Data Engineering Master Program

Data engineering is an important phase in the data science process where data is collected, prepared for analysis, transformed, and delivered to the data scientists, analysts, and other consumers. Data Engineering is a Master’s degree program offered by GoLogica, which aims at offering a broad understanding of data architecture and management and the relevant frameworks in the creation of a reliable large-scale data solution.

The Data Engineering Master’s Program is an extensive program intended for candidates interested in the profession of managing and designing the structures that underpin big data systems. Data engineers play a vital role in data-driven companies because they are charged with the responsibility of gathering, sorting, and arranging data together with the instruments for easy access to data scientists, analysts, and business communities for analysis and decision-making.

In this particular program, learners are trained in comprehending the concepts of data architecture, databases, Cloud applications, Big Data tools, as well as distributed systems. The audience will be empowered to understand the optimization of release pipelines to imbue data with the precise attributes that make it ready for analysis. Learners at the end of this course will effectively be able to use technologies such as SQL, and Python, Big Data tools such as Hadoop, and Spark, and Cloud services including AWS, Azure, and Google Cloud.

Consequently, the course incorporates theoretical concepts, as well as practical implementations to allow the participants to handle the difficulties of dealing with large sets of data. The curriculum has been designed in such a way that it will give experience about the challenges commonly found in data engineering jobs, such as scalability, performance, integration, and security.

With topics like statistics, machine learning, data visualization, and programming, this program ensures that students are well-equipped to handle real-time data problems that they are likely to come across in their work. The program mainly focuses on Data engineering, along with the combination of the latest technologies like Apache Spark, Big Data Hadoop, MongoDB, and cloud services such as Microsoft Azure. Learners will be able to design, build, and maintain a fully functional data pipeline, and construct extensible data architectures to cater to the learners' growing range of data engineering skills.

Key Highlights

• Comprehensive Curriculum: The program covers topics such as data architecture, data modeling, ETL processes, Cloud data engineering, Big Data processing, and distributed systems.

• Capstone Project: Create a complete Data engineering solution, that will allow you to understand how to work with big data and apply it to practice when working with advanced big data sets.

• Expert Mentorship: Take lessons from industry experts who will teach you the insights to develop sound, scalable, and efficient metadata systems.

• Flexible Learning Options: The program also includes live and recorded classes depending on the scheduling convenience of the learner.

• Industry-Relevant Tools and Technologies: Get an opportunity to work on the most recent tools, such as Apache Hadoop, Apache Spark, Kafka, AWS Redshift, and others, for practical experience with big data tools and technologies.

Top Skills You Will Learn

• Data Pipeline Development.
• Big Data Technologies such as Apache Spark, Hadoop.
• Database Management Programs such as SQL, NoSQL, and MongoDB.
• Cloud Computing with Azure.
• Distributed Data Processing.
• Data modeling and ETL processes.
• Data Governance and Security.