Offered by Fitch Ratings, Inc.
A part‑time, live‑online Certificate in Quantitative Finance delivered by Fitch Learning for professionals seeking practical mastery in financial engineering, Python implementation and machine‑learning techniques to advance in quant, risk and trading roles.
Fitch Ratings, Inc.
Delivered online and awarded by the CQF Institute (part of Fitch Learning), the Certificate in Quantitative Finance (CQF) is a six‑month, master’s‑level professional programme that combines quantitative finance theory with hands‑on implementation. The syllabus is updated regularly and covers stochastic calculus, risk and return, equities, fixed income, data science and machine learning, with two specialist electives to align learning to career goals.
Designed for working professionals, the CQF uses live interactive lectures, optional primers and practical Python labs so delegates can apply techniques directly to real‑world problems. Assessment includes examined modules and a practical capstone project; successful delegates receive the Certificate in Quantitative Finance and CQF alumni status with lifelong access to a 900+ hour Lifelong Learning library and career services.
Key highlights and core differentiators that set this program apart.
Awarded by the CQF Institute (Fitch Learning) — globally recognised professional designation
Live interactive online delivery with practitioner‑led faculty
Flexible part‑time format with optional primers and ability to defer up to three years
Permanent access to a 900+ hour Lifelong Learning library and CQF Careers Service
Specialist electives allowing targeted specialisation (two electives of choice)
Core capabilities, strategic skills, and managerial frameworks you will acquire.
Essential delivery mode, timeline, and candidate eligibility at a glance.
Comprehensive breakdown of course modules, masterclasses, and hands-on projects.
If a delegate’s math, finance, or programming knowledge is a little rusty, the optional online primers are just what they need to refresh their knowledge and get up to speed before the CQF program starts.
- Mathematics Primer: Get to grips with all the math preliminaries needed for the program, including calculus, differential equations, probability, statistics, linear algebra, and more.
- Python Primer: Ideal for professionals who are new to coding in Python, this primer will teach them to code from scratch by covering Python syntax, mathematical applications of Python, good programming practices, and more.
- Finance Primer: Understand the key concepts and different asset classes needed for the program, including macroeconomics, time value of money, derivatives, swaps, equities, bonds, FX, and more.
Random behavior of assets
Important mathematical tools and results
Taylor series
Partial differential equations
Transition density functions
Fokker-Planck and Kolmogorov
Stochastic calculus and Itô’s Lemma
Manipulating stochastic differential equations
Martingales
The binomial model for asset prices
Modern portfolio theory
Capital asset pricing model
Portfolio optimization for portfolio selection
Risk regulation and Basel III
Value at risk and expected shortfall
Collateral and margins
Liquidity asset liability management
Volatility filtering (GARCH Family)
- Asset returns: key, empirical stylized facts
- Volatility models: The ARCH Framework
The Black-Scholes Model
Hedging and the Greeks
Options strategies
Early exercise and American options
Finite-difference and methods
Monte Carlo simulations
Exotic options
Volatility arbitrage strategies
Martingale theory for pricing
Girsanov’s theorem
Advanced Greeks
Derivatives market practice
Advanced volatility modeling in complete markets
Non-probabilistic volatility models
FX Options
What is mathematical modeling?
Math toolbox for machine learning
Principal component analysis
Supervised learning techniques
Linear regression
- Penalized regressions: lasso, ridge, and elastic net
Logistic, SoftMax regression
K-nearest neighbors
Naïve Bayes classifier
Support vector machines
Decision tress
Ensemble models: bagging and boosting
Python: scikit learn
Unsupervised learning techniques
K-means clustering
Self-organizing maps
T-distributed Stochastic Neighbor Embedding
Uniform manifold approximation and projection
Autoencoders
Artificial neural networks
Neural network architectures
Natural language processing
Deep learning and NLP tools
Reinforcement learning
Practical machine learning case studies for finance
AI-based algo trading strategies
Quantum computing in finance
Python: TensorFlow
Fixed-income products and market practices
Yield, duration, and convexity
Stochastic interest rate models
Probabilistic methods for interest rates
Calibration and data analysis
Heath, Jarrow, and Morton
Libor market model
Structural models
Reduced-form model and the hazard rate
Credit risk and credit derivatives
X-valuation adjustment (CVA, DVA, FVA, MVA)
CDS pricing, market approach
Risk of default, structural and reduced form
Implementation of copula models
The CQF program offers you the opportunity to specialize further with two advanced electives, allowing you to develop your skills with your specific career objectives in mind. Our advanced electives include
Advanced Machine Learning I
Advanced Machine Learning II
Advanced Portfolio Management
Advanced Risk Management
Advanced Volatility Modeling
Algorithmic Trading I
Algorithmic Trading II
Generative AI Agents in Finance & Beyond, Generative AI and Large Language Models, and Modeling with C++
Behavioural Finance for Quants
Counterparty Credit Risk Modeling
Numerical Methods
R for Data Science and Machine Learning
- Risk Budgeting: Risk-Based Approaches to Asset Allocation
Advanced Ensemble Modeling
Decentralized Finance Technologies
Energy Trading
FX Trading and Hedging
Quantum Computing in Finance
Format, class schedules, campus immersion details, and evaluation criteria.
