In India, algo-trading is expected to cross 25% mark of the total equity cash market trade volume by 2020.
Quants in India get up to 4-5 openings on an average to apply in a week, which varies from domestic trading companies to large MNCs
Udacity ranked as the most disruptive learning company in the world for 2 years in a row by CNBC
Join a global community of quant traders and get a worldwide view of trading startegies with Worldquant
What You Learn
Learn the basics of quantitative analysis, and work on real-world projects from trading strategies to portfolio optimization.
classroom opening date
Learn how to analyze alternative data and use machine learning to generate trading signals. Run a backtest to evaluate and combine top performing signals.
Jonathan has previously held leadership roles such as Global Head of Equities at Millennium Management and Co-Head of Americas Equity Derivatives Trading at JPMorgan.
Cindy is a quantitative analyst with experience working for financial institutions such as Bank of America Merrill Lynch, Morgan Stanley, and Ping An Securities. She has an MS in Computational Finance from Carnegie Mellon University.
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
Elizabeth received her PhD in Applied Physics from Stanford University, where she used optical and analytical techniques to study activity patterns of large ensembles of neurons. She formerly taught data science at The Data Incubator.
Eddy has worked at BlackRock, Thomson Reuters, and Morgan Stanley, and has an MS in Financial Engineering from HEC Lausanne. Eddy taught data analytics at UC Berkeley and contributed to Udacity’s Self-Driving Car program.
Brok has a background of over five years of software engineering experience from companies like Optimal Blue. Brok has built Udacity projects for the Self Driving Car, Deep Learning, and AI Nanodegree programs.
Parnian is a self-taught AI programmer and researcher. Previously, she interned at OpenAI on multi-agent Reinforcement Learning and organized the first OpenAI hackathon. She also runs a ShannonLabs fellowship to support the next generation of independent researchers.
Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Cezanne is an expert in computer vision with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she’s applied computer vision and deep learning to medical diagnostic applications.
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
Absolutely. I learned practical knowledge, techniques, and skills in searching alpha as well as risk factors. Project 7 and project 8 are my favorites. Good work Udacity.
Some of it was confusing regarding what the quiz and test questions were asking for and subject to interpretation; a source of frustration. However, overall, it is one of the best put together and well designed courses out there.
Excellent! A bit Hard!
Very well structured and wonderful lectures! The course offers unique hands-on experiences which allow people to apply the skills in real world problems! Highly recommended to anyone who want to be quant traders!
Before taking this Nanodegree, I had no background in finance. I've actually learnt a lot. It's worth the money.
Nanodegree certification recognized and valued by top companies in India
Access to a hiring partner network of over 100 companies & Udacity Propel - our flagship career fairLearn more
A small incentive for you to come back and continue your learning with another Nanodegree program
Algorithmic trading share in total turnover grows to 50% in 8 years from merely 9.26% (average) in 2010
Quantative analysts earn upto INR 20 lakhs at India's top quant trading firms in India
It is expected that India would eventually be at par with the developed economies with 80 per cent of the total stock market turnover expected to be through HFT by 2020.
FREQUENTLY ASKED QUESTIONS
Graduates of this program will have the quantitative skills needed to be extremely valuable across many functions, and in many roles at hedge funds, investment banks, and FinTech startups.
Specific roles include:
The Artificial Intelligence for Trading Nanodegree program is designed for students with intermediate experience programming with Python and familiarity with statistics, linear algebra and calculus. In order to successfully complete this program, you should meet the following prerequisites:
Calculus and linear algebra
The Artificial Intelligence for Trading Nanodegree program is composed of two (2) three (3)-month terms. Each term has fixed start and end dates.
Students must complete both terms and all projects to graduate from the Nanodegree program. Each project will be reviewed by the Udacity reviewer network. Feedback will be provided, and if you do not pass the project, you will be asked to resubmit the project until it passes.
The full program consists of 2 (two) 3 (three)-month long terms at a cost of INR 49900 per term, for a total program cost of INR 99800.