HangukQuant 3 Courses is presented here with a complete file-by-file inventory, a clear buyer-fit assessment and direct access through Courses On Budget. No profit claims, invented modules or hidden curriculum assumptions are added.
HangukQuant 3 Courses: What Is Included?
The existing page confirms three quantitative-trading courses. The package covers trading costs, advanced Python backtesting, financial-data retrieval and a MongoDB-oriented quant database, with runnable code and configuration files.
Instead of forcing you to buy from a vague sales page, this listing lets you inspect the actual package first. Compare the curriculum below, check the latest course updates, then decide whether the material fits your current study plan.
Who should consider this course?
Python-capable quant learners who want papers, runnable scripts and database-oriented implementation material.
Core Topics Confirmed by the Course Files
| Included topic or resource | Verification |
|---|---|
| Costful Trading | Confirmed by the supplied course index |
| Flirting with CPUs – Advanced Backtesting in Python | Confirmed by the supplied course index |
| Retrieval of Financial Data and Implementation of a Quant (MongoDB) Database | Confirmed by the supplied course index |
| Creating a Data Service Layer for Data Retrieval | Confirmed by the supplied course index |
| Design and Implementation of a Quant Database | Confirmed by the supplied course index |
Complete HangukQuant – 3 courses Course Index
Open each section to inspect the exact filenames and sizes supplied with this package. The index is preserved in full.
Costful Trading (3 files)
- 01. Costful Trading.pdf (1.80 MB)
- 02. Costful Trading (w Code).pdf (1.86 MB)
- 03. Code Files (Runnable Python Scripts and Config Files).zip (28.36 MB)
Flirting with CPUs – Advanced Backtesting in Python (with Code) (4 files)
- 01. Full Table of Contents.pdf (168.19 KB)
- 02. Flirting with CPUs – Advanced Backtesting in Python (with Code).pdf (1.85 MB)
- 03. Flirting with CPUs – Advanced Backtesting in Python (with Code).pdf (2.06 MB)
- 04. Downloadable Python Code.zip (7.82 KB)
01. Creating a Data Service Layer for Data Retrieval (with Code) (3 files)
- 01. Full – Table of Contents.pdf (133.91 KB)
- 02. Creating a Data Service Layer for Data Retrieval.pdf (297.82 KB)
- 03. Creating a Data Service Layer for Data Retrieval (FULL).pdf (432.54 KB)
02. Design and Implementation of a Quant Database (with Code) (3 files)
- 01. Full – Table of Contents.pdf (153.28 KB)
- 02. Design and Implementation of a Quant Database.pdf (422.78 KB)
- 03. Design and Implementation of a Quant Database (FULL).pdf (630.63 KB)
03. Code (1 file)
- thinkificzip-220824-115054.zip (21.89 KB)
04. Improving Our Database Service (2 files)
- 01. Table of Contents and Result.pdf (130.21 KB)
- 02. Improving Our Database Service.pdf (316.73 KB)
03. Code Files (2 files)
- db_service-221009-181449.py (11.56 KB)
- generic_wrapper-221009-181449.py (5.35 KB)
- Full index visible before purchase
- Multiple learning files kept in one organized package
- Direct digital access through the product page
- Educational material is not a guarantee of trading results
- Some files or platform demonstrations may reflect their recording date
- Review the complete format list for device compatibility
Frequently Asked Questions
What exactly is included?
The supplied index confirms 18 files in 9 indexed folders, totaling 38.61 MB. Expand the course-index section above for every filename.
Is this financial advice or a profit guarantee?
No. This is educational course material. Trading and investing involve risk, and results depend on the learner’s decisions, experience and market conditions.
Where can I find current deals and new releases?
Use the active discounts page for current offers and the updates page for newly added material.
HangukQuant – 3 courses is easiest to evaluate when the full package is visible. The verified index above shows exactly what you receive, while the buyer-fit section helps you decide whether the material matches your goals.
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Independent learning resource: Python 3 documentation
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