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​​Join us for a live Q&A session with Alexey Grigorev and Ivan Brigida about the upcoming Stock Market Analytics course!

​📅 Live Q&A Session: April 14 📅 Course Start Date: May 19

​This is your opportunity to explore the course content and determine how it aligns with your learning goals before enrolling. Alexey and Ivan will walk you through the syllabus, share key insights from the registration form submissions, and provide an overview of the capstone project required for certification.

​Come prepared with your questions! Use this link to submit them in advance.

​Don't miss this chance to ask course-related questions, share your expectations, and learn about the course format and instructors.

​🔗 For more course details, visit: https://pythoninvest.com/course 📝 To register, fill out the form: https://forms.gle/qP19FoBSnzmZsJYt6

​​​​DataTalks.Club is the place to talk about data. Join our slack community!

Second workshop in our series on financial data automation and analysis. Outline covers Data Acquisition & Preprocessing (Yahoo Finance API, SQLite storage, generating additional variables); Exploratory Analysis & Time-Series Features; Forecasting Techniques (Prophet, ARIMA, Deep Learning); Visualization & Deployment (Plotly, Streamlit Cloud, GitHub Actions).

Creating Real-World Economic Insights Using Databases, Automation, and Cloud Deployment – Ivan Brigida

Description: In this hands-on workshop, participants will build a data pipeline for economic analysis with an AI-assisted development setup, utilizing the Cline (prev. ClaudeDev) plugin in VS Code and Anthropic's AI model. We'll cover essential skills like API data retrieval, database configuration, data workflows, and containerized deployment. With automated data collection and storage, participants will analyze real economic metrics such as interest rates, debt-to-GDP ratios, and stock trends. The focus will be on combining technical skills with AI-powered productivity to derive insights into current economic conditions.

​About the speaker: Ivan Brigida, a Senior Business Analyst at Google, brings over a decade of expertise in data science, economic analysis, and business intelligence. Ivan is the creator of pythoninvest.com, where he publishes analytical articles on retail investing, and he developed the Stock Markets Analytics Zoomcamp, a course focused on creating algorithmic trading strategies for stock markets using machine learning.

Join our slack: https://datatalks.club/slack.html

Join us for a live Q&A session with Alexey Grigorev and Ivan Brigida about the upcoming Stock Market Analytics course.

It is your opportunity to explore the course content and see how it aligns with your learning goals before you commit. Alexey and Ivan will walk you through the course syllabus, share the highlights from the Registration form submissions, and give you an overview of a Capstone project you will be required to submit to obtain a certification. Take your chance to ask course-related questions, share your expectations, and learn about the format and instructors. Register to join this live event! Our free Stock Market Analytics Zoomcamp starts on April 15.

For more details about the course, check the course

To register for the course, submit this form: https://docs.google.com/forms/d/e/1FAIpQLSc5H6Jc-HJg9B7irveRASJCAS4BTnJcvM2QX2ykIGZ0UNgCPQ/viewform?usp=send_form

We talked about:

Ivan’s background How Ivan became interested in investing Getting financial data to run simulations Open, High, Low, Close, Volume Risk management strategy Testing your trading strategies Sticking to your strategy Important metrics and remembering about trading fees Important features Deployment How DataTalks.Club courses helped Ivan Ivan’s site and course sign-up

Links:

Exploring Finance APIs: https://pythoninvest.com/long-read/exploring-finance-apis Python Invest Blog Articles: https://pythoninvest.com/blog

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Outline: Stock trading; Starting with trading; Machine learning for stock predictions.