Master of Science in Data Analytics

The ability to analyze data and make strategic decisions is critical to success in the modern workplace. The M.S. in Data Analytics from Nexford empowers you with the technical and data skills needed to lead organizations and unlock the true potential of data. Become a master of data analysis and shape the future of your career.

The Master of Science in Data Analytics (MSDA) program provides learners with the skills to leverage data to drive business strategy and value. The program combines data mining, programmatic data analysis, statistical modeling, and data visualization courses with a solid foundation of soft skills and business education to transform learners into data-driven decision-makers and leaders.

The industry urgently needs individuals with data analytics skills, and by obtaining a Master of Science in Data Analytics, you can acquire the necessary technical skills and business acumen to transition from an individual contributor to a leader. These skills and expertise will make you an exceptionally desirable candidate for new opportunities and professional growth.

Our MS in Data Analytics program not only equips you with a cutting-edge degree but also grants you exclusive access to the highly sought-after CompTIA Data+ certification. This industry-recognized credential validates your data expertise, making you a more competitive candidate and opening doors to exciting career opportunities.

By graduating with both a master's degree and the CompTIA Data+ certification, you'll showcase a comprehensive skill set that sets you apart in the data-driven job market.

Why Choose Nexford

Nexford is where global citizens learn the skills they need, at the moment they need them most. We help people move forward in their careers – and their lives. We're a Public Benefit Corporation based in Washington DC. Yes, we're for profit, but we prioritize public benefit over profit. Every time. Nexford aims to demonstrate a more effective way of aligning credentials to the workforce--one that is far better positioned to give any learner, regardless of starting point, an educational foundation for lifelong success. We do this through curricular innovation, leadership in learning analytics and the development of models and tools that enable personalization and impact at scale. We are a cross-disciplinary team of relentlessly optimistic, ambitiously creative, solution-oriented problem solvers who collaborate to uncover and develop new scalable ways to enable our internal and external partners to consistently drive learner impact using the latest technologies and innovative practices available.

Admission Requirements

All learners wishing to enroll in the Master of Science in Digital Transformation (MSDT) program must have:

• Bachelor’s degree in IT, business, or related field, or
• Bachelor’s degree and complete FDT5001 Foundations of Digital Transformation with a minimum grade of C or better

Program Courses

The Master of Science in Data Analytics (MSDA) program combines data mining, programmatic data analysis, statistical modeling, and data visualization courses with a solid foundation of soft skills and business education to transform learners into data-driven decision-makers and leaders.


Programming in R & Python

This course introduces programming with R and Python for data analysis and business analytics. Master the fundamentals of two powerful programming languages, R and Python, to effectively manipulate, analyze, and visualize data. Learn essential concepts such as variables, loops, functions, and data structures in Python while exploring R's statistical and graphical capabilities. Develop your skills through hands-on exercises and real-world examples, and gain the confidence to tackle complex data challenges. By the end of this course, you will be proficient in R and Python and ready to leverage their capabilities for data-driven decision-making in various industries and applications.

Data Modeling & Mining

Data Modeling and Mining provides you with an opportunity to learn about data mining methods and applications. In this course, you will learn basic concepts and tools for data mining, including data sources, data cleaning tools, methods, mainstream algorithms for data mining, statistical modeling, and popular tools for mining structured data and unstructured data. You will also learn how data mining can be effectively used in various application areas and industries to drive decisions and actions. Additionally, you will be provided with various opportunities to demonstrate your abilities in data modeling and mining by using the tools introduced in this course.

Applied Machine Learning for Business Analytics

This course is designed to provide learners with a deep understanding of the core principles, techniques, and applications of machine learning in the context of data-driven analytics. The course focuses on equipping students with the knowledge and skills required to develop, implement, and evaluate machine learning models that can be used to solve complex real-world problems in various industries, such as finance, healthcare, marketing, and supply chain management. Learners will explore a range of machine learning algorithms, including supervised and unsupervised learning techniques, reinforcement learning, and deep learning frameworks. They will also learn how to preprocess and analyze data, select appropriate features, and optimize model performance using evaluation metrics and validation strategies. Additionally, the course will cover ethical considerations and best practices in developing and deploying machine learning models.

Information Visualization & Communication

In this comprehensive and hands-on course on data visualization and communication, learners will master the art of transforming complex data into clear, compelling visual representations. Through a blend of theoretical concepts and practical exercises, learners will gain knowledge on the principles of effective data visualization, explore various visualization techniques and tools, and gain proficiency in selecting the right visualizations to convey their message. Additionally, students will delve into the psychology of visual perception and learn how to create impactful visual narratives that resonate with diverse audiences. By the end of the course, learners will possess the skills and confidence to create visually stunning and informative data visualizations, enabling them to effectively communicate insights and drive informed decision-making in any field or industry.

