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Architect & Scale End-to-End Streaming Pipelines in the Cloud

12 Weeks. Live Online Classes. Instructor-led.

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Our Partners

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Operate lake-and-warehouse architectures that stay cost-efficient and observable

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Design exactly-once pipelines with Kafka, Flink & Spark Structured Streaming

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Serve online features and analytics at sub-second latency—no batch reloads

What you will learn?

Deliver insights in under five seconds. This course takes you from change-data-capture with Debezium and Kafka to stateful stream processing in Apache Flink and Spark Structured Streaming. You’ll land data in a Delta Lakehouse, serve online features for ML, and wrap the entire pipeline with Prometheus observability and Great Expectations data contracts. Perfect for engineers facing IoT, click-stream, or telemetry workloads who need exactly-once guarantees at cloud scale.

    • Use Debezium to mirror operational DB changes to Kafka with exactly-once semantics

    • Master Kafka partitions, compaction, schema registry & consumer-group design

    • Build high-throughput joins & CEP patterns in Apache Flink and Spark Structured Streaming

    • Tune checkpoints, state back-ends, and watermarking for sub-second SLAs

    • Land streams in Parquet/Delta; automate schema evolution with Auto Loader

    • Create Bronze–Silver–Gold tables and enable time-travel querying for reprocessing

    • Feed aggregated features into Feast / Redis for real-time ML inference

    • Expose low-latency REST & gRPC services; benchmark p95 latency & QPS

    • Instrument pipelines with OpenTelemetry → Prometheus + Grafana dashboards

    • Enforce data contracts & tests with Great Expectations; integrate alerting to Slack

    • Right-size clusters and use auto-scaling to cut cost by up to 40 %

    • Team project: telemetry or click-stream pipeline → real-time dashboard & ML feature feed

    • Deliver architecture diagram, Terraform IaC, and ROI deck to a hiring-manager panel

Who Should Enrol?

  • Modernise batch ETL jobs into real-time, exactly-once pipelines.

  • Integrating Kafka / Flink into micro-services

    Embed event-driven data flows and lakehouse zones into micro-service architectures.

  • Feed models with fresh features and support online prediction services

  • Operate high-throughput Kafka/Flink clusters with robust monitoring and auto-scaling.

  • Break into one of the fastest-growing data specialties with a portfolio-ready streaming project.

Professionals who need to stream, process, and serve data in real time—not overnight.

Prerequisites
Solid Python & SQL, basic cloud familiarity. Free Data Infra 101 & Docker-K8s Mini-Camp bridge badges are provided for all Intermediate-track graduates.

Career Pathways

  • Design and maintain high-throughput CDC & streaming pipelines.

  • Build and scale Kafka/Flink/Spark clusters with CI/CD and IaC.

  • Deliver sub-second dashboards and metrics built directly on event streams.

  • Own online/offline feature parity and latency budgets for production models.

  • Define lakehouse tiers, storage formats and cluster topologies for enterprise-wide streaming workloads.

Graduates leave with a production streaming pipeline, GitHub repo, and recruiter-ready stories—aligned with the majority of “Kafka/Flink/Spark Streaming” roles advertised today.

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Amir Charkhi
Technology leader | Adjunct Professor | Founder

With 20 + years across energy, mining, finance, and government, Amir turns real-world data problems into production AI. He specialises in MLOps, cloud data engineering, and Python, and now shares that know-how as founder of AI Tech Institute and adjunct professor at UWA, where he designs hands-on courses in machine learning and LLMs.

Advanced: Real-Time Data Platforms

12 Weeks. Live Online Classes.

Advanced: Real-Time Data Platforms Advanced: Real-Time Data Platforms
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Advanced: Real-Time Data Platforms
$4,250.00

Deliver insights in under five seconds. This course takes you from change-data-capture with Debezium and Kafka to stateful stream processing in Apache Flink and Spark Structured Streaming. You’ll land data in a Delta Lakehouse, serve online features for ML, and wrap the entire pipeline with Prometheus observability and Great Expectations data contracts. Perfect for engineers facing IoT, click-stream, or telemetry workloads who need exactly-once guarantees at cloud scale.

Student Outcomes

  • "I recently completed a course at AI Tech Institute and was thoroughly impressed. The curriculum was thoughtfully structured, the instructor was truly dedicated, and the overall learning experience delivered exceptional value."

    Maria

  • "Taking the Machine Learning course at AI Tech Institute was a game changer. It gave me the skills and confidence to break into AI and helped me land a job soon after. The content was practical and beginner friendly, with clear lessons and hands-on projects that made a real difference during interviews."

    Pani

  • "Very valuable course. Amir is a great instructor, explained how machine learning used in the real world in a easy way. Highly recommend for people who want to know more about AI or work in this area."

    Hoàng Phước

  • "The AI and Data science bootcamp was one of the most impactful learning experiences I’ve had. The curriculum was well structured. The instructor was knowledgeable and supportive, and the course provided a strong balance between theory and hands on labs. Highly recommended!"

    Ehsan

  • "I took a course at AI Tech Institute, and it genuinely exceeded my expectations. The content was not only clear and well-structured, but also incredibly relevant to the challenges I deal with day-to-day at work."

    Rosha

  • "Extremely happy with clear, well designed and applicable syllabus to be implemented in day-to-day need of nowadays coding ability. Coming from non-IT background, it is a valuable experience of seamlessly and effortless the teaching was, for me to understand the complex subjects. Would definitely recommend to colleagues and friends!"

    Kresna

  • "Absolutely fantastic experience with AI Tech Institute! I couldn’t be happier with the quality of education and support I received here. The instructors are true experts — knowledgeable, approachable, and always willing to help students succeed. The curriculum is up-to-date with the latest advancements in AI and tech, blending theory with plenty of hands-on projects that really build practical skills."

    Foad

  • "Amir is both technically proficient, and a very good teacher. He was attentive to where each person in the group was and paced the information flow accordingly. I also found him very approachable, encouraging and supportive."

    Francois

Frequently Asked Questions

  • Beginner courses: none— we start with Python basics.
    Intermediate & Advanced: ability to write simple Python scripts and use Git is expected.

  • Plan on 8–10 hours: 2× 3-hour live sessions and 2–4 hours of project work. Advanced tracks may require up to 10 hours for capstone milestones.

  • All sessions are recorded and posted within 12 hours. You’ll still have access to Slack/Discord to ask instructors questions.

  • New intakes launch roughly every 8 weeks. Each course page shows the exact start date and the “Apply-by” deadline.

  • Just a laptop with Chrome/Firefox and a stable internet connection. All coding happens in cloud JupyterLab or VS Code Dev Containers—no local installs.

  • Yes. 100 % refund until the end of Week 2—no questions asked. After that, pro-rata refunds apply if you need to withdraw for documented reasons.

  • Absolutely. We issue invoices to companies and offer interest-free 3- or 6-month payment plans.

  • Live Q&A in every session, 24-hour Slack response time from instructors, weekly office-hours, and code reviews on your GitHub pull requests.