MS in Data Analytics in USA

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• Mathematical Statistics
  In this module, get an introduction to fundamental statistical analysis. You will get access to on-campus lectures and practical problem-solving sessions.
   
• Linear Regression and Time Series
  Build an overview of linear regression and time series analysis. This course will help you understand data analysis and its interpretation.
  Learn the relationships between dependent and independent variables. You will also study time series analysis to see changes in data over time. It helps predict future trends.
   
• Python Programming* 
  This is an elective course that helps you enhance your knowledge of Python. Python is one of the most prevalent languages and is beneficial for IT professionals. In this course, you will learn about Python principles and their practical applications.
  This course benefits those seeking data management and IT/cyber data analysis careers. It includes case studies. These case studies focus on using Python learning to extract and analyze data. 
   
• Data Management for Information Technology
  In this course, you will learn about the principles of data management, visualization, data mining, and AIML. You can apply these principles to enterprise intelligence. This will end up improving business performance and bring competitive advantage.
   
• Fundamentals of Data Engineering
  This module provides an in-depth knowledge of data warehouse principles and concepts. Hands-on exercises will teach you to build prototypes, structures, and tables using the ETL process. ETL stands for Extract, Transform, and Load.
  In this course, you will learn to use SQL. You will also learn use of Business Intelligence (BI) tools to find patterns in data. Get a brief introduction to cloud data platforms and the modern data management ecosystem.
   
• Data Mining With Splunk
  Become familiar with the key concepts of business intelligence and Splunk Enterprise architecture. Work on hands-on sessions to learn it better. The course includes mining machine data, identifying data patterns, and creating Splunk reports.
  Splunk Enterprise is a platform that can harness and leverage valuable machine data. It helps enterprises with valuable business, operational, and security intelligence.
   
• Applied Machine Learning*
  This course investigates the fundamental technical aspects and practices of Machine Learning. You will receive lectures, lab sessions, written assignments, and programming projects. These will help you apply ML to practical problems in Data Science using Python. You will also receive an introduction to some fundamental theories of ML.
   
• Data Visualization and Storytelling  
  Learn how organizations make frequent and quick business decisions. In this course, you will understand the critical role of business intelligence in processing large amounts of data. You will also gain hands-on experience with Tableau to visualize data and derive meaningful insights.
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*These courses are waived off.

• Research and Marketing Analytics
  Explore marketing research, a tool that helps make sound marketing decisions for the business. Learn to make these decisions after gathering and analyzing the data. This course will cover topics like segmentation, targeting, positioning, pricing decisions, and more.
   
• IoT: Securing Communication Technologies through Data Analysis
  In this module, learn about design considerations, communication and networking technologies. You will also become familiar with the data analytics platforms. Know about IoT and its role in industries. 
  Understand the security issues that come with the rapid growth of IoT technology. Equip knowledge and skills to secure IoT systems by learning to use data analytics to improve their security.
   
• Applied Deep Learning
  Get a comprehensive education experience on deep learning applications in domains like image recognition, NLP, and sequential data analysis. Learn to leverage deep learning techniques in data analytics through hands-on applications. By completing this course, you will become proficient in practical coding skills. You will be able to use strategies for data-driven decision-making and complex problem-solving.
   
• Health Data and Record Systems
  Get an overview of the healthcare data landscape. Get aware of the history of the digital healthcare industry, and IT infrastructure. Learn about the opportunities in the health sector. Understand the usage of data sources with big data methods that impact healthcare positively.
   
• Special Topics: Data Analytics
  Special topics are the current topics in data analytics. These topics can vary from semester to semester. You might also get the same course for credit if they are different.
  
  Fall 2023 - Deep Learning- This course covers modern artificial intelligence algorithms based on deep neural networks. Starting with the basics of statistics and mathematics, it follows with in-depth knowledge. You will study different types of neural network architectures and their training algorithms. The course introduces the basic concepts of NLP and its usage in deep neural architectures. You will have access to several recent research papers and a comprehensive research project in the lectures.
  
  Spring 2024 - Applied Natural Language Processing- This course will introduce you to Natural language processing (NLP). NLP is a rapidly advancing domain. Its applications are notable across various domains, such as academia, government, and industries.You will understand the generative and non-generative models in NLP, their strengths, weaknesses, and use cases. Also, learn how these models function, their mechanisms, and their practical implications. The course highlights NLP's core issues and resolutions. It provides an understanding of computers' methodologies for interpreting and producing human language. This will be an interactive lecture series, and active student involvement is important.
  
  Note: You should do weekly prescribed readings to help you with lectures. All course content will be accessible via the online learning management system (LMS).
   
• Health Informatics
  Learn to approach practical health informatics applications within the healthcare industry. This might include physicians, hospitals, insurers, government agencies, research institutions, pharma, and more. In this course, you will understand how to conduct research and identify trends in health records. You will also learn to evaluate healthcare operations and measure healthcare financial performance.
   
• Independent Study
  To pursue independent study, you must contact your advisor before registration begins. The advisor will work with you to discuss and develop a substantive proposal. The proposal will include a short synopsis of the proposed study, assignments, a bibliography, and a description of the deliverables.
  The advisor approves the final version of the completed Independent Study form. It is then attached to a proposal. You must also add a detailed syllabus to the proposal. Forward the independent study form to the Assistant Dean for review and approval.
  The Registrar's Office will email you the CRN (course registration number). You are responsible for registering for online independent study. You can only submit these proposals for independent study during the first week of registration.
   
• Capstone Practicum
  This is the practical section of the course. It integrates the coursework of the MSDA program into a practical application. Under the supervision of a faculty instructor, you will address an actual challenge. This actual challenge can be the real challenge that an organization faces.
  You need to study the issues, review the industry and trends, and research the problem. You will also make recommendations to the organization's key members. In the end, you will have to make a formal written presentation. The faculty and organization professionals will review the final version of the presentation.