Executive Programme in Algorithmic Trading - EPAT®
Become a Certified Algo Trader with Hands-On Training
Eager to launch your trading desk or advance your career in Algorithmic, Quantitative, and Automated Trading? EPAT course offers a comprehensive curriculum with top-tier faculty, including Dr. Ernest P. Chan and Dr. Euan Sinclair. Learn Python-based algo trading with hands-on experience using real-market data, leading APIs, and brokers. Get personalised support and certification while specialising in trading strategies through live project mentorship, setting the stage for a successful career as an algo trader.
11th January, 2025
Next Batch
6 Months
Batch Duration
120+ Hours
Live Lectures
20+
World Class Faculty
300+
Hiring Partners
What are EPAT Benefits?
Expert Faculty
An acclaimed team of subject matter experts
Dedicated Support
A Support Manager for each EPATian
Career Services
Lifetime placement and career assistance
EPAT features
Project work opportunity
Scholarships and Financial Aid
Lifetime access to latest course content
Verified Certification
Exclusive EPAT Community benefits
Credit Points for continuous professional development
Success
Warning
120+
Hours Live Lectures
20+
World Class Faculty
300+
Placement Partners
90+
Participant Countries
300+ PLACEMENT PARTNERS
Faculty Members
Dr. Ernest P Chan
Ernest Chan (Ernie) is the founder and CEO of Predictnow.ai, a machine learning SaaS. He started his career as a machine learning researcher at IBM's T.J. Watson Research Center's Human Language Technologies group, which produced some of the best-known quant fund managers. He later joined Morgan Stanley's Data Mining and Artificial Intelligence group. He is the founder and non-executive chairman of QTS Capital Management, a quantitative CPO/CTA. He obtained his PhD in Physics from Cornell University and his B.Sc. in Physics from the University of Toronto.
Dr. Euan Sinclair
Dr Euan Sinclair holds a PhD in theoretical physics from the University of Bristol. Dr Euan has more than 2 decades of Options trading experience and has written three books, “Volatility Trading”, “Options Trading” and "Positional Options Trading", all published by Wiley, as well as numerous papers and articles.
Dr. Robert Kissell
Dr Robert Kissell is the President of the Kissell Research Group and has a rich professional experience of 25 years. Specializing in financial and quantitative analysis, statistical modelling, and risk management, Dr Kissell is the global leader and industry expert in the electronic and algorithmic trading space, a well-known speaker, renowned author, professor at multiple educational institutions, and an expert having published numerous financial research papers. Dr Kissell is an Adjunct Professor at Fordham University and an Assistant Professor at the Molloy College.
Brian Christopher
Brian is a Quantitative researcher, Python developer, CFA charter holder, and the founder of Blackarbs LLC, a quantitative research firm. He started coding using Python to create algo trading strategies and has self-published his research which focused on trading algorithm research and development. He attained a BSc in Economics from Northeastern University in Boston, MA and received the Chartered Financial Analyst (CFA) designation in 2016.
Dr. Thomas Starke
Dr Thomas Starke is the CEO of the financial consultancy firm AAAQuants. With a remarkable career spanning working with Boronia Capital, Vivienne Court Trading and Rolls-Royce, he has conducted workshops and presentations on algorithmic trading around the world. As an academic, he was a senior research fellow and lecturer at Oxford University. A tech aficionado, he takes a keen interest in new technologies such as AI, quantum computing and blockchain.
Dr. Yves J. Hilpisch
Dr Yves Hilpisch is an expert in Python & Mathematical Finance and covers topics related to Python coding & strategy backtesting. He also covers Object-Oriented Programming concepts in Python. Yves is the founder and the CEO of The Python Quants as well as The AI Machine. He is also an Adjunct Professor of Computational Finance at the University of Miami Business School, USA.
Dr. Hui Liu
Dr Liu is the author of IBridgePy and founder of Running River Investment LLC. His major trading interests are US equities and the Forex market. Running River Investment LLC is a private hedge fund specialising in the development of automated trading strategies using Python.
Dr. Gaurav Raizada
Gaurav is an experienced professional who leads the client business at iRage. He focuses on developing and optimizing trading systems, and transaction cost analysis. He is the Chief Investment Officer for iRage Master Trust Investment Managers LLP and a Designated Partner for iRage. His educational background includes a Doctor of Philosophy in Financial Econometrics from IIT Bombay, an MBA from IIM Lucknow, and a B.Tech from IIT Kanpur.
