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Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT

Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT

Loại khoá học: Game Development

Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!

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50.000 VND
130 VND
Đầy Đủ Bài Giảng
Học Online Tiện Lợi
Kích Hoạt Nhanh 2-5 Phút
Thanh toán tự động
Được phép tải xuống

Tổng quan

Nội dung khoá học

Đánh giá

Mô tả

*** AS SEEN ON KICKSTARTER ***

Learn key AI concepts and intuition training to get you quickly up to speed with all things AI. Covering:

  • How to start building AI with no previous coding experience using Python
  • How to merge AI with OpenAI Gym to learn as effectively as possible
  • How to optimize your AI to reach its maximum potential in the real world

Here is what you will get with this course:

1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.

2. Code templates – Plus, you’ll get downloadable Python code templates for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.

3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.

4. Real-world solutions – You’ll achieve your goal in not only 1 game but in 3. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.

5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.

Bạn sẽ học được gì

Build an AI

Understand the theory behind Artificial Intelligence

Make a virtual Self Driving Car

Make an AI to beat games

Solve Real World Problems with AI

Master the State of the Art AI models

Q-Learning

Deep Q-Learning

Deep Convolutional Q-Learning

A3C

Yêu cầu

  • High School Maths
  • Basic Python knowledge

Nội dung khoá học

22 sections

Welcome to the course!

5 lectures
Welcome Challenge!
02:29
Why AI?
05:10
Course Structure
00:39
Get the PDF Handbook here
00:07
EXTRA: Use ChatGPT to Build AI More Efficiently
00:10

---------- Part 0 - Fundamentals Of Reinforcement Learning ----------

1 lectures
Welcome to Part 0 - Fundamentals of Reinforcement Learning
01:14

Q-Learning Intuition

10 lectures
Plan of Attack
04:03
What is reinforcement learning?
11:26
The Bellman Equation
18:25
The "Plan"
02:12
Markov Decision Process
16:26
Policy vs Plan
12:55
Adding a "Living Penalty"
09:47
Q-Learning Intuition
14:45
Temporal Difference
19:26
Quiz 1
5 questions

Q-Learning Implementation

1 lectures
A Q-Learning Implementation for Process Optimization
00:53

---------- Part 1 - Deep Q-Learning ----------

1 lectures
Welcome to Part 1 - Deep Q-Learning
01:00

Deep Q-Learning Intuition

5 lectures
Plan of Attack
02:17
Deep Q-Learning Intuition - Learning
15:15
Deep Q-Learning Intuition - Acting
06:06
Experience Replay
15:45
Action Selection Policies
16:23

Deep Q-Learning Implementation

21 lectures
Get the Codes here
00:21
Deep Q-Learning Implementation - Step 1
06:59
Deep Q-Learning Implementation - Step 2
06:24
Deep Q-Learning Implementation - Step 3
08:23
Deep Q-Learning Implementation - Step 4
03:58
Deep Q-Learning Implementation - Step 5
05:45
Deep Q-Learning Implementation - Step 6
03:55
Deep Q-Learning Implementation - Step 7
02:44
Deep Q-Learning Implementation - Step 8
03:07
Deep Q-Learning Implementation - Step 9
08:17
Deep Q-Learning Implementation - Step 10
07:39
Deep Q-Learning Implementation - Step 11
07:35
Deep Q-Learning Implementation - Step 12
08:59
Deep Q-Learning Implementation - Step 13
08:55
Deep Q-Learning Implementation - Step 14
06:47
Deep Q-Learning Implementation - Step 15
02:09
Deep Q-Learning Implementation - Step 16
05:38
Deep Q-Learning Implementation - Step 17
09:39
Deep Q-Learning Implementation - Step 18
20:26
Deep Q-Learning Implementation - Step 19
05:19
Deep Q-Learning Implementation - Step 20
05:44

---------- Part 2 - Deep Convolutional Q-Learning ----------

1 lectures
Welcome to Part 2 - Deep Convolutional Q-Learning
00:35

Deep Convolutional Q-Learning Intuition

3 lectures
Plan of Attack
03:26
Deep Convolutional Q-Learning Intuition
07:12
Eligibility Trace
08:38