Twice a week · Two live online lectures every week; lectures recorded and available on demand within 24 hours
Eligibility criteria, work experience requirements, and admission steps.
Graduates gain official alumni recognition and lifetime networking privileges.
Key application deadlines, batch commencement dates, and intake schedules.
| Application Deadline | 1 November 2026 |
|---|---|
| Program start date | 27 January 2027 |
Delegates may defer their studies for up to three years at no extra cost; the program is delivered part‑time over six months but start and deferral options are available.
Tuition fees, flexible installment schedules, and available financing options.
Taxes: GST/taxes are applicable (source indicates Taxes: true). Fees are listed on the awarding institute site: the CQF fees are published at www.cqf.com/fees; TimesPro advises contacting them for payment plans and support in India. The page lists 'Course Fee: Contact Us' for TimesPro; specific instalment schedule is not published on this page.
Common queries about the program, admissions, curriculum, and policies.
The Certificate in Quantitative Finance (CQF) program is a globally recognized, online, master’s-level professional qualification in quant finance and machine learning. The program teaches both the theory and the practical implementation of the latest techniques used in industry. It is designed for working professionals looking to master the cutting-edge skillset needed to advance in the field.
The CQF is studied online and part-time over six months. You can also defer their studies for up to three years at no extra cost if needed.
Before the program starts, you can refresh your skills and get up to speed with optional, online primers in math, finance and Python programming. The CQF qualification then includes six core modules, followed by two advanced electives of your choosing. The core program covers topics such as stochastic calculus, equities and currencies, data science and machine learning, risk and return, and fixed income and credit. Modules two, three, and four are examined, and at the end of the program you will complete a practical final project that ensures you can apply your skills to a scenario you are likely to come across at work.
The fees for the CQF program can be found at www.cqf.com/fees. Contact TimesPro today to find out more about payment plans and financial support for the program in India.
The CQF is awarded by the CQF Institute, part of Fitch Learning. The CQF Institute is the global membership organization in quant finance dedicated to building and educating the quant community worldwide. As part of the CQF community, you will have access to regular, free, online conferences, industry talks, careers events, and local society meetings.
A background in mathematics, finance, or programming is recommended. Optional primes in Python programming, mathematics, and finance are available once you are enrolled to help you refresh your skills before the program starts.
Yes, the CQF is a great tool for professionals looking to transition into a quant finance career. The program will help you build practical knowledge needed for roles in the field and is recognized by top tier finance firms globally.
The core CQF modules cover topics such as stochastic calculus, equities and currencies, data science and machine learning, risk and return, and fixed income and credit. After the core modules, you can specialize towards your career goals by choosing two advanced electives from a range of options including, Algorithmic Trading, Advanced Machine Learning, Advanced Volatility Modeling, FX Trading and Hedging, Decentralized Finance Technologies, Generative AI Agents in Finance & Beyond, Generative AI and Large Language Models, and many more.
Yes, CQF alumni have permanent access to the ever-expanding Lifelong Learning library. This unique resource includes over 900 hours of additional lectures, masterclasses, and the latest CQF qualification content. This means that even if you enroll on the program today, you will be able to keep upskilling with new lectures and electives added to the program long after you graduate.
CQF lectures are delivered live online twice a week. All lectures are recorded and available to watch on demand within 24 hours on the CQF portal. Throughout the program, you can also enhance your studies with additional support in the form of tutorials, Python labs, workshops, and more.
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About the primary institute
Fitch Ratings, Inc. is a leading global credit rating agency with over a century of history in financial markets. Dual‑headquartered in New York and London, Fitch provides credit opinions, research and commentary across sovereigns, corporates, financial institutions, structured finance and public finance sectors. The agency is part of the Fitch Group and, together with Moody's and S&P Global Ratings, is considered one of the 'Big Three' credit rating agencies.
Renowned for its analytical rigor and global footprint, Fitch employs thousands of professionals, including a large team of credit analysts and sector specialists. It services investors, issuers and regulators worldwide with credit ratings, data and research products. Fitch's operations also encompass related businesses within Fitch Group that provide market data, analytics and training services.