As the amount of data produced continues to increase and businesses become reliant upon it to make decisions, the need for data-driven jobs, and skilled workers to fill them is growing exponentially. As the physical and digital worlds in business continue to become more intertwined, the need for skilled data analysts and data scientists will span across all industries. As employers try to fill the void for these roles, a shortage of qualified workers will become the reality. Many employees may be forced to dive head-first into these positions to learn new data concepts. This will increase the demand for quality, distance learning programs such as the one offered by Duke Continuing Studies.
Duke Continuing Studies offers a 12 months intensive Big Data and Data Science online program combining both self-paced learning and live virtual classroom instruction. The program delivers over 300 hours of content designed by leading industry experts.
The Need for a Specialized Program in Big Data Analytics
Consumers have become more demanding in this day and age where their needs can be purchased with a few clicks of the mouse. Customers have more options now than ever, and businesses are being forced to get creative with their marketing strategies and customer service in order to acquire and keep the business they already have. Data collection and analysis plays a large part in how this is achieved. Consumer data aside, companies are using it to make more advanced, intelligent products, increase the speed of their workflows, and automate processes. In general, the need for skilled, data analysts is increasing.
Distinct Features of the Program
The Big Data and Data Science program is comprised of four mandatory courses and several non-required electives. Electives are available to students during the program to supplement the learning experience, as well as optional pre-courses which provide a brief review of programming language.
Through the mandatory courses, students will gain the following:
• Knowledge of Big Data management of large datasets and processing capabilities.
• A strong foundation for analytical and statistical concepts used in Python to become more familiar with programming.
• Data visualization techniques with Tableau, one of the most popular Business Intelligence tools in the market.
• Advanced-level training on Machine Learning applications and algorithms. Additionally, hands-on experience in multiple, highly sought-after machine learning skills in both supervised and unsupervised learning will be provided.
Last, students have the opportunity to gain insight into various other topics and platforms:
• Data Science with R
• Big Data Hadoop Administrator Course
• Python Basics
• Apache Cassandra
• Apache Kafka
• Apache Spark and Scala
• MongoDB Developer and Administrator
• Business Analytics with Excel
Program Mode and Industry Participation
The course is intended to provide students with the freedom to choose their preferred delivery format. The university offers self-paced video instruction, as well as live classes, powered by WebEx virtual classrooms. Students can take advantage of both for an optimal learning experience, tailored to their own preferences and schedules within the year allotted for access.
The curriculum is designed by industry leaders such as Ronald van Loon and Alvaro Fuentes and delivered in collaboration with the university’s online learning partner, Simplilearn.
Prerequisites for Aspiring Students
Students enrolling in this program are expected to have at least one year of basic programming experience in order to fully grasp the curriculum. Additionally, students need the motivation and discipline to complete the self-paced program and a reliable learning environment that can accommodate online connectivity and the computer hardware to access the appropriate software for projects and hands-on learning activities.
Target Audience for the Program
The Big Data and Data Science program is designed for professionals who wish to develop a broad and in-depth expertise in the spectrum of Big Data and Data Science related technologies and gain multiple data-related skills that are essential in the field of analytics. Some of the professionals who can directly benefit are individuals aspiring to become business/data analysts, project managers, mainframe professionals, data warehouse professionals, software developers, testers, or architects.