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.
Build an AI Stock Analyzer using ChatGPT, Python and LangChain
3h 3m 56s
English
Paid
About the Author: Zero To Mastery
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.
Watch Online 16 lessons
0:00
/ #1: Introduction
All Course Lessons (16)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 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.