Virtual Training Data Science, AI, and Advanced Analytics

Big Data Analytics with Apache Spark Online Course

Join our virtual, live instructor-led session and master Big Data Analytics with Apache Spark Training from anywhere in the world.

10 Days Duration
Live Online Delivery
7 Dates Available
Certificate Included
Master Big Data Analytics with Apache Spark to architect scalable data pipelines, optimize distributed workloads, and deploy real-time streaming solutions using industry-standard frameworks.

Upcoming Virtual Training Schedules

Join from anywhere in the world with our live instructor-led sessions

Code Start Date End Date Duration Fee
BDA-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Register my team →
BDA-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Register my team →
BDA-02 Weekend (8 Weeks) USD 1,700 Reserve my seat → Register my team →
BDA-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Register my team →
BDA-02 Weekend (8 Weeks) USD 1,700 Reserve my seat → Register my team →
BDA-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Register my team →
BDA-02 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Register my team →
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USD 1,700
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Training Date
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10 Days
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Training Date
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8 Weeks
USD 1,700
BDA-02
Training Date
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10 Days
USD 1,700
BDA-02
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Training Date
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10 Days
USD 1,700
BDA-02
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Here's What You'll Learn

Each module tackles real challenges you face in your role

1

Spark Foundations and Big Data Ecosystem

2

The Spark Programming Model

3

Spark SQL and Structured Data

4

Data Sources and Storage Formats

5

Advanced Spark Performance Tuning

6

Spark Structured Streaming Fundamentals

7

Integration with Apache Kafka

8

Machine Learning with Spark MLlib

9

GraphX and Graph Analytics

10

The Data Lakehouse with Delta Lake

11

Cloud Deployment and Cluster Management

12

Monitoring, Security, and Governance

13

Testing and CI/CD for Spark Jobs

Market-specific guidance for Serbia

A country-aware view of the pressures, proof points, and practical tools that shape how this course applies locally.

Why this course matters in Serbia

Strategic context for the risks, opportunities, and capability gaps this training addresses locally.

Apache Spark training is relevant in Serbia because organisations that are scaling analytics, ETL, and streaming workloads need engineers who can process larger datasets without relying on slower batch-first approaches. The course matters most for data engineering, analytics, and platform teams that are responsible for building reliable pipelines, reducing job failures, and improving time-to-insight. For leaders, the practical decision is whether to invest in distributed-data capability now so existing data platforms can support growth, cloud adoption, and faster operational reporting.

Distributed processing capability

Serbian teams that work with growing transaction, event, or sensor data need staff who can design Spark jobs that scale beyond traditional single-node or legacy batch tooling.

Streaming readiness

Structured Streaming and Kafka-style pipelines are useful where organisations need near-real-time monitoring, alerting, or customer-facing analytics instead of delayed overnight reporting.

Pipeline reliability

Training on Spark UI, execution-plan debugging, and optimisation helps teams reduce failed production jobs and control compute cost in data platforms that are under increasing load.

This training is timely because organisations in Serbia are increasingly expected to turn larger, faster data streams into usable decisions without adding avoidable infrastructure overhead. Teams that already run ETL, reporting, or cloud-data projects will feel the pressure most when pipeline latency, scalability, or operational resilience becomes a business constraint.

Tools and platforms relevant to this field

4

Field-relevant examples that may be featured in training where they support the confirmed scope. Exact coverage depends on participant needs and delivery format.

  • Apache Spark Apache Software Foundation
    Used for distributed processing, SQL analytics, streaming, and machine learning on large datasets.
  • Apache Kafka Apache Software Foundation
    Used to feed event-driven and streaming pipelines into Spark for near-real-time analytics.
  • Delta Lake Databricks
    Used to add reliable table management and transactional storage patterns to cloud data lake workflows.
  • Power BI Microsoft
    Used to visualise analytics outputs produced from Spark pipelines for business users and managers.

Where this course runs

Big Data Analytics with Apache Spark Training is delivered in the cities below — pick the one that fits your schedule.

Real Results from Real Professionals

Thousands of professionals have transformed their careers through our training programs. Now, it's your turn.

Customize Training Duration

The standard duration for Big Data Analytics with Apache Spark Training is 10 Days. The options below are alternative durations with adjusted pricing.

Looking for the standard 10 Days schedule? Use the button below.

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Barbours
Bank of Rwanda
RFA
Dahabshil Bank
Dorcas Aid
Finn Church Aid
KCB Foundation
Ministry of Education Saudi Arabia
NSSF Uganda
RBA
Reserve Bank of Malawi
WASREB Kenya
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