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Data Analytics and Engineering

Master of Science

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Overview

In the Master of Science in Business Analytics program at CSP Global, you will gain essential knowledge to excel in data analytics, data engineering, and data architecture. Get equipped with a comprehensive set of skills to work effectively with qualitative and quantitative datasets, helping you understand how to build robust data solutions.

Program
Details

Program Length

30 Credits

Location

Online

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  • Career-Centered Program: Gain essential technical, analytical, and communication skills in the master’s in data analytics online program.
  • Designed for Busy Professionals: Complete your M.S. Data Analytics and Engineering degree fully online and in as few as 12 months while you continue to enhance your career skills in machine learning, computing frameworks, and data security.
  • Data Expertise: Work effectively with qualitative and quantitative datasets, extracting valuable insights, communicating complex findings, and building data-driven solutions and strategies.
  • Grow as a Leader: Develop strong problem-solving skills, apply analytical thinking to address data-related challenges, and effectively collaborate in interdisciplinary teams.
$ 600

Cost per credit – CSP Global’s technology programs are valuable and affordable.

Jumpstart Your Future

Admissions Requirements

Career Paths

Statistician $ 98,920

2022 Median Income

Data Scientist $ 103,500

2022 Median Income

Systems Manager $ 164,070

2022 Median Income

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TUITION & FINANCIAL AID

  • Most affordable private university in MN
  • $600 per credit hour
  • Flexible payment options
  • $2,000 partnership scholarships available
  • Transfer up to 15 credit hours

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ADMISSIONS REQUIREMENTS

  • Complete a free application
  • Submit official transcripts
  • Completed degree in computing, engineering, mathematics, statistics, operations research, information technology, or a related field. OR completed degree with 2 years of relevant work experience in data analytics.

Full Requirements

Courses

  • This course provides a comprehensive exploration of Enterprise Architecture (EA), focusing on strategic planning and technical research. It equips students with the skills to design, implement, and manage architectures that align an organization’s business strategy, processes, information systems, and technology infrastructure to achieve success.

  • The CSP Project Management, Systems Development & Risk course offers an integrated study of project management principles, systems development methodologies, and risk management practices within the context of complex global IT projects. This course is designed for students and professionals seeking a comprehensive understanding of how to effectively manage projects, develop robust IT systems, lead diverse multi-disciplined teams and proactively address project risks for successful project delivery.

  • The CSP Database Systems course offers a comprehensive study of the principles, design methodologies, and practical applications of database management systems to support the enterprise of the future (DBMS). This course is designed for students and professionals interested in understanding the core concepts of database systems and developing the skills to design, implement, and manage databases and datasets for various applications.

  • The CSP Artificial Intelligence and High-Performance Computing and Ethical Considerations course offers an integrated study of the principles, techniques, ethical considerations and applications of artificial intelligence (AI) in combination with high-performance computing (HPC). This course is designed for students and professionals interested in harnessing the power of advanced computing technologies to develop and deploy AI solutions that can process vast amounts of data and solve complex problems at scale.

  • The CSP Cloud Architecture and Infrastructure course provides a comprehensive study of cloud computing principles, design methodologies, and best practices for architecting scalable and reliable cloud-based, hybrid, and multi-cloud solutions assisting global organizations design and build the architectures and infrastructures of the future. This course is designed for students and professionals interested in understanding how to design, deploy, and manage cloud infrastructure to meet the demands of modern global enterprises utilizing advanced applications and services.

  • Explore the fundamental principles and practices of data engineering, such as the building of tools and accessibility of data. By the end of the course, you will be equipped with the knowledge and skills to design, build, and maintain data pipelines.

  • This advanced-level course builds upon the foundational knowledge of data engineering principles and focuses on practical applications. By the end of the course, you will be able to apply data engineering solutions in real-world scenarios, address complex data challenges, and contribute to the success of data-driven organizations.

  • This course offers an in-depth exploration of two interrelated fields: big data and data mining. Learn to handle big data challenges, understand the fundamentals of data mining, and apply various data-mining techniques to massive datasets in real-world scenarios.

  • Study the techniques and methodologies used to predict future outcomes and trends based on historical data. Learn to effectively apply predictive analytics techniques, build accurate models, and use data-driven insights to make informed decisions across various domains, including marketing, finance, and healthcare.

  • This course shows you how to conduct empirical research and effectively communicate findings through data visualization. By the end of the course, you will be a valuable asset in any field that requires evidence-based decision-making and effective communication of insights.

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