Market data
Download and clean ten years of stock prices in Python and compute returns and correlations.
All pathsDiscover Coursera PlusAfter step 1 After step 2 After step 3
Economics & finance · 53Intermediate
Finance Data Scientist
Developers or data scientists moving into finance.
Python, portfolio construction and machine learning for asset management, then supervised and reinforcement learning in finance.
225hours of coursework
23weeks at 10 h
3steps
13courses
3universities
Target skills
Data VisualizationWeb ScrapingPredictive ModelingFinancial MarketMachine Learning MethodsMachine LearningApplied Machine LearningData ProcessingRestful APIXMLDatabase DesignJSON
Skill labels as listed on Coursera.
Target jobs
- Finance data scientist
- Banking machine learning engineer
- Quantitative analyst
Progression
- 1University of MichiganBeginnerPython, SQL, SQLite
Stated prerequisites: No prerequisites; designed as an on-ramp to programming
Show the 5 courses
Course Level Length Rating (reviews) Programming for Everybody (Getting Started with Python) Beginner 17 h 4.8 (233,775) Python Data Structures Beginner 20 h 4.9 (97,365) Using Python to Access Web Data Beginner 19 h 4.8 (44,591) Using Databases with Python Beginner 14 h 4.8 (21,659) Capstone: Retrieving, Processing, and Visualizing Data with Python Beginner 9 h 4.7 (14,483) - 2EDHEC Business SchoolBeginnerPython
Stated prerequisites: No prior experience required
Show the 4 courses
Course Level Length Rating (reviews) Introduction to Portfolio Construction and Analysis with Python — 25 h 4.8 (1,477) Advanced Portfolio Construction and Analysis with Python Intermediate 12 h 4.7 (514) Python and Machine Learning for Asset Management Intermediate 16 h 3.1 (333) Python and Machine-Learning for Asset Management with Alternative Data Sets Intermediate 21 h 4.4 (238) - 3New York UniversityIntermediatePython, TensorFlow
Stated prerequisites: Basic math, probability and statistics, Python
Show the 4 courses
Course Level Length Rating (reviews) Guided Tour of Machine Learning in Finance Intermediate 24 h 3.8 (684) Fundamentals of Machine Learning in Finance Intermediate 18 h 3.7 (345) Reinforcement Learning in Finance Advanced 17 h 3.6 (134) Overview of Advanced Methods of Reinforcement Learning in Finance Advanced 13 h 3.8 (86)
With Coursera Plus
This path takes 225 hours, about 5 months at 10 hours a week. A Coursera Plus subscription gives access to most of its courses during that time.
Projects to build
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Build a sentiment indicator from news headlines and test its link with returns.
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Train a reinforcement learning agent on a simulated market and compare it with a simple strategy.
Free textbooks
Python for EverybodyCharles R. SeveranceFree, CC BY 4.0
An Introduction to Statistical Learning (Python)G. James, D. Witten, T. Hastie, R. Tibshirani, J. TaylorFree PDF
Foundations of Reinforcement Learning with Applications in FinanceA. Rao, T. JelvisFree PDF