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Woodcroft University was founded with a mission to make high-quality education accessible to learners everywhere. Built for the digital era, Woodcroft embraces innovation, flexibility, and global connection, offering students a modern academic experience grounded in excellence. Through immersive online learning, industry-aligned programs, and a diverse international community, Woodcroft continues to empower learners to grow, advance, and create meaningful impact in their fields. 

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St. Petersburg, FL 33702, USA info@woodcroftedu.us
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7901 4th St N, Suite 300,
St. Petersburg, FL 33702, USA

Email

info@woodcroftedu.us

Phone Number

+1 850-312-3081

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Master's in Data Science

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Program Overview

The Master’s in Data Science at Woodcroft University is a comprehensive, industry-aligned graduate program designed for learners seeking advanced expertise in data analytics, machine learning, artificial intelligence, and large-scale data systems. The program combines strong theoretical foundations with applied, real-world problem solving, enabling students to translate complex data into meaningful insights and strategic decisions.

This program is ideal for graduates and working professionals aiming to advance into high-impact data roles across technology, finance, healthcare, consulting, research, and emerging AI-driven industries. Learners gain hands-on experience with modern data science tools, programming frameworks, cloud platforms, and analytical methodologies used globally.

Delivered through Woodcroft’s fully online learning ecosystem, the Master’s in Data Science offers a flexible yet academically rigorous pathway—supported by expert faculty, virtual labs, industry-relevant projects, and continuous academic mentorship—allowing students to upskill without interrupting their professional commitments.

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Why Choose Woodcroft University for Your Master’s?

🌐 Industry-Relevant Curriculum

Curriculum aligned with current industry standards, tools, and practices in data science, AI, and analytics.

👩‍🏫 Expert Faculty & Academic Mentorship

Learn from experienced faculty with strong academic credentials and real-world data science expertise.

🧪 Hands-On Learning & Virtual Labs

Access cloud-based environments, real datasets, and applied projects to build practical competence.

📚 Flexible, Online, Career-Focused

Designed for working professionals with structured modules, recorded lectures, live sessions, and project-based assessments.

🌍 Global Learning Community

Collaborate with learners from diverse professional and geographic backgrounds.

Program Outcomes

Graduates of the Master’s in Data Science will be able to:

  • Apply statistical, analytical, and machine learning techniques to real-world datasets
  • Design and evaluate predictive and prescriptive models
  • Work with structured and unstructured data using modern data tools
  • Implement end-to-end data science pipelines
  • Communicate data-driven insights to technical and non-technical stakeholders
  • Demonstrate industry-ready skills through applied projects and capstone work

Curriculum Structure

Quarter 1 — Foundations & Data Engineering (Months 1–3)

(Compressed but rigorous foundations)

Courses

  1. Mathematics & Statistics for Data Science Programming for Data Science (Python, R, SQL) Data Engineering & Management Systems
    • Linear algebra, probability, regression, optimization
    • Students will: mathematically interpret ML models and outputs
    • Data pipelines, Pandas, NumPy, SQL querying
    • Students will: build reusable data-processing workflows
    • Relational + NoSQL databases, ETL pipelines
    • Students will: design scalable data architectures

Quarter Deliverables

  • 2 programming assignments
  • 1 statistical analysis project
  • Data pipeline mini-project

Quarter 2 — Core Machine Learning & Analytics (Months 4–6)

(Full ML depth delivered intensively)

Courses

  1. Machine Learning Algorithms & Modeling
  • Supervised, unsupervised, evaluation metrics
  • Students will: train, test, and benchmark predictive models
  1. Feature Engineering & Model Optimization
  • Data cleaning, dimensionality reduction, tuning
  • Students will: improve model performance and robustness
  1. Time Series Analysis & Predictive Analytics
  • ARIMA, forecasting, sequential data
  • Students will: build forecasting models for real datasets

Quarter Deliverables

  • End-to-end ML project
  • Forecasting case study
  • Model evaluation report

Quarter 3 — Advanced AI, Big Data & Cloud (Months 7–9)

(High-impact advanced specialization)

Courses

  1. Deep Learning & Neural Networks
    • CNNs, RNNs, Transformers
    • Students will: develop deep learning models
  2. Natural Language Processing (NLP)
    • Text mining, embeddings, language models
    • Students will: build NLP-based applications
  3. Big Data & Cloud-Based Data Science
    • Spark, distributed systems, cloud ML pipelines
    • Students will: deploy scalable analytics systems

Quarter Deliverables

  • Deep learning project
  • NLP application
  • Cloud deployment assignment

Quarter 4 — Ethics, Strategy & Capstone (Months 10–12)

(Professional readiness & mastery)

Courses

  1. Ethical AI, Governance & Data Privacy
    • Bias mitigation, explainable AI, compliance
    • Students will: design responsible AI systems
  2. AI for Business & Decision Systems
    • Data-driven strategy, executive analytics
    • Students will: translate analytics into business impact

Master’s Capstone Project (Runs Months 10–12)

(Major academic component)

Capstone Requirements

  • Real-world problem statement
  • Data collection & preprocessing
  • Model development & validation
  • Cloud-based implementation (where applicable)
  • Final technical report + presentation

Domains include finance, healthcare, smart cities, cybersecurity analytics, and public data.

