Scholarship Program · August 2026 cohort

Data Analysis & AI Training Program

Delivered in Arabic·100% Online·Official Certificate
Apply Now Course outline
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

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Training starts after the September intake
Applicants are notified after the September cohort closes
Cohort 2 — August 2026

The next cohort opens in August

Cohort 1 filled fast — over 130 researchers applied. Leave your email and we'll notify you the moment applications for the August cohort open, so you don't miss your place.

We'll only email you about the training program — no spam, and you can unsubscribe anytime.