Rajib Ranjan Borah
Rajib focuses on business strategy, trading strategies, risk management & internal processes. He is a regular speaker at algorithmic trading conferences across Asia, America & Europe Prior experiences – quant research (Bloomberg, NY); high-frequency trading (Optiver, Amsterdam); data analytics technology (Oracle); business strategy for an investment firm & derivatives exchanges Represented India at the World Puzzle Championship 4 times. Top 24 finalists at the Indian National Biology Olympiad. Rajib is also a visiting faculty in finance at IIM Ahmedabad.
Anil Yadav
At iRage, Anil managed multiple trading strategies and then also designed firm-wide risk and compliance practices. Currently, he is building the infrastructure to evaluate alpha signals (both individually and in combinations). Before iRage, Anil worked as an independent commodities trader, managing a portfolio of metals and energy products and as a senior Analyst at TCG’s Private Equity fund and as a Convertible Analyst at Lehman Brothers.
Ashutosh Dave
Ashutosh Dave has more than a decade of experience in the area of financial derivatives trading and quant finance. His key areas of interest include applying advanced data science and machine learning techniques to financial data. Ashutosh worked as a derivatives trader specialising in trading interest rates and commodities with a proprietary trading firm in London for several years before joining QuantInsti.
Ishan Shah
Ishan leads Quantra's Research and Content team and has prior experience at Barclays and Bank of America Merrill Lynch. Ishan has a rich experience in financial markets spanning various asset classes in different roles. He has co-authored a book on Machine Learning for Trading.
Jay Parmar
Jay Parmar works as an Associate, Content & Research at QuantInsti and comes with several years of experience in the BFSI industry. He is actively engaged in content development for quant finance courses and mentors EPAT participants across the globe. His research interests are in applying machine learning models to various facets of trading.
Nitesh Khandelwal
Nitesh Khandelwal is presently the CEO of QuantInsti, an institute co-founded in 2010 as part of iRage, a leading algorithmic trading player in India. Before co-founding iRage, he had worked in bank treasury (FX & Interest rate domain) and on a proprietary trading desk.
Nitin Aggarwal
Nitin is the Founder and CEO of Alphom Advisory Pvt. Ltd. (a trading firm). His gamut of experience ranges from developing novel breakthrough chemical technologies to creating proprietary trading strategies. Before leading the Alphom Advisory, he led the Operations team in Pentagon Advisory, has been a quant at iRage and a Leadership Associate with the Aditya Birla Group.
Prodipta Ghosh
Prodipta leads the Fin-tech products and platforms development at QuantInsti. Before joining QuantInsti, Prodipta spent more than a decade in the banking industry – in various roles across trading and structuring desks for Deutsche Bank in Mumbai & London, and as a corporate banker with Standard Chartered Bank. Before that, Prodipta worked as a scientist in India’s Defence Research & Development Organization (DRDO).
Radha Krishna Pendyala
Radha works as a Data Scientist at Thomson Reuters. His work involves applying machine learning and quantitative financial modelling techniques to large datasets to solve specific problems in the financial sector. He obtained his Master’s in Financial Engineering from the City University of New York.
Varun Pothula
Varun Pothula possesses an extensive experience in the field of quantitative finance. With a Master's degree in Financial Engineering, he has excelled as a trader, global macro analyst, and algo trading strategist. Currently, Varun holds the position of Quantitative Analyst in the Content & Research Team at QuantInsti, where his valuable contributions aid in the development of comprehensive educational offerings tailored to the algorithmic and quantitative trading domain.
Dr. Ankur Sinha
Dr Ankur Sinha carries a rich professional experience being associated with the prestigious IIM Ahmedabad, India, as a faculty member and also heading various departments at IIM Ahmedabad. He has taught at Aalto University School of Business, Finland & Michigan State University, United States. He is a renowned expert in the domain of Big Data and Business Intelligence. He holds a PhD in Business Technology from Aalto University School of Business, Helsinki, Finland, and has done Mechanical Engineering at one of India's finest institutions, IIT Kanpur.
