MS in Data Science by Birchwood University

Smart Pathway through PGP in Generative AI and Agentic AI

  • Earn dual credentials within 12 months instead of standard 24 months 
  • Fast-track your MS journey through an RPL-enabled (Recognition of Prior Learning) pathway
  • Dual Credential Phase 1: Earn PGP in Generative AI and Agentic AI  in 6 months
  • Dual Credential Phase 2: Accelerated MS in Data Science from Birchwood University 
  • Earn 30 Academic Credit Hours upon successful completion of the PGP in Generative AI and Agentic AI
  • Learn through a perfect blend of live online and asynchronous learning modules
  • Build hands-on expertise in GenAI, Agentic AI, ML and Data Science through practical projects and real-world applications
  • Make advanced technical education more accessible with introductory pricing and upfront payment benefits
2209 Learners 4.9 102 Ratings

Earn two career-defining certifications within 12 months through our RPL enabled learning pathway. Begin with a 6-month PGP in Generative AI and Agentic AI, then progress to an accelerated MS in Data Science from Birchwood University. Learn through live and self-paced modules, work on real projects, and join us now to get a special combo price.

Program Highlights

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Two Credentials. One Accelerated Journey

Earn a PG certificate in GenAI & Agentic AI and progress towards a full MS in Data Science through a single integrated pathway.

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Alumni Status on Completion
Successful program completion grants full alumni status, providing ongoing access to networking platforms, professional events, and exclusive alumni benefits.

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Accelerated Completion in 12 Months
The program is structured for rapid progression, enabling completion within approximately 12 months while accommodating professional and personal commitments.

Program Learning Track

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Market Opportunities

$279 B

MARKET SIZE
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The global artificial intelligence market is estimated at USD 539.5 billion in 2026 and projected to reach approximately USD 3.5 trillion by 2033

- Grand View Research

35%

Job Growth
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Employment of data scientists in the United States is projected to grow by 35% between 2025 and 2035, significantly faster than the average for all occupations

- Bureau of Labor Statistics

$184.8 K

Average Salary
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The average annual base salary for AI Engineers in the United States is approximately USD 184,800, reflecting the market value of specialized AI expertise

- builtin.com

PHASE 1 PROGRAM STRUCTURE

Post Graduate Program in Generative AI and Agentic AI

  • Module 1: Python Programming Essentials
  • Module 2: Data Structures, Control Flow, and File Operations
  • Module 3: Advanced Python Concepts
  • Module 4: Numerical Computing and Data Analysis with NumPy and Pandas
  • Module 5: Data Visualization with Matplotlib and Seaborn
  • Module 6: Building AI APIs and Backends with FastAPI
  • Module 7: Building AI Native Applications with Streamlit and Gradio
  • Module 8: AI Pair Programming Fundamentals with GitHub Copilot

  • Module 1: Generative AI and LLM Foundations
  • Module 2: Transformer Architectures and How LLMs Work
  • Module 3: Working with LLMs: APIs, SDKs, Parameters and Open-Source Models
  • Module 4: Prompt Engineering Essentials
  • Module 5: Advanced Prompting Techniques
  • Module 6: Context Engineering: Memory, Windowing and Retrieval
  • Module 7: Structured Outputs, Function Calling and Tool Use
  • Module 8: Prompt Optimization, Evaluation and DSPy

  • Module 1: Embeddings and Semantic Search
  • Module 2: Working with Vector Databases
  • Module 3: Developing RAG Systems
  • Module 4: Advanced RAG: Hybrid Retrieval, Re-ranking and Agentic RAG
  • Module 5: Building LLM Apps with LangChain and LlamaIndex
  • Module 6: Multimodal LLMs and Beyond
  • Module 7: Building and Deploying End-to-End GenAI Applications
  • Module 8: Securing LLM Applications: Guardrails, Safety and Prompt Injection Defense
  • Module 9: Evaluating GenAI Applications
  • Module 10: Fine-Tuning and PEFT

  • Module 1: Agentic AI Foundations and Agent Architectures
  • Module 2: LangChain Core — Chains, Memory and RAG
  • Module 3: LangChain Agents and Tool Use
  • Module 4: LangGraph — Stateful Workflows and Routing
  • Module 5: LangGraph — Cycles, Human-in-the-Loop and Persistence
  • Module 6: Multi-Agent Orchestration with CrewAI
  • Module 7: Multi-Agent Systems with Microsoft AutoGen
  • Module 8: Agentic RAG and GraphRAG for Agents
  • Module 9: Deep Agents — Reflection, Planning and Long-Term Memory

  • Module 1: Model Context Protocol — Architecture and Custom Servers
  • Module 2: MCP Ecosystem Integrations
  • Module 3: Agent Interoperability — A2A Protocol 
  • Module 4: Agent Interoperability — ACP and ANP
  • Module 5: Evaluation and Tracing with LangSmith
  • Module 6: AI Guardrails and Safety — NeMo and Guardrails AI
  • Module 7: Fine-Tuning and Agent Performance Optimization
  • Module 8: Dockerizing and Deploying AI Agents

