Table of contents : 1. Introducing Data Science and Trading Understanding Data Understanding Data Science Introduction to Financial Markets and Trading Applications of Data Science in Finance Summary 2. Essential Probabilistic Methods for Deep Learning A Primer on Probability Introduction to Probabilistic Concepts Sampling and Hypothesis Testing A Primer on Information Theory Summary 3. Descriptive Statistics and Data Analysis Measures of Central Tendency Measures of Variability Measures of Shape Visualizing Data Correlation The Concept of Stationarity Regression Analysis and Statistical Inference Summary 4. Linear Algebra and Calculus for Deep Learning [Heading to Come] Vectors and Matrices Introduction to Linear Equations Systems of Equations Trigonometry Limits and Continuity Derivatives Integrals and the Fundamental Theorem of Calculus Optimization Summary 5. Introducing Technical Analysis Charting Analysis Indicator Analysis Moving Averages The Relative Strength Index Pattern Recognition Common Pitfalls of Technical Analysis Wanting to Get Rich Quickly Forcing the Patterns Hindsight Bias, the Dream Smasher Assuming That Past Events Have the Same Future Outcome Making Things More Complicated Than They Need to Be Summary 6. Introductory Python for Data Science Downloading Python Basic Operations and Syntax Control Flow Libraries and Functions Exceptions Handling and Errors Data Structures in Numpy and Pandas Importing Financial Time Series in Python Summary About the Author