instruction Manual (CRITICAL)
All Course Lessons (76)
#Lesson TitleDurationAccess
1
Instruction Manual (CRITICAL) Demo
04:43
2
How to Succeed
03:03
3
What you can expect (success!)
04:54
4
How to Come up With Project Idea
04:56
5
Welcome! About Me!
06:32
6
What to Read / Learn Before the Course
02:10
7
How to Use This Course
02:20
8
How to Learn Anythin
08:12
9
How To Learn
03:53
10
How to Debug Your Issues
04:59
11
[Concept] LLMs
03:11
12
[Concept] Chains
04:05
13
How To Use Google Collab
02:13
14
[Collab] Chains
04:48
15
[Concept] Prompts
02:39
16
[Collab] Prompts
05:52
17
[Concept] Memory
06:14
18
[Collab] Memory in Langchain
06:24
19
[Concept] Document Loaders
04:13
20
[Collab] Document Loader
09:23
21
[Concept] Indexes
02:35
22
[Concept] Vector Database/Embeddings
04:57
23
[Misc] AI Voice / AI Image
02:22
24
Streamlit Overview
02:19
25
Overview of the Project
01:38
26
[Coding] Project 1
28:37
27
[Concept] Agents
02:32
28
[Collab] Agents & Tools
08:45
29
[Concept] How to Create a Personal Chatbot Overview
04:40
30
How to Fit It All In (Context Windows Explained
10:57
31
What we'll be building
00:49
32
[Coding] Project 2
16:49
33
What we're building
01:44
34
[Coding] Project 3
22:46
35
Project Intro
01:08
36
What we're building
01:22
37
High Level Overview & Concepts
01:29
38
Understanding Scraping
02:54
39
Scraping for Chroma
18:08
40
Chatbot for Chroma
18:34
41
Scraping for Pinecone
09:45
42
Chatbot for Pinecone
09:06
43
Project Overview
00:48
44
What we're building
07:42
45
Gathering The Data
05:53
46
Putting into JSONL format
05:59
47
Starting the fine-tuning model
02:32
48
Following the fine-tuning
00:43
49
Testing the New Fine-Tuned Model
06:59
50
Interview w/ AI Abs Founders
46:59
51
Gotta go Fast
11:46
52
1- Pros and Cons of Streamlit
02:11
53
2- Things to Consider in Production
05:27
54
3-Boilerplate Action
07:51
55
4-My tech stack (actual app walkthrough)
06:35
56
5-Actionable Next Steps
02:49
57
From 0 to 250k+ Software Engineer Offers
00:00
58
TLDR; Of How It All Happened
00:00
59
Explain Like I'm 5: Leetcode
00:00
60
How I Secured Multiple 250k+ Offers
05:17
61
The Software Offers I got
00:00
62
Why You Should Care..
00:00
63
Monk Mindset
00:00
64
Critical Resources to Use
00:00
65
Fundamentals. Fundamentals. Fundaments ((CRITICAL))
00:00
66
The Secret Study Technique *no one* talks about..
08:19
67
Beat them at their own games (( Use Company Lists ))
05:18
68
Underrated af (but as important)..
05:25
69
Securing Senior Offers..
00:00
70
Secret Hack (for studying)..
03:24
71
Don't waste your time..
05:51
72
How to improve *quickly*
03:19
73
Pass Leetcode rounds *with ease*
04:44
74
How to properly stack interviews
04:16
75
How to add 50-100k to your offer..
08:48
76
The Future: More money & more fulfillment
04:36
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Frequently asked questions

What are the prerequisites for enrolling in this course?
No prior AI experience is necessary to enroll in this course. The course is designed to guide you through creating a product from scratch, focusing on 'just-in-time learning' to help you build and deploy AI applications. However, it's beneficial to have a basic understanding of programming concepts and comfort with coding, as you will be actively participating in coding five live-production projects.
What kind of projects will I build during the course?
Participants will engage in building five live-production projects. These include creating an AI chatbot and an AI voice app. The course involves understanding concepts such as Language Model Models (LLMs), prompts, memory, document loaders, and vector databases. You will also work with tools like Google Collab and Streamlit, ensuring you can build and deploy these AI applications effectively.
Who is the target audience for this course?
This course is ideal for individuals who are eager to transition from consuming information to actively building AI products. It's suitable for beginners with no prior AI experience, as well as seasoned professionals from diverse backgrounds, including FAANG engineers and Wall Street traders, looking to enhance their skills by participating in a community of builders.
How does the depth and scope of this course compare to similar courses?
Unlike other courses that focus heavily on theory, this course emphasizes 'just-in-time learning' and practical application. It offers a structured approach to building and deploying real AI products quickly. The course covers 76 lessons, including detailed modules on concepts like chains, agents, and vector databases, making it a practical choice for those who prefer hands-on learning.
What specific tools or platforms are used in this course?
The course makes extensive use of Google Collab and Streamlit for building and deploying projects. Participants will learn to work with various concepts such as chains, prompts, memory, and document loaders within these platforms. Additionally, the course involves working with vector databases and embedding techniques to enhance AI applications.
What topics or areas are not covered in this course?
While the course focuses on building and deploying AI products, it does not cover topics such as deep theoretical AI research or advanced machine learning algorithms. The emphasis is on practical application and rapid development, rather than in-depth exploration of AI theory or data science methodologies.
What is the expected time commitment for completing the course?
The course consists of 76 lessons and is designed to be completed in 30 days or less. This timeline aligns with the course's goal to help you launch an AI product quickly. While the exact time commitment can vary based on individual pace and prior experience, the structure encourages active participation and rapid application of learned concepts.