Data Science in the age of AI Career Accelerator

Become the data scientist who ships real impact. Build a portfolio of real-world projects, master modern ML/AI (including GenAI), and get one‑to‑one career coaching.

7 months, part-time

100% online

~20 hours/week

12 months of 1:1 career coaching (during & after the program)

Bi‑weekly industry mentoring throughout the program

Certificate of Completion from Johns Hopkins University

"This is not a bootcamp; it's not where you go to learn to code, it's where you go to actually become a fully-fledged data scientist."

— Giwa, Career Accelerator Learner

STARTS

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Check if this is right for you

See if this program aligns with your career goals and help shape the curriculum.

The JHU Data Science in the age of AI Career Accelerator is currently in development. By expressing interest, you're helping the University assess market needs and shape the curriculum. Final program details subject to confirmation.

Featuring real-world projects from companies like:*

*Industry partners are subject to change.

During this program you will:

Gain advanced ML & AI skills, including NLP, time series, and practical GenAI workflows.

Deliver a 6‑week employer project that earns portfolio‑ready artifacts and industry feedback.

Earn a university‑backed credentiala valued by U.S. employers.

TARGET AUDIENCE

Who is this program for?

Career advancers in analytics, BI, or engineering who want to lead ML/AI workstreams

Career changers from quantitative fields (engineering, economics, physics, etc.) ready to switch into data science

Researchers/health professionals (fit for the JHU ecosystem) seeking to leverage data and AI for impact

Early professionals with strong fundamentals who want a structured path to 'job ready'

ACADEMIC EXCELLENCE

Why choose this Career Accelerator?

A portfolio employers notice

Tackle a sequence of scoped, business‑led projects culminating in a 6‑week employer project. You'll leave with case studies you can defend in interviews.

Modern ML/AI you'll actually use

Supervised/unsupervised ML, deep learning, NLP, time series, and GenAI (RAG, evaluation, prompt patterns, PEFT)—applied to real data.

Strong statistics, strong decisions

You'll develop statistical judgment (not just models) so you can frame problems, quantify uncertainty, and make trade‑offs leaders trust.

Commercial thinking baked in

Translate models into outcomes—experimentation, constraints, ROI, risk, and shipping to production.

Responsible AI and governance

Practical risk, privacy, bias, and compliance for regulated industries (healthcare, finance, public sector).

Human support end‑to‑end

Structured learning path, bi‑weekly mentoring, 1:1 carer coaching, and a community that keeps you moving.

JHU credibility

A Johns Hopkins certificate signals academic rigor and mission‑driven excellence to employers.

REGIONAL OPPORTUNITY

Built for the Baltimore–D.C.–Philadelphia corridor

Within ~150 miles of JHU you'll find one of the nation's densest data ecosystems—federal agencies, national labs, health systems, defense, consulting, fintech, and Big Tech.

Deep job base within ~124 miles

Washington–Arlington–Alexandria

~6,840 data scientists • $139,080 mean annual wage • LQ 1.74 (above‑average concentration)

Bureau of Labor Statistics

Baltimore–Columbia–Towson

~850 data scientists • $126,410 mean annual wage

Bureau of Labor Statistics

Philadelphia–Camden–Wilmington

~4,240 data scientists • $113,670 mean annual wage

Bureau of Labor Statistics

U.S. outlook remains exceptional

$112,590 median pay (May 2024) and 36% job growth (2023–33) with ~20,800 openings/year projected.

Bureau of Labor Statistics

"We're not just teaching data science—we're training the leaders who will reshape entire industries. In 7 months, our learners go from curious professionals to the data scientists that Fortune 500 companies are desperately seeking. That's the Johns Hopkins difference."

Dr. Sarah Mitchell

Professor of Applied Mathematics & Statistics Johns Hopkins University

REGIONAL JOB OPPORTUNITIES

Major employers nearby

Amazon HQ2 (Arlington)

25,000 jobs planned by 2030; 8,000+ employees already on site—is expanding the private‑sector tech footprint in the Capital Region.

Arlington County Virginia, arlingtoneconomicdevelopment.com

Johns Hopkins Applied Physics Laboratory (Laurel)

8,800+ staff working across national security, space, health, and AI.

JHU Applied Physics Lab

NIH (Bethesda)

A biomedical research hub supporting ~18,000 staff on the Bethesda campus and driving demand for data talent.

nems.nih.gov

CMS (Baltimore area)

Active recruitment for Data Science Careers to advance health equity and outcomes.

CMS

NASA Goddard (Greenbelt)

Careers in data science, cyber, and IT tied to Earth and space missions.

NASA

Ready to see if this program fits your goals?

Join the waiting list and help shape the curriculum. Get 12 months of career coaching to ensure your success.

CURRICULUM

Program Curriculum

Bridge the gap between theory and practice with a sequence designed for advanced, job‑ready impact.

Tools & Languages

Python (NumPy, pandas, scikit‑learn), SQL, matplotlib, TensorFlow/PyTorch, Git, cloud notebooks, LangChain/RAG workflows.

Course 1

Applying Statistics & Core Data Science in Business

  • Statistical thinking • hypothesis testing • experiment design
  • Feature engineering • unsupervised learning for segmentation/anomaly detection
  • From analysis to recommendation: narrative and stakeholder influence

Course 2

Solving Business Problems with Supervised Learning

  • Regression/classification • model tuning and ensembles
  • Evaluation and trade‑offs (accuracy, cost, fairness)
  • Intro to deep learning on tabular/text/image signals

Course 3

Advanced Techniques for Real‑World Impact

  • NLP (embeddings, transformers) • time‑series forecasting & anomalies
  • Pipelines/MLOps • monitoring, performance, and efficiency at scale

Course 4

The Future of Data Science + Employer Project

  • GenAI & LLMs in practice: prompt patterns, RAG, evaluation, PEFT, and RLAIF/RLHF concepts
  • Risk & governance in regulated environments
  • 6‑week employer project with live feedback—ship a portfolio‑ready case study

CAPSTONE PROJECT

Live employer project with industry leaders

Apply your skills end‑to‑end: problem framing → data wrangling → modeling → evaluation → business storytelling. Present to industry reviewers, iterate on feedback, and add a polished case study to your portfolio.