Deep Convolutional Q-Learning Implementation

14 lectures
Get the Codes here
00:21
Deep Convolutional Q-Learning Implementation - Step 1
05:17
Deep Convolutional Q-Learning Implementation - Step 2
05:30
Deep Convolutional Q-Learning Implementation - Step 3
11:06
Deep Convolutional Q-Learning Implementation - Step 4
04:33
Deep Convolutional Q-Learning Implementation - Step 5
07:14
Deep Convolutional Q-Learning Implementation - Step 6
04:05
Deep Convolutional Q-Learning Implementation - Step 7
02:03
Deep Convolutional Q-Learning Implementation - Step 8
08:20
Deep Convolutional Q-Learning Implementation - Step 9
09:48
Deep Convolutional Q-Learning Implementation - Step 10
07:37
Deep Convolutional Q-Learning Implementation - Step 11
14:13
Deep Convolutional Q-Learning Implementation - Step 12
03:54
Deep Convolutional Q-Learning Implementation - Step 13
05:24

---------- Part 3 - A3C ----------

1 lectures
Welcome to Part 3 - A3C
00:36

A3C Intuition

6 lectures
Plan of Attack
03:39
The three A's in A3C
04:44
Actor-Critic
06:36
Asynchronous
11:42
Advantage
15:21
LSTM Layer
15:36

A3C Implementation

16 lectures
Get the Codes here
00:21
A3C Implementation - Step 1
06:06
A3C Implementation - Step 2
05:53
A3C Implementation - Step 3
11:46
A3C Implementation - Step 4
08:26
A3C Implementation - Step 5
05:48
A3C Implementation - Step 6
07:14
A3C Implementation - Step 7
11:51
A3C Implementation - Step 8
18:28
A3C Implementation - Step 9
02:06
A3C Implementation - Step 10
09:59
A3C Implementation - Step 11
07:22
A3C Implementation - Step 12
09:59
A3C Implementation - Step 13
03:46
A3C Implementation - Step 14
20:21
A3C Implementation - Step 15
13:16

---------- Part 4 - PPO and SAC ----------

1 lectures
Build and Train the PPO and SAC models for a Self-Driving Car! Theory included.
01:05

---------- Part 5 - Intro to Large Language Models (LLMs) ----------

1 lectures
Welcome to Part 5 - Intro to Large Language Models (LLMs)
00:22

LLMs Intuition

8 lectures
Introduction to LLMs
01:40
Ingredients of an LLM
02:50
Who invented LLMs?
01:24
How LLMs generate text
02:56
Inside an LLM - Under the Hood
04:43
LLM Parameters
02:04
LLM Context Window
02:07
Fine-Tuning LLMs
02:58

LLMs Implementation

8 lectures
Get the Codes here
00:41
Fine-Tuning LLMs with Hugging Face - Step 1
09:59
Fine-Tuning LLMs with Hugging Face - Step 2
12:13
Fine-Tuning LLMs with Hugging Face - Step 3
07:43
Fine-Tuning LLMs with Hugging Face - Step 4
05:11
Fine-Tuning LLMs with Hugging Face - Step 5
12:59
Fine-Tuning LLMs with Hugging Face - Step 6
06:42
Fine-Tuning LLMs with Hugging Face - Step 7
10:37

THANK YOU

1 lectures
THANK YOU Video
02:40

Annex 1: Artificial Neural Networks

9 lectures
What is Deep Learning?
12:34
Plan of Attack
02:51
The Neuron
16:15
The Activation Function
08:29
How do Neural Networks work?
12:47
How do Neural Networks learn?
12:58
Gradient Descent
10:12
Stochastic Gradient Descent
08:44
Backpropagation
05:21

Annex 2: Convolutional Neural Networks

9 lectures
Plan of Attack
03:31
What are convolutional neural networks?
15:49
Step 1 - Convolution Operation
16:38
Step 1(b) - ReLU Layer
06:41
Step 2 - Pooling
14:13
Step 3 - Flattening
01:52
Step 4 - Full Connection
19:24
Summary
04:19
Softmax & Cross-Entropy
18:20

Extra Materials

7 lectures
Extra Section - Q-Learning Intro
00:11
Extra Section - Q-Learning Part I
01:15
Extra Section - Q-Learning Part II
04:07
Extra Section - Q-Learning Part III
07:04
Extra Section - Q-Learning Part IV
04:40
Extra Section - Q-Learning - Part V
01:09
Extra Section - Q-Learning Section VI
08:05

Congratulations!! Don't forget your Prize :)

2 lectures
Huge Congrats for completing the challenge!
01:15
Bonus: How To UNLOCK Top Salaries (Live Training)
00:44

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