Training

How to Conduct Study Group Sessions

Frequency

you can conduct study group sessions every two weeks. This will give everyone enough time to read and prepare for the discussion.

Book Selection

it is recommended to select a book that is relevant to the current work, but not specific to any product or technology. This will allow everyone to relate to the content and gather insights that can be applied to their work.

Appointing a Coordinator

you can appoint a coordinator to facilitate study group sessions by rotation, set an agenda, take notes, and control time. This will ensure that the discussion stays on track, everyone gets a chance to speak, and important points are noted down.

Preparation & Commitment

all members are required to prepare and complete reading a certain amount of material beforehand. For instance, they should aim to read 50 pages of the book per session, with an average of 300 pages (one book) per quarter. The coordinator doesn’t need to present the content.

Ideal Study Group Size

the size of the group should be small and recommended to be less than 8. This will allow sufficient time for everyone to share their thoughts on reading and engage in a meaningful discussion.

Participating in Hackathon and OSS

members could take opportunities to share their experience on applying training to current projects through a hackathon or open-source community. This will help everyone to learn from each other and improve their skills.

Training Journey

Leadership Track

  1. Culture - Open: The Story Of Human Progress

  2. User Behavior - Element of Choice

  3. Roadmap - Rewired

  4. Alignment - Design Thinking Metrics

  5. Risk Management - How to Measure Anything

  6. Recognition - The Carrot Principle

  7. Leadership - Essential Deming

  8. Finance - Financial Intelligence

  9. Certificate Program - MIT Sloan: Business Process Design for Strategic Management

Business Track

  1. Innovation - The Design Thinking Playbook

  2. Business Model - Value Prepositions

  3. Operation - Operating Model Canvas

  4. Economics - Product Development Flow

  5. Lean - Value Stream Management

  6. Rules - Business Rules

  7. UX - Mapping Experience

  8. Requirement - User Story Mapping

  9. Certificate Program - International Institute of Business Analysis

Software Engineering Track

  1. Principles - Software Fundamentals

  2. Domain Modeling - Domain-Driven Design

  3. Event Modeling - Event Mining for Explanatory Modeling

  4. Functional Modeling - Domain Modeling Made Functional

  5. System Design - Righting Software

  6. Modularity - Java Application Architecture

  7. Construction - Code Complete

  8. Models & Methods - Formal Methods

  9. Security - ISO 27001:2022 ISMS Lead Implementer Training Course

  10. Checklist - The Missing README

  11. Certificate Program - Professional Software Engineering Master Certification

Data Science & Infrastructure Track

  1. Computing: Distributed Systems

  2. Data Model - Data Modeling Made Simple

  3. Database - Refactoring Database

  4. Data Warehouse - The Data Warehouse Toolkit

  5. Data Engineering - Designing Data-Intensive Applications

  6. Data Management - Data Management at Scale

  7. Machine Learning - Designing Machine Learning Systems

  8. Artificial Intelligence - Artificial Intelligence: A Modern Approach

  9. SaaS - Cloud Native Patterns

  10. IaaS - Design Patterns for Cloud Native Applications

  11. Operation - The DevOps Handbook

  12. Certificate Program - Data Management Body of Knowledge

References

  • [RUS10] S. J. Russell, P. Norvig, and E. Davis, Artificial Intelligence: A Modern Approach. Prentice Hall, 2010.

  • [LAM20] G. S. W. Lam, R. G. Ross, K. Seer, M. Norton, D. Lyalin, and W. Williams, Business Rules: Management and Execution. Future Strategies Inc., 2020.

  • [DAV19] C. Davis, Cloud Native Patterns: Designing change-tolerant software. Simon and Schuster, 2019.

  • [MCC04] S. Mcconnell, Code Complete, 2nd Edition. Wiley India Pvt. Limited, 2004.

  • [HOB09] S. Hoberman, Data Modeling Made Simple: A Practical Guide for Business and IT Professionals. Technics Publications, 2009.

  • [IND21] K. Indrasiri and S. Suhothayan, Design Patterns for Cloud Native Applications. O’Reilly Media, Inc., 2021.

  • [KLE17] M. Kleppmann, Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. O’Reilly Media, Inc., 2017.