Focus areas you might explore

Generative AI & LLMs

RAG architectures, prompt evaluation, safety/guardrails

Frameworks & methods

experiment design, pipeline orchestration, monitoring

Real‑world applications

cost/latency trade‑offs, A/B test design, success metrics

EXPERT FACULTY & INDUSTRY MENTORS

Learn from leading experts

"Data science becomes valuable when models change decisions. Our focus is on that last mile—evidence, narrative, and adoption."

— Dr. Firstname Lastname | Academic Director, Johns Hopkins Universit

Dr. Ian McCulloh

Dr. Ian McCulloh leads AI Continuing and Executive Education at Johns Hopkins Engineering where he specializes in data science, network analysis, and artificial intelligence. He holds a PhD in computer science from Carnegie Mellon University.

Johns Hopkins University

Dr. Anthony (Tony) Johnson

Dr. Anthony (Tony) Johnson is a senior professional staff member and research scientist at the Johns Hopkins University Applied Physics Laboratory. He serves as a program manager in the Whiting School of Engineering.

Johns Hopkins University

Dr. Erhan Guven

Dr. Guven is an AI scientist at Johns Hopkins University Applied Physics Laboratory and assistant program manager in Johns Hopkins Engineering’s #1 ranked online master’s programs in AI and data science.

Johns Hopkins University, Johns Hopkins Applied Physics Laboratory

Dr. Jesus Caban

Jesus Caban is Chief Data Scientist in the Program Executive Office, Defense Healthcare Management Systems and instructor in Johns Hopkins Engineering’s #1 ranked online master’s program in Data Science.

Johns Hopkins University, Defense Healthcare Management Systems

LEARNER TESTIMONIALS

What our learners say

“The Data Science Career Accelerator is helping me to shape my thoughts to see a business problem with data as the background and applicable techniques as the foreground. It gave me the empowerment to face harder business problems with a conviction that with appropriate techniques comes higher business value.”

— Arijit

Career Accelerator Learner

“What stood out for this Career Accelerator over other programmes I looked at was the Employer Project - being able to experience what it's like working in an industry and being teamed up with an employer. I knew that I'd be getting taught skills that employers would really value, and a company like the Bank of England is really big.”

— Zari

Career Accelerator Graduate

“I said [to my Career Coach] I need this much salary to support my family, I want it to be in this kind of environment – and I hit all of those goals."

— James

Career Accelerator Graduate

“The highlights of taking the programme were the practical aspects of it – so having that direct industry input and being able to work on an actual Employer Project. Being able to show that on a CV and talk about it in job interviews later was definitely invaluable.”

— Megan

Career Accelerator Graduate

“The Career Accelerator has opened up a whole world that I never knew was out there before. I love what I do…but sometimes I felt like, "What’s next?". But now there’s so much opportunity – so many doors have opened up for me.”

— Haroon

Career Accelerator Graduate

“I like the support that you get from the Facilitator of the course, and from having an expert being there that you can ask questions. With a lot of self-taught stuff, you don't have that option to ask questions and get a rapid response that's tailored to your needs.”

— James

Career Accelerator Graduate

PROVEN RESULTS

Outcomes you can expect

Portfolio‑ready work that proves problem framing, modeling, and business impact

Confidence with modern ML/AI, including hands‑on GenAI patterns and evaluation

Career support that moves the needle—coaching, interview prep, GitHub/LinkedIn polish, and job‑search sprints

FourthRev learner outcomes (all Career Accelerators)

87.5%

achieve their desired career goal within 6 months

+21.9%

average salary increase reported post‑program

Source: FourthRev 2023/24 Completers' & Satisfaction Surveys. Online Career Accelerators

FREQUENTLY ASKED QUESTIONS

FAQs

  • How long is the program and what's the time commitment?

    7 months part‑time (~20 hours/week). Live sessions are scheduled for working professionals, with recordings available.

  • Is it fully online?

    Yes, delivered via a modern virtual learning environment—accessible on desktop and mobile.

  • What are the entry requirements?

    This is an advanced program. You'll need:

    • Undergraduate degree with quantitative work (e.g., math, stats, engineering, economics) or equivalent professional experience
    • Foundational skills in Python, SQL, and descriptive statistics
    • ~1 year of relevant experience (analytics, engineering, research, BI, etc.) preferred

    (If you're missing a prerequisite, we'll share prep resources during admissions. English proficiency may be required for non‑native speakers.)

  • How much does it cost?

    Tuition and flexible payment options vary by cohort—download the brochure or speak with an Enrollment Advisor for current pricing and financing.

  • What recognition do I receive?

    A Certificate of Completion from Johns Hopkins University upon successful completion of program requirements.

  • What's the role of employer partners?

    Employer partners shape project briefs, share tech expertise, and provide feedback on your work—so your learning stays tightly aligned to hiring demand. (Partners subject to change.)

Check if this is right for you

See if this program aligns with your career goals and help shape the curriculum

The JHU Data Science in the age of AI Career Accelerator is currently in development. By expressing interest, you're helping the University assess market needs and shape the curriculum. Final program details subject to confirmation.