Big Data Developer certification by IBM

Department of Computing Science is pleased to be able to offer IBM professional training courses which are highly in demand. IBM in its ever-continuing effort to support the technical institutions has partnered with University of Stirling, RAK Campus, UAE to deliver full comprehensive training. The changed face of job market has made it necessary for young professionals to obtain professional training in their field of interest. In today's super competitive employment arena, professional qualifications can help our students to stand out from the competition and give them an edge when applying for the job.

Big Data Developer

Big data is being always generated by everything around us. Systems, social media, sensors, and mobile devices generate it. This course helps to extract meaningful value from big data using optimal processing power, analytics capabilities, and skills.

Career path description

The Big Data Engineer career path prepares students to use the Big Data platform and methodologies to collect and analyze large amounts of data from different sources. This will require skills in Big Data architecture, such as Apache Hadoop, Ambari, Spark, Big SQL, HDFS, YARN, MapReduce, ZooKeeper, Knox, Sqoop, and HBase.

Delivery method

95% instructor led and 5% web-based.


Undergraduate senior students from IT related academic programs i.e. computer science, software engineering, information systems and similar others

Learning objectives

After completing this course, you should be able to understand the following topics:

• Big Data and Data Analytics • Hortonworks Data Platform (HDP) • Apache Ambari • Hadoop and the Hadoop Distributed File System • MapReduce and Yarn • Apache Spark • Storing and Quering data • ZooKeeper, Slider, and Knox • Loading data with Sqooq • Dataplane Service • Stream Computing • Data Science essentials • Drew Conway’s Venn Diagram - and that of others • The Scientific Process applied to Data Science • The steps in running a Data Science project • Languages used for Data Science (Python, R, Scala, Julia, ...) • Survey of Data Science Notebooks • Markdown language with notebooks • Resources for Data Science, including GitHub • Jupyter Notebook • Essential packages: NumPy, SciPy, Pandas, Scikit-learn, NLTK, BeautifulSoup... • Data visualizations: matplotlib, ..., PixieDust • Using Jupyter “Magic” commands • Using Big SQL to access HDFS data • Creating Big SQL schemas and tables • Querying Big SQL tables • Managing the Big SQL Server • Configuring Big SQL security • Data federation with Big SQL • IBM Watson Studio • Analyzing data with Watson Studio

Prerequisites Skills:

• Basic knowledge of Linux • Basic SQL knowledge • Working knowledge with big data and Hadoop technologies • Have a basic understanding of notebook technologies for data science • Students can attend free courses at to acquire the necessary requirements • Exposure to the IBM Skills Academy Portal learning environment • Exposure to the IBM Skills Academy Cloud hands-on labs platform

Total Hours

60 hours

Students can start the training and earn the open badges from IBM and add to their catalog of experience. Badges provide digital recognition for skills attained. Students can combine their credentials to form a complete overview of your skills, display their accomplishment in their e-mail signature, display their qualifications on social and professional networking sites like linked in, Provide employers with easy, valid verification of their credentials.

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