Vivek Krishnamoorthy
Vivek leads the Research & Content team for EPAT at QuantInsti. He teaches participants data analysis, building quant strategies and time series analysis using Python. He has over 15 years of experience across India, Singapore, and Canada in industry, academia, and research. He is the co-author of the books, “Python Basics: With illustrations from the financial markets (2019)” and “A rough-and-ready guide to algorithmic trading (2020)”.
Curriculum
Certificate
This programme has been accredited by The Institute of Banking and Finance (IBF, Singapore) under the IBF Standards. IBF-STS provides upto 50% funding for direct training costs subject to a cap of S$ 3,000 per candidate per programme subject to all eligibility criteria being met. This is applicable to Singapore Citizens or Singapore Permanent Residents, physically based in Singapore. Find out more on www.ibf.org.sg
EPAT is accredited by CPD, UK (Continuing Professional Development, UK)
QuantInsti has registered this program with GARP for Continuing Professional Development (CPD) credits. Attending this program qualifies for 30 GARP CPD credit hours. If you are a Certified Financial Risk Manager (FRM®), or Energy Risk Professional (ERP®), please record this activity in your Credit Tracker.
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STUDENT TESTIMONIALS
We have a 4.8 rating out of 300+ Google reviews
Jad Mawlawi
United Kingdom
EPAT has been a great experience for me. It is definitely the best programme out there to learn quantitative finance and algorithmic trading. The… See More
EPAT has been a great experience for me. It is definitely the best programme out there to learn quantitative finance and algorithmic trading. The team was and still is very helpful and caring. The course itself is a combination of different disciplines including programming, finance, and statistics taught by very knowledgeable and experienced faculty.
Billy Davila
United States
I recently completed the EPAT programme from QuantInsti, and it was a rich experience. I learned more here than I did on my university curriculum… See More
I recently completed the EPAT programme from QuantInsti, and it was a rich experience. I learned more here than I did on my university curriculum. This is mainly since the EPAT course is very practical and I was able to learn a lot in such a short time. It provided me with a lot of theoretical and practical knowledge in the algorithmic trading domain. Besides their excellent curriculum, the support team is friendly, dedicated, and always there to support you during your EPAT journey. They also have a placement team that keeps you updated with career opportunities. However, keep in mind that your background will influence how well you fit into those career opportunities. They also have a self-paced learning portal named Quantra which I really enjoy. Overall, they are excellent at what they do.
Marcus Coleman
United States
QuantInsti is the best place to learn professional algorithmic and quantitative trading. The EPAT programme is a highly structured and hands-on l… See More
QuantInsti is the best place to learn professional algorithmic and quantitative trading. The EPAT programme is a highly structured and hands-on learning experience and it's being updated frequently. The faculty and staff are extremely competent and available to address any concerns you may have. Upon completion of the EPAT programme you will have the necessary tools to begin a career in algorithmic/quantitative trading.
Jim Ike
Singapore
From basic knowledge of quantitative finance to practical hands-on python session of back testing trading strategies, EPAT course covers a large … See More
From basic knowledge of quantitative finance to practical hands-on python session of back testing trading strategies, EPAT course covers a large portion of knowledge needed to join algorithmic trading industry. Good introduction to dive in.
Ronnie Varghese
United Arab Emirates
The Executive Programme in Algorithmic Trading (EPAT) is a well structured, intensive course which takes approx. 6 months to complete. The core f… See More
The Executive Programme in Algorithmic Trading (EPAT) is a well structured, intensive course which takes approx. 6 months to complete. The core focus areas of the course are stock market theories and quantitative principles, statistical analysis and programming. With the current trend of businesses moving towards implementing Artificial Intelligence (AI) or data-centric approaches to solving difficult problems, the skills gained from this course can be used to solve any AI-related problem (i.e. these skills can be used for any domain other than algorithmic trading). Having these skills in your repertoire will likely increase the probability of finding employment. Further, the Institute actively works towards the placement of the students enrolled (or alumni) in the course. The faculty are experts in their respective fields. In order to successfully complete this course, the student must be committed to completing the assignments and projects to cement their understanding of the course material. An added advantage is that there is lifetime access to the course materials, which will enable any alumni of the EPAT course to stay updated on the developments in this field. Overall, in my opinion, EPAT provides value for your money.
