Python for Clinical Research
Master Python to clean, analyze, and automate clinical trial workflows — from data validation to regulatory-grade reporting and CDISC-aligned deliverables.
- On-demand video
- Downloadable materials
- Lifetime access
- Desktop, mobile & TV
- Certificate of completion
- Closed captions
- 30-Day Money-Back Guarantee
Why This Course?
This 6-hour, hands-on program turns Python into a practical tool for clinical data management and analysis. You’ll clean datasets, run reproducible analyses with Pandas and NumPy, build visualizations with Matplotlib, and learn how Python fits with CDISC standards (SDTM, ADaM) and regulatory expectations.
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$199.00
What You’ll Learn
- Enjoy Learning in Podcast Format
- Data cleaning & validation for clinical datasets
- Pandas & NumPy for analysis and wrangling
- Visualization & reporting with Matplotlib
- Automating common CDM workflows
- Reproducible notebooks for team reviews
- How Python supports CDISC (SDTM, ADaM)
Who Should Enroll?
SAS programmers, Clinical Data Managers, CRAs, Biostatisticians, Clinical Programmers, and newcomers who want job-ready Python skills for clinical research.
Course Curriculum
Introduction
- Welcome & Orientation Preview Free
Pre-Module
Module 1 — Getting Started with Python for Clinical Trials
- Lesson 1.1 The Evolving Landscape: Why Python in Clinical Trials? Enroll to unlock Locked
- Lesson 1.2 Setting Up Your Python Environment Enroll to unlock Locked
- Lesson 1.3 Basic Python Concepts for SAS Users Enroll to unlock Locked
Module 2 — Mastering Data Handling and Manipulation with Pandas & NumPy
- Lesson 2.1: Introduction to NumPy for Numerical Operations Preview Free
- Lesson 2.2: Pandas DataFrames: The Core of Clinical Data Enroll to unlock Locked
- Lesson 2.3: Importing and Exporting Clinical Data Enroll to unlock Locked
- Lesson 2.4: Data Cleaning and Preprocessing Enroll to unlock Locked
- Lesson 2.5: Data Transformation and Reshaping Enroll to unlock Locked
- Lesson 2.6: Grouping and Aggregation Enroll to unlock Locked
Module 3 — Statistical Analysis with Python
- Lesson 3.1: Descriptive Statistics and Data Summarization Enroll to unlock Locked
- Lesson 3.2: Hypothesis Testing with SciPy and Statsmodels Enroll to unlock Locked
- Lesson 3.3: Regression Analysis Enroll to unlock Locked
- Lesson 3.4: Survival Analysis with lifelines Enroll to unlock Locked
Module 4 — Data Visualization for Clinical Reporting
- Lesson 4.1: Fundamentals of Matplotlib Enroll to unlock Locked
- Lesson 4.2: Enhanced Visualizations with Seaborn Enroll to unlock Locked
- Lesson 4.3: Creating Common Clinical Trial Visualizations Enroll to unlock Locked
Module 5 — CDISC Standards and Python (SDTM & ADaM)
- Lesson 5.1: Introduction to CDISC Standards Enroll to unlock Locked
- Lesson 5.2: Mapping Raw Data to SDTM Domains (Conceptual & Practical) Enroll to unlock Locked
- Lesson 5.3: Generating ADaM Datasets with Python Enroll to unlock Locked
- Lesson 5.4: Basic Programmatic Validation for CDISC Compliance Enroll to unlock Locked
Module 6 — Advanced Topics & Regulatory Considerations
- Lesson 6.1: Introduction to Machine Learning in Clinical Trials Enroll to unlock Locked
- Lesson 6.2: Natural Language Processing (NLP) for Unstructured Data Enroll to unlock Locked
- Lesson 6.3: Automated Reporting and Document Generation Enroll to unlock Locked
- Lesson 6.4: Regulatory Compliance and Good Practices for Python Code Enroll to unlock Locked
Module 7 — Capstone Project & Next Steps
- Lesson 7.1: End-to-End Clinical Data Project Enroll to unlock Locked
- Lesson 7.2: Continuous Learning and Community Enroll to unlock Locked
Meet Your Instructor
Our lead instructor has designed training for cross-functional clinical teams and brings hands-on experience across clinical programming, biostatistics collaboration, and submission-ready documentation.
Certificate of Completion
Complete all modules and the final project to receive a verifiable digital certificate — great for LinkedIn and job applications.
“Clear, practical, and directly applicable to clinical research. The hands-on lessons saved our team weeks.” — Kira. A
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