Scholarship Program · Cohort Status

Data Analysis & AI Training Program

A fully-funded scholarship by Analysez AI — intensive training in data analysis, statistics, R programming, and AI-powered research workflows.

Delivered in Arabic·100% Online·Official Certificate
Join the waitlist Course outline
Training Cohorts Status
Cohort 1 — completed.
Cohort 2 — applications closed; training in progress now.

Want the next cohort? Join the waitlist

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The curriculum

From your first data point to the final report

Everything the program gives you, from the first session to your certificate.

Live communitydirect supportReal datasetsnot toy examplesWatch & rewatchduring the training period
01.

Data Types, Distributions & Descriptive Statistics

  • Data basics & formats: CSV, Excel, SPSS (.sav), variables, and column structuring
  • Variable types: numerical vs. categorical (ICD codes, Age, BMI)
  • Distributions: the normal curve and the 68–95 empirical rule
  • Central tendency & spread: mean, median, mode, variance, SD, and IQR
  • Normality testing: Shapiro–Wilk, histograms, and Q–Q plots
  • Univariate reporting: Mean ± SD vs. Median [IQR]
  • Hands-on: extract and audit baseline tables from 3 published papers
02.

Bivariate & Multivariate Inferential Analysis

  • Matching research questions to the right statistical test
  • Hypothesis testing: null/alternative hypotheses, significance, and p-values
  • Test families: parametric & non-parametric bivariate tests, ANOVA, Chi-Square, regression
  • Multiple comparisons: when and how to apply post-hoc corrections
  • End-to-end workflow: cleaning, missing values, EDA, and execution
03.

AI Agents & Computational Pipelines

  • AI chat vs. AI agents: conversational tools vs. autonomous frameworks
  • Agent ecosystems: Claude, Hermes, Codex, and a local OpenCode Agent setup
  • File formats for LLMs: why .md and .csv outperform .pdf and .docx
  • Coding ecosystems: the statistical roles of Python, R, and Shell
  • Pipeline generation: prompting agents to write, debug, and run reproducible scripts
  • Guided Analysez AI walkthrough
04.

Live Practical Capstone — Real Dataset Walkthrough

  • Live end-to-end cleaning, EDA, and statistical testing on a raw clinical dataset
  • OpenCode workflow: live script generation, terminal execution, and output debugging
  • Analysez AI workflow: the same dataset in Analysez AI — speed, ease, and reporting quality compared
  • Post-course assessment briefing: exam guidelines, dataset delivery, submission format, and grading rubric
Muhammed Elnaggar

Instructor

Muhammed Elnaggar

Founder & Lead Biostatistician, Analysez AI

After the training

Certification Exam

An independent submission after completing Session 4.

1

Clean a provided raw dataset and handle variable encoding

2

Generate a publication-ready Table 1 (baseline characteristics)

3

Select, justify, and execute the correct inferential models

4

Submit a verified, reproducible R/Python script with your findings summary

Score ≥ 80% → Official Certificate of Completion
50% discount voucher toward an Analysez AI subscription

Cohort Status

Applications closed

Cohort 1 — completed.
Cohort 2 — applications closed; training in progress now.
Cohort Status

Want the next cohort? Join the waitlist

Cohort 1 is completed. Cohort 2 applications are now closed and training is currently underway. Join the waitlist to receive priority notification when the next cohort opens.

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