Learn Big Data Analytics with Apache Spark
![Big_Data_Analytics_WBG.png](https://images.squarespace-cdn.com/content/v1/60b6fd136dae8570d704e0d7/1624874336545-OL85MINVI4HHGUJ4XTP3/Big_Data_Analytics_WBG.png?format=500w)
Build and maintain applications with faster startup, better parallelism, and better CPU utilization.
Gain an in-depth and comprehensive understanding of big data analytics and AI project from project initiation to project completion.
Best suited for system developers who want to perform operations on a large volume of data in clusters quickly and with fault tolerance.
Duration:
2 days
Master the new ‘King’ that powers big data analytics and machine learning.
Apache Spark helps increase system development productivity leveraging parallel processing of distributed data with iterative algorithms.
![unsplash-image-NqOInJ-ttqM.jpg](https://images.squarespace-cdn.com/content/v1/60b6fd136dae8570d704e0d7/1625225211427-KPSU45QJ8Y2DOAGIRU71/unsplash-image-NqOInJ-ttqM.jpg?format=750w)
Lightning-fast analysis at scale.
Apache Spark is a lightning-fast unified analytics engine for big data and machine learning. It has quickly become the largest open source community in big data, with over 1000 contributors from 250+ organizations. Many data scientists, analysts, and general business intelligence users rely on interactive SQL queries for exploring data.
![unsplash-image-zt0HWquGXlQ.jpg](https://images.squarespace-cdn.com/content/v1/60b6fd136dae8570d704e0d7/1625225313209-59O0VKPHKV3FUFS84CT1/unsplash-image-zt0HWquGXlQ.jpg?format=750w)
Real-time analytics made possible.
Not only Spark can be seamlessly combined to create complex workflows, but it also provides in-memory computing capabilities to deliver speed, a generalized execution model to support a wide variety of applications, for ease of development.
![](https://images.squarespace-cdn.com/content/v1/60b6fd136dae8570d704e0d7/1625225456907-X87FBCJHV47ITZ9AIPC4/unsplash-image-s4dfrh7hdDU.jpg?format=500w)
Build faster, robust, scalable systems.
Best suited for analysts, data scientists, and business professionals who manage huge database architecture with a robust and versatile framework. For system architects and developers needing to analyze large volumes of data faster, in a more scalable way and with cheaper implementation and maintenance costs, you must not miss this course.
Learning Outcome
Upon completion, participants should be able to demonstrate each of the following;
- Understand and familiar with Big Data and Apache Spark ecosystem.
- Familiar with DataFrames and Spark SQL.
- Ability to Build machine learning models and data streaming processing.
Learning Path
![](https://images.squarespace-cdn.com/content/v1/60b6fd136dae8570d704e0d7/1625124748676-M1OQOZL1U5RTFMG5MFHC/EDS_300x150.png?format=750w)
Big Data Analytics with Apache Spark is one of the modules under the CADS Enterprise Data Scientist (EDS) Programme. EDS is a 23-26 days training program that supercharges Business Data Scientists with new skills to analyze and communicate insights effectively.
CADS Certification
![](https://images.squarespace-cdn.com/content/v1/60b6fd136dae8570d704e0d7/1624874687554-4V7D7OVS6S8DGL7WM8GD/EDS-Certification.png?format=750w)
Each exam in this program certifies job-ready knowledge and skill. Those that pass all are recognized as being able to distil insight from data and communicate its value to a decision-maker. Enter the world of Data Professionals.