Mark J. van der Laan is a Hsu/Peace Professor of Biostatistics and Statistics at the University of California, Berkeley. His research concerns causal inference, prediction, adjusting for missing and censored data, and estimation based on high-dimensional observational and experimental biomedical and genomic data. He is the recipient of the 2005 COPSS Presidents' and Snedecor Awards, as well as the 2004 Spiegelman Award, and is a Founding Editor for the International Journal of Biostatistics.

Sherri Rose is currently a PhD candidate in the Division of Biostatistics at the University of California, Berkeley. Her research interests include causal inference, prediction, and applications in rare diseases. Upon completion of her doctoral degree, she will begin an NSF Mathematical Sciences Postdoctoral Research Fellowship at Johns Hopkins Bloomberg School of Public Health.

Abbreviations and Notation.- Philosophy of Targeted Learning in Data Science.- Part I: Introductory Chapters.- 1. The Statistical Estimation Problem in Complex Longitudinal Big Data.- 2. Longitudinal Causal Models.- 3. Super Learner for Longitudinal Problems.- 4. Longitudinal Targeted Maximum Likelihood Estimation (LTMLE).- 5. Understanding LTMLE.- 6. Why LTMLE?.- Part II:Additional Core Topics.- 7. One-Step TMLE.- IV: Observational Longitudinal Data.- 19. Super Learning in the ICU.- 20. Stochastic Single-Time-Point Interventions.- 21. Stochastic Multiple-Time-Point Interventions on Monitoring and Treatment.- 22. Collaborative LTMLE.- Part V: Optimal Dynamic Regimes.- 23. Targeted Adaptive Designs Learning the Optimal Dynamic Treatment.- 24. Targeted Learning of the Optimal Dynamic Treatment.- 25. Optimal Dynamic Treatments under Resource Constraints.- Part VI: Computing.- 26. ltmle() for R.- 27. Scaled Super Learner for R.- 28. Scaling CTMLE for Julia.- Part VII: Special Topics.-29. Data-Adaptive Target Parameters.- 30. Double Robust Inference for LTMLE.- 31. Higher-Order TMLE.- Appendix.- A. Online Targeted Learning Theory.- B. Computerization of the calculation of efficient influence curve.- C. TMLE applied to Capture/Recapture.- D. TMLE for High Dimensional Linear Regression.- E. TMLE of Causal Effect Based on Observing a Single Time Series.