Avi Nandwani
United States
I found the EPAT course to be exactly what I was looking for – the right mix of statistics, financial markets and coding. The faculties were exce… See More
I found the EPAT course to be exactly what I was looking for – the right mix of statistics, financial markets and coding. The faculties were excellent, and most importantly, the support team was exceptional with their efforts towards my learning.
Rajeev Chahar
India
Your one-stop solution for the niche and opaque domain of Algorithmic Trading. Be it faculty, student support service, training content & resourc… See More
Your one-stop solution for the niche and opaque domain of Algorithmic Trading. Be it faculty, student support service, training content & resources or communication, they match the standards of international repute!
Raymond Philips
South Africa
I had a great experience through QuantInsti Learning. If you are passionate about Algorithmic/Quantitative Trading, or you want to start your jou… See More
I had a great experience through QuantInsti Learning. If you are passionate about Algorithmic/Quantitative Trading, or you want to start your journey in this amazing discipline, this is a great place to begin and grow your knowledge and interest. The administration and faculty were outstanding. Lectures are well-delivered and informative and there is always additional help should you require it. There is a wide array of learning material both through coursework and through the community as a whole.
Eriz Zárate
Spain
Only great words to say about QuantInsti and my learning path during the EPAT programme. Always curious, always listening and improving. All the … See More
Only great words to say about QuantInsti and my learning path during the EPAT programme. Always curious, always listening and improving. All the staff, starting from the CEO down to the support people were very nice 120% of the time (the 20% excess goes to all the help that they have given me after concluding the course, every time with a consistent will to help others).
Regarding the EPAT programme content, the key thing I would like to say is that is a wide covering approach. During six months, industry experts (i.e. real practitioners, not Gurus) dive into a variety of topics from scratch, so that, after that, you can choose in which field are you going to focus.
My final thoughts for new EPATians are: it is a must-do course if you are beginning in the field of algorithmic trading and quantitative finance. Although the real value is in the people that drive the institution. Be sure that you will have to take more courses after EPAT to succeed in this field, but you won't find the life-long learning support that they will give you anywhere else.
Nicolò Pirozzi
Italy
The course is very organized, both theoretical and practical, the staff is very competent and helpful, I found myself at ease during the whole co… See More
The course is very organized, both theoretical and practical, the staff is very competent and helpful, I found myself at ease during the whole course of study, I learned the basics to start a career in algorithmic trading and finance in general. What I appreciated the most were the lessons held with prominent personalities from the world of finance and trading, who shared their knowledge and experiences with the students. I would definitely recommend the course to anyone wishing to pursue a career in trading and finance.
Krishna Tunga
United States
I took the EPAT course already being familiar with algorithmic trading. I liked the content related to statistical arbitrage, order book mechanic… See More
I took the EPAT course already being familiar with algorithmic trading. I liked the content related to statistical arbitrage, order book mechanics and dispersion trading. The faculty and staff were very responsive and helpful. The lifelong continuing education part is also awesome as it keeps you current with what's happening in the field. Highly recommended for beginners interested to learn more about algorithmic trading.
Brian Chai
Singapore
I completed the EPAT course from QuantInsti and it was one of the best decisions I made to further my skills as a trader. The modules are care… See More
I completed the EPAT course from QuantInsti and it was one of the best decisions I made to further my skills as a trader. The modules are carefully chosen to provide you with a wide variety of skills needed for algorithmic and quantitative trading. Aside from the lecture materials, they also provide additional reading material and relevant references for you to dive deeper as well. The course is taught by practitioners who run funds and are authors of books that are some of the best in this space. The lectures are live and u get to interact with the faculty members too. The faculty members, mentors and support managers are always there to help me out with any queries that I have. Personally, I struggled a lot initially with coding as I did not come from a programming background but by the end of the course, I was able to deploy machine learning techniques in my strategies. I believe they have even added extra Python materials in the newer batches too. Overall if you are looking for a comprehensive course for algorithmic or quantitative trading then I would recommend EPAT by QuantInsti.
