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Modern Backend Systems are actually Distributed Systems in disguise. This course will combine theory, workshops, and projects to help you gain practical experience. You will also learn key concepts like CAP theorem, Event Driven Systems, Monitoring and Observability to building highly scalable, distributed backend services.
ex-Engineering Director
Victor was previously Employee #1 and one of the Engineering Directors at Carousell, focusing on scaling the organization to build a world-class engineering team to empower our users with Classifieds 4.0. Victor is a pragmatist at work, and believes in taking small actionable steps that will bring us closer to our goals.
Sr Software Engineer ( Team Lead )
Li Yi is an experienced and skilled Senior Software Engineer/Team Lead with extensive experience in designing, developing, and delivering core e-commerce/lending/delivery platform solutions. He is a product minded engineer who likes to ask "why?" behind all things and dedicated himself to solving problems that could make impact on users.
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Need to be proficient in at least 1 programming language that is able to write HTTP API services
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Know about In-memory Stores
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Have used Database (Relational / NoSQL) and Code Versioning in small projects
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Software engineers who want to learn and build distributed systems
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Frontend engineers with little or some backend experience looking to move to Backend
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Duration: week of 5/2 to week 6/6
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Schedule: Every Tuesday from 19:30-21:30 (GMT+8)
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Introduction to Distributed Systems and their properties
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Types of Distributed Systems (Peer-to-Peer, Client-Server, Hybrid)
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CAP Theorem and its implications
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Fallacies of Distributed Systems
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Overview of data replication and its importance
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CAP applied to Databases
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Consensus Protocols for leader election
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Backups and Mitigation Strategies
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Importance of Monitoring and Observability in Distributed Systems
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Metrics to monitor in Distributed Systems (Latency, Throughput, Error Rates)
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Logging and Tracing in Distributed Systems
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Distributed tracing (e.g. Zipkin, Jaeger)
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Monitoring tools (e.g. Prometheus, Grafana)
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Queues and Distributed Message Queues
Data is the lifeblood of modern organisations, allowing them to succeed by making informed decisions quickly to react to a fast changing environment.
You will learn how to build high impact data analytics and engineering to enable your data team to deliver business impact and insights beyond just numbers and statistics.
ex-Sr Data Analyst
A data social scientist wants to make our world a better place by providing a lens through analytics, technologies and social science theories. Interests: philosophy, data, tech, cybersecurity, cities and art.
Co-founder / Practicum Director
Koo is experienced in the full process of getting value from data, from data collection, management & governance to implementation of insights through strategy and business performance measurement.
His research interest is in how an organization can build Data Science & Artificial Intelligence capabilities, Artificial General Intelligence, and Smart Cities with a focus on the standard of living.
( Guest Speaker )
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Need to be proficient in at least 1 programming language (Python, R, SQL for data analysis)
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Occasionally use Database and Dashboard tools for analytics purposes
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Know about Task Orchestration and Code versioning
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Experienced data professionals who want to scale the impact of their data team
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Senior technical leaders who want to gain a broad set of experience to better guide their data team
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Duration: week of 5/25 to week of 7/6
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Schedule: Every Thursday from 19:30-21:30 (GMT+8) （Due to national holiday, there will be no live course on 6/29）
Learn about different organizational structures for data teams, such as centralized, decentralized, or hybrid models, and the pros and cons of each for optimal collaboration.
Establish data governance policies to reduce risks and improve quality and consistency through understanding how to choose the right data storage and processing technologies and implement data security measures.
Learn to overcome resistance to data-driven decision-making, build trust in data, and incentivize data use and collaboration to create a culture that values data and encourages its use in decision-making.
Identify bottlenecks and inefficiencies in data workflows and provide strategies for streamlining processes to increase overall operational efficiency.
Gain knowledge on how to align data efforts with business goals and identify metrics to measure the impact of data-driven insights on business performance.
Becoming an effective engineering manager requires you to be good at managing both technologies and people. You will gain crucial knowledge about yourself, your team, and what it takes to be an effective manager.
Through role-playing with real-world situations and creating decision-making frameworks to enhance your communication and management techniques.
Director of Engineering
Site lead of Carousell's Taiwan Development Center.
Overseeing engineering teams building products such as Recommerce, Buyer Experience, Search and Seller Experience.
Mentors engineering leaders and has created an Engineering Manager Academy.
ex-Engineering Manager
Lead an engineering team within the Support Products team to use technology to improve the customer service experience and scale Airbnb's customer service support.
Help to grow Airbnb Seattle office from 5 people to 350+ people and create a vibrant office culture.
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Be open to sharing your experience and getting feedback
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Practice what you learn in your role and reflect upon your progress
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Current engineering managers
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Aspirational tech leads
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Duration: week of 4/24 to week 5/29
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Schedule: Every Monday from 19:30-21:30 (GMT+8) （Due to national holiday, the live course on 5/1 will be rescheduled to 5/4）
Discover what drives you through a deep dive into personal motivation for management roles.
Build your confidence and sharpen your communication skills by learning how to handle difficult conversations such as performance reviews, resignations, and pay raises.
Learn to make informed engineering decisions as a manager, balancing technical and managerial responsibilities
Great managers can come in many forms. Define what makes a successful engineering manager and develop the skills to become an effective leader.
Learn to engage and motivate your team through effective communication, 1-on-1 meetings, review meetings, and other team management techniques.