View Syllabus View Curriculum

Admission Requirements

Admission Requirements

General Requirements

  • Completed online application
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline
  • Applicants from other backgrounds may be considered with foundational coursework
  • Academic transcripts
  • Government-issued ID

Preferred (Not Mandatory)

  • Prior exposure to programming or statistics
  • Relevant professional experience

Learning Format & Tuition

Learning Format

🎓 Learning Delivery, Tuition & Financial Support

100% Online Delivery
Designed for flexibility without compromising academic rigor. The program is delivered entirely online through Woodcroft University’s digital learning ecosystem.
Includes:
  • Recorded lectures and structured learning modules
  • Live interactive sessions with faculty
  • Guided projects and graded assignments
  • Virtual laboratories and cloud-based tools
  • Continuous academic and faculty support

Tuition & Fees

  • Tuition per year (Domestic): $19,999
  • Tuition per year (International): $29,999
  • Research & Technology Fee: $999 per term
  • Graduation Fee: $499

Scholarships & Assistantships Available

Woodcroft University offers multiple financial support options to eligible students:
  • Merit-based scholarships
  • Academic excellence awards
  • Need-based tuition assistance
  • Limited project-based assistantships (subject to availability and academic performance)

🚀 Career Readiness & Industry Alignment

The Master’s in Data Science is designed to prepare learners for real-world data and AI roles, with a strong focus on applied skills, professional relevance, and career progression.
Key Highlights:
  • Industry-aligned curriculum mapped to current data science roles
  • Hands-on projects using real-world datasets
  • Capstone project demonstrating end-to-end problem solving
  • Exposure to modern tools used in analytics, AI, and machine learning
  • Career-oriented skill development without unrealistic job guarantees
Graduates complete the program with a portfolio of practical work, strong analytical foundations, and the ability to contribute effectively in data-driven teams across industries.

Career Pathways, Technology Requirements & Student Support

Career Pathways

Career Pathways

Graduates of the Master’s in Data Science pursue roles such as:

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • AI Associate / Engineer
  • Analytics Consultant
  • Research Analyst

Technology Requirements

To ensure optimal participation:

  • High-speed internet connection
  • Laptop/Desktop (minimum 8GB RAM; 16GB recommended)
  • Windows, macOS, or Linux OS
  • Ability to run Python-based tools and cloud platforms

Student Support Services

Woodcroft University provides:

  • Academic advising & faculty mentorship
  • Technical support (LMS & tools)
  • Career development guidance
  • Project and capstone supervision
  • Virtual library and learning resources

Frequently Asked Questions

This is a full Master’s degree awarded by Woodcroft University. It follows graduate-level academic standards and includes advanced coursework, applied labs, and a formal capstone project. It is not a certification or short-term training program.

This is an accelerated Master’s program designed for high-performing students and working professionals. The curriculum covers the same depth as traditional 18–24 month programs but is delivered through an intensive structure with higher weekly academic workload.

Students should expect to dedicate approximately 15–20 hours per week to lectures, labs, assignments, and projects. During capstone periods, the workload may increase.

Yes. The Master’s in Data Science is delivered 100% online, including lectures, labs, assessments, mentoring, and the capstone presentation. No campus visits are required.

Live sessions are recommended but not mandatory. All sessions are recorded and available for asynchronous access. However, active participation contributes to academic performance and learning outcomes.

Prior exposure to Python, SQL, or basic programming is recommended but not mandatory. Foundational programming modules are included to ensure all students reach the required competency level.

Yes. Students complete multiple applied projects, case studies, and a final capstone project using real-world datasets across domains such as finance, healthcare, smart cities, and AI applications.

An optional virtual internship or applied industry project is available to eligible students. Internship availability depends on performance, program eligibility, and industry partner requirements.

Assessments include:

  • Programming assignments
  • Applied projects
  • Case studies
  • Quizzes and evaluations
  • Final capstone project and presentation

All assessments are conducted online.

Graduates receive a Master’s Degree in Data Science from Woodcroft University. The degree is issued physically and delivered to the registered address. Digital verification is also available through the University portal.

Student Reviews — Student Reviews — Master’s in Data Science at Woodcroft University

“Well-structured and practical.”

The curriculum is well-paced and practical. The capstone project helped me apply machine learning concepts to real datasets confidently.

— Rohan Malhotra, Florida, USA

“Excellent balance of theory and application.”

The program covers both foundational theory and modern tools. Faculty feedback on assignments was detailed and constructive.

— Emily Watson, UK

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