Module 1: Python for finance: 8 hours

THE LINGUA FRANCA OF DATA SCIENCE, MACHINE LEARNING, AND FINANCE

QDC Lecture 1 (Module 1): Introduction to Python by Saeed Amen: 2 hours

• Installing Anaconda and PyCharm – Instructions

QDC Lecture 2 (Module 1): Data Analysis in Python by Saeed Amen: 2 hours

• Data Analysis in Python – Forum

QDC Lecture 3 (Module 1) Analysis of financial data using Python by Saeed Amen: 2 hours

• Analysis of Financial Data Using Python – Forum

QDC Lecture 4 (Module 1): Financial market case studies using Python by Saeed Amen: 2 Hours

• Financial Market Case Studies Using Python – Forum

Module 1 Test

Module 2: Databases in finance – Kdb+/q: 9 hour 30 minutes

AN UNRIVALED TOOL FOR BIG DATA AND HIGH-FREQUENCY DATA

QDC Lecture 5 (Module 2): Overview of kdb+/q by Paul Bilokon: 1 hour 50 minutes

• Installing kdb+/q – Slides
• What is kdb+/q? – Slides
• Variables, types, and operators – Slides (no solutions)
• Overview of kdb+/q – Self Study Forum

QDC Lecture 6 (Module 2): Foundation of the q programming language by Paul Bilokon: 1 hour 36 minutes

• Lists – Slides
• Dictionaries – Slides 
• Foundation of the q programming language – Forum

QDC Lecture 7 (Module 2): Working with tables by Paul Bilokon: 1 hour 50 minutes

• Control Flow – Slides
• Iterators  – Slides
• q-sql – Slides
• Working with tables – Forum

QDC Lecture 8 (Module 2): Kdb+/q for big data and machine learning by Paul Bilokon: 1 hour 45 minutes

• q-sql – Slides
• Big Data in kdb+/q – Slides
• Parallelisation – Slides
• Joins – Slides
• kdb+/q for big data and machine learning – Forum

QDC Lecture 9 (Module 2): Kdb+/q in practice by Paul Bilokon: 2 hours

• Big Data in kdb+/q – Slides
• kdb+tick – Slides
• kdb+/q in practice – Forum

Module 2 Test

Module 3: C++ fundamentals with use cases from finance: 6 hours

PERFORMANCE, PRODUCTION STABILITY, AND PORTABILITY

QDC Lecture 10 (Module 3): C++ introduction by Ivan Zhdankin: 1 hour 30 minutes

• QDC Tutorial 1 Curve Interpolation – Slides
• QDC lecture 1 Intro – Slides
• Sample Code – Lecture1
• Sample Code – Tutorial1
• coderpad(3)
• coderpad (1)
• C++ introduction – Forum

QDC Lecture 11 (Module 3): Introduction to OOP in C++ by Ivan Zhdankin: 1 hour 40 minutes

• Lecture Intro OOP – Slides
• Tutorial Algo IR risk hedging – Slides
• Sample Code – Lecture2
• Sample Code – Tutorial2
• Introduction to OOP in C++ – Forum

QDC Lecture 12 (Module 3): Defining your own structures in C++ by Ivan Zhdankin: 1 hour 30 minutes

• QDC Tutorial 3 – Slides
• QDC lecture 3 – Slides
• Sample Code – Lecture3
• Sample Code – Tutorial 3
• Defining your own structures in C++ – Forum

QDC Lecture 13 (Module 3): Introduction to Standard Library by Ivan Zhdankin: 1 hour 20 minutes

• QDC Tutorial 4 – Slides
• QDC lecture 4 – Slides
• Sample Code – Lecture4
• Sample Code – Tutorial 4
• Introduction to Standard Library – Forum

Module 3 Test

Module 4: Data structures and algorithms in C++: 5 hours

THE CORE OF COMPUTING

QDC Lecture 14 (Module 4): Git and GitHub by Ivan Zhdankin: 1 hour 20 minutes

• Git and GitHub – Webex Link
• Git and GitHub – Recording Link
• Data Structures and Algorithms – Slides
• What is Git? – Slides
• Git and GitHub – Forum

QDC Lecture 15 (Module 4): Analysis Tools, Recursion and Sorting by Ivan Zhdankin: 1 hour 5 minutes

• Analysis Tools, Recursion and Sorting – Recording Link
• Analysis tool, Recursion – Slides
• Interview Questions
• Pricing Vanilla instruments and Derivatives – Slides
• Analysis Tools, Recursion and Sorting – Forum

QDC Lecture 16 (Module 4): Arrays, Linked Lists, Stacks and Queues by Ivan Zhdankin: 1 hour 5 minutes