Prachiti Asolkar
India
It's a one-of-a-kind programme. The course extensively covers most areas required to begin a career as a quantitative trader. Their team is very … See More
It's a one-of-a-kind programme. The course extensively covers most areas required to begin a career as a quantitative trader. Their team is very helpful and professional, right from signing up for the program to placements. A dedicated account manager was assigned who encouraged the timely completion of courses/assignments (very important for any online course). The placement team is very proactive and helps out all the way till interview prep/test/assignments in the job search process.
Jad Mawlawi
United Kingdom
EPAT has been a great experience for me. It is definitely the best programme out there to learn quantitative finance and algorithmic trading. The team was and still is very helpful and caring. The course itself is a combination of different disciplines including programming, finance, and statistics taught by very knowledgeable and experienced faculty.
Billy Davila
United States
I recently completed the EPAT programme from QuantInsti, and it was a rich experience. I learned more here than I did on my university curriculum. This is mainly since the EPAT course is very practical and I was able to learn a lot in such a short time. It provided me with a lot of theoretical and practical knowledge in the algorithmic trading domain. Besides their excellent curriculum, the support team is friendly, dedicated, and always there to support you during your EPAT journey. They also have a placement team that keeps you updated with career opportunities. However, keep in mind that your background will influence how well you fit into those career opportunities. They also have a self-paced learning portal named Quantra which I really enjoy. Overall, they are excellent at what they do.
Marcus Coleman
United States
QuantInsti is the best place to learn professional algorithmic and quantitative trading. The EPAT programme is a highly structured and hands-on learning experience and it's being updated frequently. The faculty and staff are extremely competent and available to address any concerns you may have. Upon completion of the EPAT programme you will have the necessary tools to begin a career in algorithmic/quantitative trading.
Jim Ike
Singapore
From basic knowledge of quantitative finance to practical hands-on python session of back testing trading strategies, EPAT course covers a large portion of knowledge needed to join algorithmic trading industry. Good introduction to dive in.
Ronnie Varghese
United Arab Emirates
The Executive Programme in Algorithmic Trading (EPAT) is a well structured, intensive course which takes approx. 6 months to complete. The core focus areas of the course are stock market theories and quantitative principles, statistical analysis and programming. With the current trend of businesses moving towards implementing Artificial Intelligence (AI) or data-centric approaches to solving difficult problems, the skills gained from this course can be used to solve any AI-related problem (i.e. these skills can be used for any domain other than algorithmic trading). Having these skills in your repertoire will likely increase the probability of finding employment. Further, the Institute actively works towards the placement of the students enrolled (or alumni) in the course. The faculty are experts in their respective fields. In order to successfully complete this course, the student must be committed to completing the assignments and projects to cement their understanding of the course material. An added advantage is that there is lifetime access to the course materials, which will enable any alumni of the EPAT course to stay updated on the developments in this field. Overall, in my opinion, EPAT provides value for your money.
Avi Nandwani
United States
I found the EPAT course to be exactly what I was looking for – the right mix of statistics, financial markets and coding. The faculties were excellent, and most importantly, the support team was exceptional with their efforts towards my learning.
Rajeev Chahar
India
Your one-stop solution for the niche and opaque domain of Algorithmic Trading. Be it faculty, student support service, training content & resources or communication, they match the standards of international repute!
Raymond Philips
South Africa
I had a great experience through QuantInsti Learning. If you are passionate about Algorithmic/Quantitative Trading, or you want to start your journey in this amazing discipline, this is a great place to begin and grow your knowledge and interest. The administration and faculty were outstanding. Lectures are well-delivered and informative and there is always additional help should you require it. There is a wide array of learning material both through coursework and through the community as a whole.
Eriz Zárate
Spain
Only great words to say about QuantInsti and my learning path during the EPAT programme. Always curious, always listening and improving. All the staff, starting from the CEO down to the support people were very nice 120% of the time (the 20% excess goes to all the help that they have given me after concluding the course, every time with a consistent will to help others).
Regarding the EPAT programme content, the key thing I would like to say is that is a wide covering approach. During six months, industry experts (i.e. real practitioners, not Gurus) dive into a variety of topics from scratch, so that, after that, you can choose in which field are you going to focus.
My final thoughts for new EPATians are: it is a must-do course if you are beginning in the field of algorithmic trading and quantitative finance. Although the real value is in the people that drive the institution. Be sure that you will have to take more courses after EPAT to succeed in this field, but you won't find the life-long learning support that they will give you anywhere else.