  • [HUY22] C. Huyen, Designing Machine Learning Systems. O’Reilly Media, Inc., 2022.

  • [TAN17] A. S. Tanenbaum and M. van Steen, Distributed Systems. CreateSpace Independent Publishing Platform, 2017.

  • [WLA18] S. Wlaschin, Domain Modeling Made Functional: Tackle Software Complexity with Domain-Driven Design and F#. Pragmatic Bookshelf, 2018.

  • [JAL21] L. Jalali and R. Jain, Event Mining for Explanatory Modeling. Association for Computing Machinery, 2021.

  • [BER13] K. Berman and J. Knight, Financial Intelligence, Revised Edition: A Manager’s Guide to Knowing What the Numbers Really Mean. Harvard Business Press, 2013.

  • [NIE19] F. Nielson and H. R. Nielson, Formal Methods: An Appetizer. Springer International Publishing, 2019.

  • [HUB10] D. W. Hubbard, How to Measure Anything: Finding the Value of Intangibles in Business. John Wiley & Sons, 2010.

  • [KNO12] K. Knoernschild, Java Application Architecture: Modularity Patterns with Examples Using OSGi. Prentice Hall, 2012.

  • [KAL21] J. Kalbach, Mapping Experiences: A Complete Guide to Customer Alignment Through Journeys, Blueprints, and Diagrams. O’Reilly, 2021.

  • [NOR20] J. Norberg, Open: The Story Of Human Progress. Atlantic Books, 2020.

  • [CAM17] A. Campbell, M. Gutierrez, and M. Lancelott, Operating Model Canvas. Van Haren Publishing, 2017.

  • [AMB06] S. W. Ambler and P. J. Sadalage, Refactoring Databases: Evolutionary Database Design. Pearson Education, 2006.

  • [LAM23] E. Lamarre, K. Smaje, and R. Zemmel, Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI. John Wiley & Sons, 2023.

  • [LOW19] J. Löwy, Righting Software. Addison-Wesley Professional, 2019.

  • [PAR01] D. L. Parnas, Software Fundamentals: Collected Papers by David L. Parnas. Addison-Wesley, 2001.

  • [GOS12] A. Gostick and C. Elton, The Carrot Principle: How the Best Managers Use Recognition to Engage Their Employees, Retain Talent, and Drive Performance. Simon and Schuster, 2012.

  • [KIM13] R. Kimball and M. Ross, The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. John Wiley & Sons, 2013.

  • [LEW18] M. Lewrick, P. Link, and L. Leifer, The Design Thinking Playbook: Mindful Digital Transformation of Teams, Products, Services, Businesses and Ecosystems. John Wiley & Sons, 2018.

  • [KIM21] G. Kim, J. Humble, P. Debois, J. Willis, and N. Forsgren, The DevOps Handbook: How to Create World-Class Agility, Reliability, & Security in Technology Orions. IT Revolution, 2021.

  • [JOH21] E. J. Johnson, The Elements of Choice: Why the Way We Decide Matters. Riverhead Books, 2021.

  • [DEM12] W. E. Deming, The Essential Deming: Leadership Principles from the Father of Quality. McGraw Hill Professional, 2012.

  • [RIC21] C. Riccomini and D. Ryaboy, The Missing README: A Guide for the New Software Engineer. No Starch Press, 2021.

  • [REI09] D. G. Reinertsen, The Principles of Product Development Flow: Second Generation Lean Product Development. Celeritas, 2009.

  • [PAT14] J. Patton and P. Economy, User Story Mapping: Discover the Whole Story, Build the Right Product. O’Reilly Media, Inc., 2014.

  • [OST15] A. Osterwalder, Y. Pigneur, G. Bernarda, and A. Smith, Value Proposition Design: How to Create Products and Services Customers Want. John Wiley & Sons, 2015.

  • [TAP02] D. Tapping, T. Luyster, and T. Shuker, Value Stream Management: Eight Steps to Planning, Mapping, and Sustaining Lean Improvements. Taylor & Francis, 2002.

  • [EVA03] E. Evans, Domain-Driven Design: Tackling Complexity in the Heart of Software. Addison-Wesley, 2003.