• Queues Sorting – Slides
• Code / Interview Questions
• Data Structures and Algorithms, Risk-Factor Simulation – Slides
• Arrays, Linked Lists, Stacks and Queues – Forum

QDC Lecture 17 (Module 4): Trees and Graphs by Ivan Zhdankin: 1 hour 25 minutes

• Data Structures and Algorithms in C++ – Maps and Hash Tables, Trees, Graph Algorithms – Slides
• Data Structures and Algorithms – Risk-Factor Simulation, Aggregation – Slides
• Trees and Graphs – Forum

Module 4 Test

Module 5: Designing algorithmic trading applications: 8 hours 45 minutes

STATE-OF-THE-ART CONTENT

QDC Lecture 18 (Module 5): The hardware of electronic trading by Paul Bilokon: 2 hours 5 minutes

• The hardware of electronic trading – Slides
• The hardware of electronic trading – Forum

QDC Lecture 19 (Module 5): The networking of electronic trading by Paul Bilokon: 1 hour 50 minutes

• The networking of electronic trading – Slides
• The networking of electronic trading – Forum

QDC Lecture 20 (Module 5): Low-latency programming by Paul Bilokon: 1 hour 45 minutes

• Low-latency programming – Slides
• Low-latency programming – Forum

QDC Lecture 21 (Module 5): Event-driven architecture by Paul Bilokon: 1 hour 30 minutes

• Event-driven architecture – Slides
• Event-driven architecture – Forum

QDC Lecture 22 (Module 5):The workflow of a trading platform by Paul Bilokon: 1 hour 30 minutes

• The workflow of a trading platform – Slides
• The workflow of a trading platform – Forum

Module 5 Test

Final Examination

Candidates will sit a formal examination on a computer. The exam is taken online by students globally.

Marking Classifications:

Students achieving an overall mark of 70% or higher will be awarded the Certificate with Distinction. The total mark is calculated as equally weighted marks for module tests and final exam.

• Distinction: 70-100%; US equivalent: A/A+
• Merit: 60-69%; US equivalent: B+/A
• Pass: 50-59%; US equivalent: B-/B

QUANTITATIVE Analyst Developer Strat: THE PROFESSION: 15+ hours

Course curriculum

This is the first of a kind course that teaches what the job of a quantitative analyst, developer or strat really is. There will be nearly no math in the course, but you will learn about the exact types of the quant jobs on the sell and buy-side, in consulting and in fintech, daily routines of different types of quants and their interaction among themselves and with other stakeholders, quant reports and other deliverables, quant library organization, the quant R&D process on the sell and buy-side and, finally, the skills that are really necessary beyond the technical ones and the career prospects.

There is also a special section providing a very high-level view on the quant modelling for pricing, risk and trading strategy design.

Sections on the organizational structure, quant job types and quant deliverables will be also useful for non-quants, including MBAs and CFA candidates.

Introduction

• Welcome
• The course outline
• Who is this course for?
• Evolution of the profession
• Pricing and signal vs Risk and Return
• The ultimate motivation
• Why becoming a quant?
• (Special topic) Probability vs Statistics vs ML
• (Special topic) Why everything needs to be priced?

Financial firms and quant roles

• Financial businesses and risks
• Sell-side organisation
• Sell-side quants
• Buy-side organisation and quants
• Financial Consulting
• Fintech and financial software vendors

Daily tasks and reports

• Daily operations of a trading desk or a POD
• Products, positions, books; ageing and position effects
• Evolution of the quant and IT responsibilities
• FO Reports: Position and PNL
• FO Reports: Scenarios and Risk
• FO Reports: PNL explain and PNL predict
• Regulatory reports and limits

Quant libraries and systems

• Quant library. Use cases and deployment
• Quant library organization
• The pricing function
• End user tools
• Case Study: Numerix

Required skills

• Introduction
• Required skills. Part 1
• Required Skills. Part 2

Grades. Progression and Pay.

• Grades. Progression and pay. Introduction
• Grades. Progression and pay

Final Examination: 

Examination Preparation Week: Thursday 2nd October 2025
Examination Date: Thursday 23rd October 2025

• Candidates will sit a formal examination on a computer. The exam is taken online by students globally.

Marking Classifications:

Students achieving an overall mark of 70% or higher will be awarded the Certificate with Distinction. The total mark is calculated as equally weighted marks for module tests and final exam.

• Distinction: 70-100%; US equivalent: A/A+
• Merit: 60-69%; US equivalent: B+/A
• Pass: 50-59%; US equivalent: B-/B