Master of Science in Data Science
August 8, 2022 2024-12-12 10:37Master of Science in Data Science
The Masters in Data Science is an 18-month professional master’s program designed for students who want to begin or advance their careers in data science. Our industry-relevant curriculum gives you the skills to extract valuable insights from big data. This program equips you with expertise in statistical modeling, data management, machine learning, data visualization, software development, research design, data ethics, and user experience to meet the growing needs of industry, nonprofits, government agencies, and other organizations. Our students have high undergraduate grades and technical skills, but we look for more when forming our cohorts and welcome students from a variety of backgrounds and perspectives. Because of this, our programs can offer a unique lived experience.
At Birchwood, it costs an average of $325/credit to pursue your online Master of Science in Data Science. Invest in your future, not in a campus.
Personalizing your Master of Science in Data Science is easy. Pick a pathway based on your career goals, with support at every stage.
Take a different path and stand out from the crowd with Birchwood Online Master of Science in Data Science Program.
The Data Science Landscape
50X
1.5 Million
$108,000
90%
94% Students who say they've achieved their goals post graduation.
66% of students got a bigger role and 80% say Birchwood helped them get it.
Median salary increases +23% within 6 months of graduation.
Why choose a Master of Science in Data Science?
The Master in Data Science opens the door for your career in data-driven businesses. After your graduation, you are typically responsible for all aspects of transforming data into value, from designing the technical infrastructure to building advanced machine and deep learning models, as well as improving data quality and evaluating the performance of the predictions. It can also be your responsibility to help companies and teams to achieve their goals in becoming a predictive enterprise. In this case, you are responsible to identify potential use cases, performing the initial project planning, and defining the relevant measures and metrics to define success.
Admission Requirements
General Admission Requirements
Submission of a copy of valid government-issued picture identification.
Submission of a copy of an updated Resume.
Any document not in English must be accompanied by a certified translated copy.
Additional Admission Requirements for Master of Science in Data Science.
Submit a 500-word essay (Minimum) summarising the applicant’s interest in the program and their professional goals.
Provide an Official undergraduate degree transcript in business, marketing, management, operations management, statistics, or a related field with a GPA of 2.5 or higher.
Provide two (2) Professional Recommendation Letters.
A professional readiness interview will be conducted with the Director of Education if the GPA is below 2.5.
Admission Decisions & Process
We evaluate candidates on their academic background, career accomplishments, and the thoughtfulness and candor within their application. Ultimately, we look for driven, early-career professionals with business leadership potential.
Online Application
Online Assessment
Personal Interview
Entry Documents Verification
Final Committee Decision
Admission Application and Graduation Requirements
Application For Admission
All persons interested in applying for admission to the university should complete an application which must be accompanied by a non-refundable required application fee of $500.00 (check, money order, or credit card) to process the application. The check/money order should be made payable to Birchwood University. Applicants must submit all required application documents to be considered for admission. Once a decision is made, an email will be sent to the candidate with further instructions. Candidates will be contacted by their admissions agent regularly to ensure the completed documents are received by the office.
Graduation Requirements
To graduate from Birchwood University, and to receive a degree, the student must:
Complete all credits as stated in the catalog.
Earn a minimum 3.0 cumulative grade point average.
Meet satisfactory academic progress.
Fulfill all monetary obligations.
Master of Science in Data Science Course - Key Highlights
Earn a globally recognized online master’s degree equally credible as offline.
100% Online Programs
No campus visit required
24*7 Access
to World class advanced learning management system
World Class Curriculum
developed by experts from Leading MNCs
The Cohort Experience
build your professional network and establish connections across industries.
Program Description
Upon completion of the program, students will:
- Apply the necessary skills to communicate effectively, thoughtfully, and compassionately within the global Analytics field.
- Apply, synthesize, analyze, and integrate the knowledge of Data Science, Python, Machine Learning, and Artificial intelligence to arrive at innovative solutions to organizational problems.
- Demonstrate the skills to work in multicultural organizations within a globalized society.
- Demonstrate the ability to develop, analyze and communicate empirical scholarly work.
- Develop the competencies in Data Science
Program Curriculum
MDS500 | Python Programming | 4 Credit Hours
Gain insight into the Python Programming language with this introductory course. An
essential programming language for data analysis, Python, Programming is a fundamental
key to becoming a successful Data Science professional. In this course, you will learn how to
write python code, learn about Python’s data structures, and create your functions. After the
completion of this course, you can represent yourself as an ideal candidate for python
Developer
MDS510 | Data Base Management System | 4 Credit Hours
In this course, students will learn how to manage the Data Effectively using My SQL Work
Bench. Students will come to know how to Apply Certain Joins techniques, How to
manipulate the data. Will be able comfortably design SQL queries to add data to the database,
will be familiar with editing, deleting data from the database, and will be able to describe
and develop Relational Algebra and Relational Calculus queries.
