Real Time Machine Learning
4 weeks US$ 400
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Real Time Machine Learning

Stream processing enables companies in every industry to drive intelligence and action in real-time by processing data as it comes in from sources such as IoT devices, customer interactions and order transactions, social media, etc. Use cases for stream processing can broadly be categorized into four areas: streaming analytics, monitoring, leaderboard, and real-time predictions. This course will cover stream processing paradigm, and streaming processing system architecture. Each week, students will build stream processing applications using widely adopted stream processing technologies, such as Apache Kafka, Apache Spark and Apache Flink.

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Hien Luu
Head of Machine Learning Platform @ Doordash
Price
US$ 400
Course Duration
4 weeks
Start Date
August 15
Registration By
August 12
Lecture
Monday @ 3:30 PM UTC
Project Sessions
Wednesday @ 4:00 PM UTC or
Thursday @ 12:00 AM UTC
Learn alongside a small group of your professional peers
Connect with experts through live sessions and office hours
Real-world projects that teach you industry skills.
Created and taught by
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Hien Luu

Head of Machine Learning Platform @ Doordash

Hien Luu is Head of Machine Learning Platform at DoorDash, author of Beginning Apache, and has been teaching at UCSC Extension School for more than 10 years. Previously, Hien was an Engineering Manager at LinkedIn where he helped build big data applications and infrastructure. And before that, Hien was at Uber, where he led the engineering team responsible for building a streaming processing platform to extract actionable business insights.

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The course

Stream processing enables companies in every industry to drive intelligence and action in real-time by processing data as it comes in from sources such as IoT devices, customer interactions and order transactions, social media, etc. Use cases for stream processing can broadly be categorized into four areas: streaming analytics, monitoring, leaderboard, and real-time predictions. This course will cover stream processing paradigm, and streaming processing system architecture. Each week, students will build stream processing applications using widely adopted stream processing technologies, such as Apache Kafka, Apache Spark and Apache Flink.

1
Week 1
Understand Stream Processing
Learn
  • Introduction to stream processing
  • Streaming processing application architecture
  • Stream processing techniques
  • Stream processing technology landscape
Project
Setting environment for streaming applications
    2
    Week 2
    Working with Apache Kafka
    Learn
    • Overview of Apache Kafka architectures
    • Understanding the Kafka programming model
    • Setting up and interacting with Apache Kafka
    Project
    Setting up a Kafka cluster and producing and consuming Kafka messages
      3
      Week 3
      Stream Process with with Apache Spark
      Learn
      • Apache Spark Structured Streaming Overview
      • Interacting with Apache Spark Structured Streaming
      • Implement streaming analytics and monitoring applications
      Project
      Spark streaming applications
        4
        Week 4
        Stream Processing with Apache Flink
        Learn
        • Apache Flink Overview
        • Work with Flink streaming processing APIs
        • Implement streaming leaderboard and monitoring applications
        Project
        Flink streaming applications
          Paul Marxhausen Senior Staff Software Engineer

          Hien is one of the best technical instructors that I have ever had. He is able to combine enthusiastic lectures with challenging homework projects, with a devotion to answer any and all questions asked of him with clear and precise responses. Most importantly he teaches a course that has real job market value. I would take further classes from Hien.

          Gaurav Aggarwal Founder, Stealth Startup (former Linkedin, Google, Microsoft)

          Hien is a brilliant, energetic, highly motivated, inspiring manager. He is among those hard to find people, who have technical expertise to tackle any problem in an optimal manner as well as manage people to deliver high impact results. He can easily step into the shoes of developer and solve the problems. His knowledgeable and perceptive insights has really helped me in my time at LinkedIn.

          James (Mitch) ZollingerDirector of Security Engineering & Streaming Architecture, Netflix

          Hien is a rare breed of engineer, taking pride and passion in his work, always willing to branch out in his knowledge and bring that knowledge to bear on something the world has never seen before.

          This course is for...

          Data Engineers who want to build stream processing applications

          Software Engineers who want to incorporate stream processing into their products to extract actionable insights

          Prerequisites

          Familiar with Java programming language

          Familiar with big data process, i.e SQL

          Familiar with Intellij IDEA community edition, Docker

          Able to install Java 11, maven, Docker Desktop

          Course experience

          Live Sessions with Experts

          Top industry leaders teach you everything you need in only 4 weeks

          Interactive Learning

          Real-world projects put your learning into immediate action

          Professional Communities

          Grow your network by learning with an intimate cohort of peers from top companies
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