Systematic trading

QuantInsti and the EPAT programme: what an algorithmic trading course covers, and how to evaluate one

Systematic trading · Published 2026-10-24

People who want to move into algorithmic trading often look for a structured course. QuantInsti, an education company based in India, is one of the better-known providers, through its Executive Programme in Algorithmic Trading (EPAT) and its self-paced Quantra courses. This article describes what the company says it offers, based on its own published information, and then sets out a checklist for evaluating any trading course. Out of Sample has no relationship with QuantInsti or any other course provider.

What QuantInsti is

QuantInsti describes itself as an algorithmic and quantitative trading research and training firm. It was founded in 2010 and is headquartered in Mumbai. Its activities, as presented on its website, fall into a few strands:

• EPAT, a part-time programme delivered online over several months, aimed at working professionals and students who want a broad grounding in algorithmic trading.
• Quantra, a platform of shorter, self-paced courses on specific topics, such as particular strategy types, machine learning for trading or options.
• Blueshift, a platform for research, backtesting and trading strategies.
• Free content, including a blog, webinars and educational material.

What EPAT covers

According to QuantInsti's programme page, the EPAT curriculum spans statistics and econometrics, financial computing with Python, derivatives and options, quantitative trading strategies, machine learning for trading, market microstructure, execution, and risk and portfolio management, together with a final project. The programme is taught through live online lectures by practitioners and academics, with recorded sessions, assignments and access to support. Successful participants receive a certificate. The exact syllabus, duration and fees are set out on the provider's site and change between cohorts.

Programmes of this kind are not university degrees. Their value depends on the quality of teaching, the effort of the participant and how the content is applied. Employers in quantitative finance generally weight demonstrable skills, such as programming, statistics, and well-documented research projects, more heavily than any single certificate.

How to evaluate an algorithmic trading course

Whatever provider you consider, the following questions help separate useful education from marketing.

Curriculum

• Does it teach the foundations, probability, statistics, programming and market structure, rather than only strategies?
• Does it cover backtesting pitfalls, such as look-ahead bias, survivorship bias, overfitting and transaction costs, in depth?
• Is the material up to date with current tools and market regulations?

Teaching and practice

• Who teaches, and can you verify their professional or academic background independently?
• How much hands-on coding is there, with feedback on your work?
• Does the course end with a project you can show to others, with your own code and data?

Claims

• Be wary of any course that promises trading profits, specific returns or guaranteed jobs. No course can guarantee either.
• Testimonials and placement statistics are selected by the provider. Ask how they are defined and whether they are audited.
• Check whether the provider sells trading signals, brokerage or software alongside education, which creates incentives.

Cost and alternatives

• Set the fee against the free and low-cost alternatives: university open courseware, textbooks, documentation of open-source libraries, and the resources listed on our resources page.
• Consider formal degrees, such as master's programmes in financial engineering or data science, if the goal is a career change into a large institution.
• Ask about refund policies and whether you can view sample lectures before paying.

Learning without a course

Many practitioners learned on their own. A self-directed path might combine an introductory statistics and Python course, a textbook such as Ernest Chan's Quantitative Trading for the practical side, Marcos López de Prado's work for the methodological side (see our map of Advances in Financial Machine Learning), and a public research project documented in the way we describe in running a research project in the open. Courses can add structure, deadlines and feedback; they are not the only route.

Regulation and certificates

Course certificates are distinct from regulatory qualifications. Working at a regulated firm may require passing specific exams, such as FINRA examinations in the United States, depending on the role. A trading course does not replace them.

Questions to ask before enrolling in any programme

• Can I see the full syllabus and a sample lecture?
• How many hours per week does the programme realistically require, and over how long?
• What prior knowledge is assumed in mathematics, statistics and programming?
• What exactly is assessed, and how is the final project evaluated?
• What support is available after the course ends, and for how long?
• What is the total cost including any platform or data fees, and what is the refund policy?
• How does the provider define any career outcomes it publishes?

Answers to these questions, in writing, are a better basis for a decision than marketing material or testimonials. It is also worth speaking to people who completed the programme, found independently rather than through the provider, and asking what they would do differently. Finally, decide in advance what you want from the course, whether a structured introduction, a credential for a career change, or a specific skill, and judge any programme against that goal rather than against its promotional claims.

Why this page exists

Readers searching for a specific provider usually want two things: a neutral description of what is offered, and a way to decide whether it suits them. We give the first only from the provider's own published information, with links so it can be checked, and we spend most of the page on the second, because the same questions apply to every course on the market, whoever runs it and wherever it is based.