The Law & Ethics of Information Technology

This course offers a comprehensive understanding of the rapidly evolving field of IT's legal and ethical aspects, exploring the interplay between technology, law, and ethics. Topics covered include intellectual property rights, data privacy, cybersecurity, digital rights management, social media, artificial intelligence, and the societal impacts of emerging technologies. We'll also delve into ethical considerations and legal frameworks guiding IT decision-making. Join us to navigate this dynamic landscape while upholding legal and ethical principles.

The Art of Communication

What is the number one job skill American and global employees are lacking, according to LinkedIn CEO, Jeff Weiner? Communication. The Art of Communication is designed to strengthen and promote a leadership-driven communications model that extends from an audience centered communications approach. How do leaders persuade shareholders? How do leaders negotiate with clients and business partners across cultures?

This course introduces learners to a foundation in rhetorical awareness that will transfer through a variety of contexts, including corporate communications, public speaking, negotiation, and a range of executive leadership scenarios. Coursework includes genre analysis, professional writing, presentation design and delivery, and negotiation workshops.

Data Sciences for Decision Making

Learn the foundation of how to apply advanced analytics skills to complex data analysis and modes. You’ll build an understanding of design, data analytics tools, and advanced analytics translators to communicate complex data-related requirements between data engineers, business, and IT stakeholders.

The course examines four major areas; the momentum gains in the data and analytics revolution; the five elements of successful data analytics transformation; the mapping value in data ecosystems, and data analysis; the models of distribution.

Statistics for Business Analytics

This course provides students with a comprehensive understanding of statistical principles and their application in the field of business analytics. Through a combination of theoretical concepts and practical exercises, students will develop the skills necessary to collect, analyze, and interpret data, enabling them to make informed decisions in a data-driven business environment. Topics covered include probability theory, descriptive statistics, hypothesis testing, regression analysis, and data visualization. By the end of the course, students will be equipped with the knowledge and tools to utilize statistical techniques effectively, communicate insights to stakeholders, and contribute to data-informed decision-making processes.

Accounting and Financial Reporting

Accounting and Financial Reporting engages learners in applying the principles of corporate finance and accounting to business decision making.

Course topics include financial statements and other reports, the basics of financial forecasting and budgeting, accounting analytics, and the communications and vocabulary related to financial statements. Learners reconcile financial transactions and accounting records, and examine the implications of international differences in accounting frameworks and financial reporting requirements.

Corporate Sustainability

Before the year 2000, environmental management for a business was typically driven by the need to respond to restrictions imposed by environmental regulation; however, at the dawn of the new millennium, leading businesses began to change their concept of environmental management to look beyond simply meeting governmental dictates. These organizations began to evolve and utilize environmental strategy to create new ways of growing their business by bringing sustainability to the core of their business strategy.

This course explores how to effectively work in senior management today, executives need to be knowledgeable not only about their specific business functions, but also, how their business will be impacted by governmental regulations & policies, corporate sustainability initiatives, green marketing regulations, industry guidelines or ‘best practices’, new sustainable technologies, energy planning, environmental performance metrics, and required reporting on the environmental impact of their business unit.

Business Analytics

Analytics focuses on discovering the power of data-driven decisions in the competitive business landscape, harnessing the potential of their data in driving growth. The concepts in business analytics, such as data collection, data visualization, and statistical analysis, can be applied in the transformative journey of a data-driven organization. The course exposes learners to different analytical tools and techniques to be used to solve complex business problems, identify trends, and predict future outcomes. By mastering these essential skills, learners will become invaluable assets to any organization in any vertical looking to make data-driven decisions.

Business Analytics Capstone

The Business Analytics Capstone Project is an immersive, project-based learning experience that allows learners to apply what they’ve learned throughout the business analytics studies about how to make data-driven decisions to real business challenges organizations face. Throughout the course, the learner will tackle real-world business problems in several verticals, such as marketing, finance, operations management, human resources, and organizational management. The learner will utilize data-driven decision-making techniques, cutting-edge analytical tools, and strategic thinking. This capstone course will challenge learners to synthesize their understanding of data visualization, predictive modeling, and machine learning while honing their communication and presentation skills. By the end of the course, they’ll be better prepared to make better data-driven business decisions in the ever-evolving field of business analytics.

What You'll Learn

Big Data
Develop skills in managing, designing, and architecting large datasets to enable cross-functional teams to efficiently access and retrieve information for their work areas

Modern Tools
Build mastery in complex data analysis using advanced technologies such as SQL, Python, and R. Develop expertise in selecting the most suitable tools for each project.

Machine Learning
Apply machine learning and predictive modeling to real-world scenarios and gain valuable skills and experience to influence strategic decision-making.

Data Visualization
Learn how to present complex information in a simple way that non-technical team members can understand and use