CF

Build an AI Stock Analyzer using ChatGPT, Python and LangChain

3h 3m 56s
English
Paid

Build an AI Stock Analyzer using ChatGPT, Python and LangChain is a 16-lesson 3 hours 3 minutes self-paced course by Zero To Mastery. Create your own AI application for stock analysis and portfolio optimization using OpenAI GPT models, Python, and LangChain (100% suitable for beginners).

Course facts

Lessons
16
Duration
3 hours 3 minutes
Level
All levels
Language
English
Updated
Instructor
Zero To Mastery
Price
Premium

Create your own AI application for stock analysis and portfolio optimization using OpenAI GPT models, Python, and LangChain (100% suitable for beginners). During the course, you will also study investment strategies such as modern portfolio theory and the Black-Litterman model.

Who teaches Build an AI Stock Analyzer using ChatGPT, Python and LangChain? Zero To Mastery

Zero To Mastery thumbnail

Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.

The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.

The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.

What lessons are included in Build an AI Stock Analyzer using ChatGPT, Python and LangChain?

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#1: Introduction
All Course Lessons (16)
#Lesson TitleDurationAccess
1
Introduction Demo
04:47
2
OpenAI Key Setup
03:01
3
What is LangChain?
05:32
4
Python - LangChain OpenAI Setup
09:36
5
Python - Download the Stock Data
04:41
6
Introduction to Finance
07:54
7
Top Fundamental KPIs for Stock Analysis
08:03
8
Top Trading KPIs for Stock Analysis
08:41
9
Python - Top Trading KPIs - Part 1
28:34
10
Python - Top Trading KPIs - Part 2
05:55
11
Modern Portfolio Theory
11:11
12
Python - Modern Portfolio Theory
14:39
13
The Black-Litterman Model
08:16
14
Python - Black-Litterman Model
21:59
15
Building an Optimized Python Script
28:56
16
From Diogo: How I Invest
12:11
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Frequently asked questions

What are the prerequisites for enrolling in this course?
This course is designed to be 100% suitable for beginners, so no prior knowledge of stock analysis, AI models, or Python programming is necessary. However, a basic understanding of programming concepts and financial terminology can be beneficial for grasping the content more quickly.
What will I build by the end of the course?
By the end of the course, you will have built an AI application capable of stock analysis and portfolio optimization. This application will utilize OpenAI's GPT models, Python, and LangChain to analyze stock data and apply investment strategies like modern portfolio theory and the Black-Litterman model.
Who is the target audience for this course?
The course is aimed at beginners who are interested in applying AI to finance, specifically in stock analysis and portfolio management. It is also suitable for those looking to explore Python programming in the context of financial technology.
How does this course compare in depth and scope to other AI finance courses?
This course offers a focused introduction to using AI models like ChatGPT in the context of stock analysis and portfolio optimization. While it covers essential financial theories and Python programming, it may be less comprehensive in terms of covering other AI applications in finance, compared to more advanced courses.
What specific tools and platforms will be used in the course?
The course will primarily use Python for programming, OpenAI's GPT models for AI capabilities, and LangChain for managing language models. These tools will be integrated to download and analyze stock data, and implement investment strategies such as the modern portfolio theory and the Black-Litterman model.
What topics are not covered in this course?
The course does not cover advanced financial derivatives, algorithmic trading strategies beyond the basics, or other AI models outside of OpenAI's GPT. It focuses specifically on stock analysis and portfolio optimization using the mentioned tools and strategies.
How can the skills gained in this course benefit my career?
The skills acquired in this course can be valuable for careers in financial technology, data analysis, and AI development. The integration of AI with financial analysis is a growing field, and proficiency in tools such as Python, OpenAI, and LangChain can enhance your employability in roles focusing on AI-driven financial solutions.