Apache Flink tutorial curriculum

While an Apache Fink tutorial can be a focused way of learning, a standalone Apache Fink course may be difficult to find. However, instruction on stream processing with Apache Flink can be part of a larger “big data” or data engineering curriculum.

In these kinds of courses, learners may spend time on some of the following topics:

• Understanding challenges businesses face given the upsurge of data

• Using ETL (extract, transform, load) tools

• Managing data pipelines

• Processing large-scale data streams

• Querying data streams

• Creating machine learning models with streaming frameworks

It could be helpful to have a basic understanding of Python or Java programming before getting started with Apache Flink. Other skill areas that could make learning the stream processing service easier include, basic statistics, SQL, and business intelligence analytics.

Jobs that use Apache Flink

With Apache Flink processing skills in your wheelhouse, you could be qualified for a variety of different jobs, such as:

• Data scientist: Builds machine learning and automation systems to leverage data.^{Footnote 3}

• Software engineer: Develops back-end solutions to improve user experience.^{Footnote 4}

• Database administrator or data engineer: Migrates and converts cross-platform data.^{Footnote 5}

For learners interested in advancing their knowledge of the field, edX offers a variety of educational pathways, including specialized boot camps, full programs that enable you to earn a bachelor's degree or pursue a master’s degree. Find the right course for you.

How to conduct stream processing with Apache Flink

Today’s data scientists are handling real-time data from web activity, internet of things (IoT) devices, financial service transactions, and location-based tracking feeds. Stream processors like Apache Flink provide an open-source framework for creating stateful, fault-tolerant stream processing at scale, and providing immediate insights. 

Once you install Apache Flink, you can begin using Flink’s DataStream API to stream and filter data inputs. You will need to select a deployment mode: Local, Cluster, or Cloud. From there, learners could implement basic operations on streaming data, or start incorporating multiple stream sources.^{Footnote 6}

If you are interested in adding new skills to your resume, explore how online learning opportunities such as a data analytics boot camp or even a bachelor’s degree in data science can help you build the expertise and experience you need to pursue roles in this field.