  • Module 1: Agentic Workflows with n8n
  • Module 2: Workflow Automation with Zapier
  • Module 3: Building with Make
  • Module 4: No-Code Agentic AI with Flowise

  • Module 1: Foundations of MLOps and LLMOps
  • Module 2: LLM Infrastructure, Tooling and the Open-Source Stack
  • Module 3: Deployment, Containerization and Scaling of LLM Systems
  • Module 4: Monitoring, Governance and Responsible AI in Production

  • Design, create and deploy end-to-end agentic AI applications

  • Module 1: Vibe Coding Fundamentals and AI Driven Development
  • Module 2: AI-Powered Development with Cursor AI
  • Module 3: AI-Native Software Development with Google Antigravity
  • Module 4: Accelerating Development with Amazon Q Developer

  • Module 1: NLP Foundations and Text Processing
  • Module 2: Feature Engineering and Text Representation
  • Module 3: Tokenization, Embeddings and Text Encoding
  • Module 4: Sentiment Analysis and Text Classification
  • Module 5: Neural Language Models and Sequence Modelling
  • Module 6: Transformers and the Path to Large Language Models

  • Module 1: Introduction to Claude and the Anthropic Model Family
  • Module 2: The Anthropic API — Messages, System Prompts and Tool Use
  • Module 3: Claude Code and Agentic Development with Claude
  • Module4: Claude with MCP

PHASE 2 PROGRAM STRUCTURE

MS in Data Science by Birchwood

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.

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.

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.

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 hypotheses about the world that the data can address. In this course, we will study 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.

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.

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.

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 data from multiple sources. And learn how to transform the data. It is an essential asset to those wishing to succeed in Data Science.

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.

Program Certificate

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The actual certificate might slightly differ from the sample certificate

Same Master as On Campus: Receive the same world-class education and global recognition as on-campus doctorates without the need to relocate. Globally Recognized US Degree: Birchwood University is licensed by the Florida Commission for Independent Education, Florida Department of Education.

Lifetime Alumni Status: Join an alumni network of professionals, many of whom hold key leadership roles across the globe.,

Program Fees

Post Graduate Program in Generative AI and Agentic AI
$2,599
MS in Data Science by Birchwood
$11,850
Total Price: $14,449
Total Price: $14,449
Limited Time Discounted Introductory Fee on Upfront Payment*

Payment Options

The Indian pricing is inclusive of GST for all learners.
*Above fee applicable only for full upfront payments and until offer lasts.
Finance (EMI) option is available for learners who prefers flexible payment options.

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Frequently Asked Questions (FAQs)

  • Birchwood University takes pride in its focused approach to education, concentrating on key domains that drive the future. The university aligns its programmes with the evolving needs of the professional landscape. It caters to a diverse range of academic pursuits, offering programmes from Bachelors to Doctoral levels.

    This comprehensive spectrum allows students to embark on their educational journey with the university and progress seamlessly through various stages of academic advancement. The university engages students in research activities, encouraging them to explore, innovate, and contribute to the body of knowledge in their respective fields.

    The University stands at the forefront of futuristic education, specializing in Data Science, Cyber Security, Software Development, and Management courses. Birchwood University, authorized by the Commission of Independent Education (CIE) in Florida, USA, holds a prestigious position in the global education landscape.

    Birchwood University is committed to delivering outstanding teaching and research pedagogy to students worldwide. Understanding the evolving landscape of education, Birchwood University invests in ongoing faculty training. The goal is to equip faculty members with the necessary tools and knowledge to provide an enriching and supportive educational experience to students.

    • 1. Offers a globally oriented MS in Data Science programme designed to prepare professionals for emerging opportunities in Data Science, Artificial Intelligence, and Machine Learning.
    • 2. Opens pathways to careers in leading technology companies, multinational corporations, consulting firms, financial institutions, and data-driven organisations.
    • 3. Provides strong earning potential, with growing demand for skilled professionals in Data Science, Generative AI, Machine Learning, and AI engineering.
    • 4. Prepares professionals to solve complex business challenges through data-driven decision-making, predictive analytics, and intelligent AI-powered solutions.
    • 5. Enables career growth across specialised roles such as Data Scientist, Machine Learning Engineer, AI Engineer, Data Science Consultant, and AI Solutions Architect.
    • 6. Supports opportunities in technology consulting, AI solution development, advanced analytics, and digital transformation across global industries.
    • 7. Equips graduates with the technical and analytical expertise needed to lead data-driven initiatives, manage AI projects, and contribute to organisational innovation.
    • 8. Combines advanced Data Science education with practical Generative AI and Agentic AI capabilities through an accelerated pathway, enabling professionals to build expertise in emerging technologies while earning two qualifications.