MDS520 | R Programming | 4 Credit Hours
Gain insight into the R Programming language with this introductory course. An essential
programming language for data analysis, R Programming is a fundamental key to becoming
a successful Data Science professional. This course will teach you how to write R code, learn
about R’s data structures, and create your functions. After the completion of this course, you
will be fully able to begin your first data analysis
MDS530 | Exploratory Data Analysis | 4 Credit Hours
This course includes the necessary exploratory techniques for summarizing data. These
techniques are typically implemented before formal modeling begins and can help in
informing the development of numerous complex statistical models.
Exploratory techniques are also essential for eliminating or sharpening potential hypothesis
about the world that the data can address. In this course, we will study the plotting systems
and the basic principles of constructing data graphics. We will also cover some of the
standard multivariate statistical techniques used to visualize high-dimensional data
techniques are typically implemented before formal modeling begins and can help in
informing the development of numerous complex statistical models.
Exploratory techniques are also essential for eliminating or sharpening potential hypothesis
about the world that the data can address. In this course, we will study the plotting systems
and the basic principles of constructing data graphics. We will also cover some of the
standard multivariate statistical techniques used to visualize high-dimensional data
MDS540 | Machine Learning | 4 Credit Hours
Machine Learning course will make you an expert in Machine Learning, a form of Artificial
Intelligence that automates data analysis to enable computers to learn and adapt through
experience to do specific tasks without explicit programming. You will master Machine
Learning concepts and techniques, including supervised and unsupervised learning,
mathematical and heuristic aspects, and hands-on modeling to develop algorithms and
prepare you for your role with advanced Machine Learning knowledge.
Intelligence that automates data analysis to enable computers to learn and adapt through
experience to do specific tasks without explicit programming. You will master Machine
Learning concepts and techniques, including supervised and unsupervised learning,
mathematical and heuristic aspects, and hands-on modeling to develop algorithms and
prepare you for your role with advanced Machine Learning knowledge.
MDS550 | Machine Learning Model Deployment | 4 Credit Hours
Implementing models such as support vector machines, kernel SVM, Naive Bayes,
decision tree classifier, random forest classifier, logistic regression, K-means clustering,
and more in Flask, Sending and receiving the requests from deployed machine learning
models, Building machine learning model APls, and deploy models into the cloud,
Design testable, version-controlled, and duplicate production code for model
deployment.
MDS560 | Artificial Intelligence | 4 Credit Hours
The Artificial Intelligence course will expand your technical function and become an
expert in Artificial Intelligence that automates data analysis to enable computers to learn
and adapt through experience to do specific tasks without explicit programming. You
will master Al concepts and techniques, including, Deep Learning, mathematical and
heuristic aspects, and hands-on modeling to develop algorithms and prepare you for
your role with advanced Al knowledge. Also, it will help in understanding Convolution
Neural Networks Convolution, Pooling and Generative Networks Adversarial
Networks, and these skills will enable candidates to seek their career in their desired
companies.
• Data Visualization using Tableau – Tableau Course will help you master the
various aspects of the program and gain skills such as building visualization,
organizing data, and designing dashboards. You will also learn concepts of
statistics, mapping, and data connection. It is an essential asset to those wishing
to succeed in Data Science. After learning the tableau tool, one must be able to
display and analyze data. Also, it enables the users to create various reports and
presentations about data.
• Data Visualization using Power Bi – In this course, you will master the various
aspects of the program and gain skills such as building visualization, organizing
data, and designing dashboards utilizing data visualization using Power Bi. You
will also learn concepts of mapping, and data connection; users will be able to
provide clear and actionable insights in less than a minute. It also enables the candidate to import the data from multiple sources. And learn how to transform
the data. It is an essential asset to those wishing to succeed in Data Science.
MDS570 | Data Visualization Using Tableau/Power BI | 4 Credit Hours
In this course, students will learn about Introduction to Visualization, Rules of Visualization, Data Types, Sources, Connections, Loading, Reshaping, Data Aggregation, Working with Continuous and Discrete Data, Using Filters, Using Calculated Fields and parameters, Creating Tables and Charts, Building Dash Boards and story boards, Sharing Your Work and Publishing for wider audience, Introduction to Microsoft Power BI, The key features of Power BI workflow, Desktop application, BI service, File data sources
Sourcing data from the web (OData and Azure), Building a dashboard, Data visualization, Publishing to the cloud, DAX data computation, Row context, Filter context, Analytics pane, Creating columns and measures, Data drill down and drill up, Creating tables, Binned tables, Data modeling and relationships
Power BI components such as Power View, Map, Query, and Pivot.
Sourcing data from the web (OData and Azure), Building a dashboard, Data visualization, Publishing to the cloud, DAX data computation, Row context, Filter context, Analytics pane, Creating columns and measures, Data drill down and drill up, Creating tables, Binned tables, Data modeling and relationships
Power BI components such as Power View, Map, Query, and Pivot.
MDS600 | Capstone Project | 4 Credit Hours
The capstone project will allow you to implement the skills you learned throughout this
program. Through dedicated mentoring sessions, you’ll learn how to solve a real-world,
industry-aligned Data Science problem, from data processing and model building to
reporting your business results and insights. The project is the final step in the learning
path and will enable you to showcase your expertise in Data Science to future employers.
Additional
Information
Additional Information for Master of Science in Data Science Program
FAQs
Your Career Starts Here!
Take the first step.