Explore a free healthcare and pharmacy data analytics virtual internship. Review project milestones, data practices and portfolio submission guidance.
Use public, synthetic, or properly de-identified datasets. Never publish patient identifiers, private records, or confidential workplace material in a repository or walkthrough.
These are the published project topics and deliverables. Your selected duration determines the required tasks in your workspace; use each task brief for its materials and evidence requirements.
Download your official Offer Letter from your workspace, format a professional LinkedIn announcement tagging #EdBytes, and submit your live public post URL for mentor verification.
Clean and standardize synthetic outpatient clinic patient records in Excel or Google Sheets, calculating appointment wait times, no-show rates, and department patient volumes.
Analyze a synthetic clinical patient dataset in Python using Pandas to explore demographic breakdowns (age, gender, diagnosis cohorts) and evaluate treatment recovery rates.
Write 4 straightforward SQL queries on a hospital database table to filter patients by diagnosis, calculate average hospital stay, and identify top medication costs.
Create a visual clinic overview dashboard in Google Looker Studio displaying total patients treated, departmental patient breakdown bar chart, and average recovery days score.
After your required tasks are approved, your workspace shows the optional certificate and evaluation report, its saved price and download availability. Public verification distinguishes registration from an issued credential; it does not guarantee employment or accreditation.
This healthcare and pharmacy data analytics virtual internship brings a domain-specific lens to project analysis. Explain the meaning of each measure, check the assumptions behind your calculations, and make the relationship between the dataset and the question explicit. The work is educational; a project result is not a clinical recommendation.
Use public, synthetic, or properly de-identified datasets. Never publish patient identifiers, private records, or confidential workplace material in a repository or walkthrough.
This educational project track is for students and early-career learners who want to practise healthcare & pharmacy data analytics and document their own work. Check the milestone tools and prerequisites against your current skills. Participation is not employment or a promise of placement.
Registration offers 7-, 15-, 30-, 45-, and 60-day options. Your selected programme and active workspace determine the required tasks and deadline. The published milestones show the project topics; check your workspace for the tasks assigned to your enrolment.
Enrolment, learning materials, submissions, and mentor feedback are free. The certificate is optional. Its price is saved when you register; a saved ₹0 price requires no certificate payment. Check its current price in your workspace; see the terms and refund policy before purchasing.
Submit the evidence named in the task brief, such as a repository, prototype, report, public post, or walkthrough. Open each link while signed out and document your own contribution. Follow the project proof checklist before sending it for review.