  • The Birchwood University Online MS in Data Science – PGP in Generative AI and Agentic AI pathway offers a smarter, more industry-relevant way to earn a master's qualification while building expertise in two of today's most in-demand technology domains – Generative AI and Agentic AI. Learners begin their journey with the PGP in Generative AI and Agentic AI, featuring a blend of live, synchronous sessions and asynchronous learning modules designed to help professionals develop practical skills in Large Language Models (LLMs), Generative AI applications, intelligent AI agents, and real-world AI solutions. On successful completion of the six-month PGP, learners earn a postgraduate certificate with 30 academic credit hours and become eligible to progress into the accelerated MS in Data Science programme from Birchwood University, subject to the university's admission requirements.

    What makes this pathway distinctive is that the learning does not stop with the PGP. Through the Recognition of Prior Learning (RPL) framework, eligible learners can apply their prior learning and earned credits towards the MS in Data Science programme, allowing them to complete the remaining academic requirements for the master's qualification. This enables working professionals to first gain a valuable qualification in emerging AI technologies and then build on that foundation to earn an MS in Data Science qualification – through an accelerated pathway designed to complete both programmes in just 12 months instead of the standard 24 months. It is a pathway designed for professionals who want to stay ahead of the rapidly evolving AI and Data Science landscape while investing their time in qualifications that deliver immediate practical skills and long-term career value.

  • The Integrated MS + PGP Program in Data Science & AI combines two complementary qualifications: the Post Graduate Program in Generative AI and Agentic AI by Edureka and the Master of Science in Data Science from Birchwood University.

    The program follows a two-phase learning pathway.

    Phase 1: Learners complete a 6-month PGP focused on Generative AI, Agentic AI, LLM applications, Python, AI workflow automation, and practical AI development.

    Phase 2: Learners progress to an accelerated MS in Data Science covering programming, statistical analysis, Machine Learning, Artificial Intelligence, model deployment, and data visualization.

    Through the Recognition of Prior Learning (RPL) pathway, eligible learners can complete both qualifications within approximately 12 months instead of pursuing them separately over a conventional 24-month period.

    Each qualification is awarded only after successful completion of its respective academic and assessment requirements.

  • Recognition of Prior Learning (RPL) is an academic process that recognizes knowledge, skills, and competencies acquired through previous education, professional experience, or other relevant learning activities.

    In this integrated pathway, RPL can help eligible learners avoid repeating learning outcomes they have already achieved. Depending on academic assessment, this may result in credit recognition, module exemptions, or other approved progression arrangements.

    By integrating the PGP in Generative AI and Agentic AI with the MS in Data Science, the program provides a structured pathway designed for completion within 12 months.

    All RPL decisions are subject to the academic policies, eligibility requirements, and approval of Birchwood University.

  • We evaluate candidates based on their educational background, professional experience, and readiness to undertake the programme.

    The selection process involves the following steps:

    1. Application Submission: Complete and submit the online application form with the required details.

    2. Document Verification: Submit relevant academic and professional documents for verification.

    3. Eligibility Assessment: The admissions team reviews your educational qualifications and eligibility for the programme.

    4. Profile Evaluation: Candidates are assessed based on their academic background, professional experience, and motivation to pursue the programme.

    5. Selection Confirmation: Shortlisted candidates receive confirmation of their selection following the evaluation process.

    6. Admission and Enrolment: Selected candidates receive an admission offer and can complete the enrolment formalities to begin their learning journey.

  • Applicants should have a bachelor’s degree in a relevant field (such as Computer Science, IT, Engineering, Mathematics, or Statistics). Prior experience in analytics, data, or programming is beneficial but not mandatory.

  • The program follows a blended learning model, combining live online sessions, self-paced learning, and hands-on industry projects.

  • Learners are not required to complete two separate projects. The Capstone Project completed as part of the PGP program can also be used to earn credentials in the MS program.

  • The PGP and MS programs operate as independent academic tracks. If a learner qualifies for the MS program but does not meet the requirements of the PGP, they will receive only the MS degree. Learners must successfully complete the graded components of each program individually to earn the respective degree or certificate.

  • No. Both programs are designed specifically for working professionals and therefore do not include placement assistance or career support services.

  • No. The program does not include any form of campus immersion.

  • You can withdraw and claim a refund at any time up to 48 hours after your cohort’s first live session.

    Refunds are paid less a processing fee of ₹10,000 (US$150 for international participants). After that period, no refund is payable, but you may defer once to a later cohort.

    Deferring: You can defer once to a later cohort free of charge at any time before your cohort begins. After it begins, one transfer is available in any three-month period, subject to seat availability, for ₹10,000 (US$150).

    How to request: Write to learner.support@edureka.co from your registered email address. We will give you a decision within 7 working days, and process an approved refund within a further 7 working days. If you disagree with a decision, write to grievance@edureka.co and we will respond within 3 business days.

    The terms that apply: The terms published here apply to your enrolment. If anything different has been described to you, please ask us to confirm it in writing before you enrol. Full terms are available on our Terms & Conditions page.

  • The program does not include placement support services.
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