Nicolò Pirozzi
Italy
The course is very organized, both theoretical and practical, the staff is very competent and helpful, I found myself at ease during the whole course of study, I learned the basics to start a career in algorithmic trading and finance in general. What I appreciated the most were the lessons held with prominent personalities from the world of finance and trading, who shared their knowledge and experiences with the students. I would definitely recommend the course to anyone wishing to pursue a career in trading and finance.
Krishna Tunga
United States
I took the EPAT course already being familiar with algorithmic trading. I liked the content related to statistical arbitrage, order book mechanics and dispersion trading. The faculty and staff were very responsive and helpful. The lifelong continuing education part is also awesome as it keeps you current with what's happening in the field. Highly recommended for beginners interested to learn more about algorithmic trading.
Brian Chai
Singapore
I completed the EPAT course from QuantInsti and it was one of the best decisions I made to further my skills as a trader. The modules are carefully chosen to provide you with a wide variety of skills needed for algorithmic and quantitative trading. Aside from the lecture materials, they also provide additional reading material and relevant references for you to dive deeper as well. The course is taught by practitioners who run funds and are authors of books that are some of the best in this space. The lectures are live and u get to interact with the faculty members too. The faculty members, mentors and support managers are always there to help me out with any queries that I have. Personally, I struggled a lot initially with coding as I did not come from a programming background but by the end of the course, I was able to deploy machine learning techniques in my strategies. I believe they have even added extra Python materials in the newer batches too. Overall if you are looking for a comprehensive course for algorithmic or quantitative trading then I would recommend EPAT by QuantInsti.
Prachiti Asolkar
India
It's a one-of-a-kind programme. The course extensively covers most areas required to begin a career as a quantitative trader. Their team is very helpful and professional, right from signing up for the program to placements. A dedicated account manager was assigned who encouraged the timely completion of courses/assignments (very important for any online course). The placement team is very proactive and helps out all the way till interview prep/test/assignments in the job search process.
ADMISSION PROCESS
Send your
Application
Get on a call
with a Counsellor
Application
acceptance
Pay the fee
and get started
Send your
Application
Get on a call
with a Counsellor
Application
acceptance
Pay the fee
and get started
Before admission, we will facilitate a one-on-one counselling session that will focus on understanding the strengths and weaknesses of the participant. These sessions do not necessarily decide the participants' eligibility but help counsellors assist them with informed guidance prior to enrollment.
Fees
Entire course fee starting at $ 9499
Scholarship and Financial Aid available for the deserving candidates
Schedule
We have four batches in a year. Duration of the programme is 6 months. The tentative programme start dates are:
Batch | Start Date |
---|---|
65 | 11th January, 2025 |
66 | 12th April, 2025 |
Programme Fee
Tier | Applicable till | Global Participants | Indian Residents* |
---|---|---|---|
Super Early Bird Enrollment Fees | 30th Oct 2024 | 7799 | 3,19,000 |
Early Enrollment Fees | 6th Dec 2024 | 7999 | 3,22,000 |
Standard Enrollment Fees | 4th Jan 2025 | 9499 | 3,79,000 |
Tier | Super Early Bird Enrollment Fees | Early Enrollment Fees | Standard Enrollment Fees |
Applicable till | 30th Oct 2024 | 6th Dec 2024 | 4th Jan 2025 |
Global Participants | 7799 | 7999 | 9499 |
Indian Residents* | 3,19,000 | 3,22,000 | 3,79,000 |
Tier | Applicable till | Global Participants | Indian Residents* |
---|---|---|---|
Super Early Bird Enrollment Fees | 31st Jan 2025 | 7,799 | 3,19,000 |
Early Enrollment Fees | 8th Mar 2025 | 8,599 | 3,49,000 |
Standard Enrollment Fees | 5th Apr 2025 | 9,499 | 3,79,000 |
Tier | Super Early Bird Enrollment Fees | Early Enrollment Fees | Standard Enrollment Fees |
Applicable till | 31st Jan 2025 | 8th Mar 2025 | 5th Apr 2025 |
Global Participants | 7,799 | 8,599 | 9,499 |
Indian Residents* | 3,19,000 | 3,49,000 | 3,79,000 |